Bizuayehu Tesfaye
REYST report 05-2011
Bizuayehu Tesfaye Im
proved Sustainable Power Supply
RE
YS
T rep
ort 05-2011
Improved Sustainable Power Supplyfor Dagahabur and Kebridahar Town
of Somalia Region in Ethiopia
REYKJAVIK ENERGY GRADUATE SCHOOL OF SUSTAINABLE SYSTEMS
Reykjavík Energy Graduate School of Sustainable Systems (REYST) combines the expertise of its partners: Reykjavík Energy, Reykjavík University and the University of Iceland.
Objectives of REYST:Promote education and research in sustainable energy
earth sciences
REYST is an international graduate programme open for students holding BSc degrees in engineering, earth sciences or business.
REYST offers graduate level education with emphasis on practicality, innovation and interdisciplinary thinking.
REYST reports contain the master’s theses of REYST graduates who earn their degrees from the University of Iceland and Reykjavík University.
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ABSTRACT
The oil price volatility, growing concerns of global warming, and depleting oil/gas reserves have made it inevitable to seek energy from renewable energy resources. Many nations are embarking on introduction of clean/ renewable energy for displacement of oil-produced energy. Moreover, solar photovoltaic (PV)–Wind/batter hybrid power generation system technology is an emerging energy option since it promises great deal of challenges and opportunities for developed and developing countries. Ethiopia is developing country and as of 2009 the total population size estimated 84.9 million inhabitants. From the total population size, current figures indicated that only about 33% of the population is estimated to have access to electricity and the per capita energy consumption is 40.59kWh, which is the lowest in the world. Degehabur and Keberdahar towns are located Somalia region in Ethiopia and total population size is estimated 125,000. They could have access to electricity from conventional diesel generator and power supplied are only limited to six to eight hours per day. Somalia region of being enriched with higher level of solar radiation as well as a second class wind speeds are a prospective candidate for deployment of solar PV /wind hybrid systems. The aim of this study was to investigate alternative power supply options to replace the existing diesel-only power system for remotely located towns detached from the main electricity grid in Ethiopia with a hybrid PV–wind–battery power systems to meet energy consumption of commercial and residential building (with total annual electrical energy demand of 3,291,920 kWh) consumers. The monthly average daily solar global radiation for Kebridehar and Degehabur towns ranges from 5.5 to 7.03 kWh/m2/day and monthly average wind speed varies from 4.2 to 8.2 m/s. Two power supply options were identified. The first option was a hybrid (standalone Solar/wind/battery) system and the second option was to construct new transmission line from nearest substation to selected towns. The HOMER simulation program developed by the NREL has been used as the design tool for both options. From First option, the simulation results indicated that for a hybrid system composed of solar/wind/battery and battery storage of 48 h of autonomy has been selected. The cost of generating energy (COE, US$/kWh) from the above hybrid system was found 0.422 $/kWh and 0.441$/kWh for Kebri Dehar for Degehabur town respectively. But the diesel-only option in the existing arrangement, levelized cost of energy for Kebri Dehar and Degehabur are $0.564/kWh and $0.543/kWh respectively and if diesel remains at $1.0/liter. The costs of energy (COEs) of hybrid system would be lower than the COE of a diesel-only system. Though the optimum system configuration changes under different diesel price assumptions, the hybrid system remains most economically feasible solution than the existing arrangements (diesel-only), under all scenarios considered so the selected hybrid energy system with 100% renewable energy contribution eliminating the need for conventional diesel generator. The grid extension of energy cost for Kebri Dehar and Degehabur are 1.172 and 0.869 $/kWh for Kebri Dehar and Degehabur towns respectively. The grid connected option according to the given circumstances was found to be not economical feasible solution the power supplied for the two towns.
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Acknowledgements
Primarily, I would like to give glory to God and the Virgin Mary without which the
completion of this thesis would have been unthinkable.
Next, I would like to thank Reykjavik Energy Graduate School of Sustainable Systems,
REYST for offering me the scholarship to do my MSc study at this prestigious University.
My deepest heartfelt gratitude goes to my supervisors Assistant professor Kristinn
Sigurjónsson for his generosity and kindness throughout the lifespan of my thesis work. The
thesis would not have been accomplished without his readiness to help; his willingness for
series of intensive discussions which brought about more valuable suggestions; and his
supports are highly appreciated in this regard.
I would like to extend my appreciation to The U.S. National Renewable Energy Laboratory
(NREL) to offer me free Homer optimization software to completion of this thesis.
I dedicate my thesis to my beloved parent; to my mother Etenesh Worku and to my wife;
Helina Tesfaye, my sources of inspiration and strength, who have dedicated their years
supporting my study, that make me feel loved, proud and fortunate.
Last but not least, I would like to thank some Ethiopian community live in Iceland, my
friends and my classmate who stood always by my side.
.
.
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LIST OF NOMENCLATURE
The maximum power point efficiency under standard test conditions [%]
The temperature coefficient of power [%/°C]
The cell temperature under standard test conditions [25°C]
The rated capacity of the PV array, meaning its power output under
standard test conditions [kW]
The PV derating factor [%]
The solar radiation incident on the PV array in the current time step [kW/m2]
The incident radiation at standard test conditions [1 kW/m2]
The temperature coefficient of power [%/°C]
PV cell temperature in the current time step [°C]
The PV cell temperature under standard test conditions [25 °C]
The nominal operating cell temperature [°C]
The ambient temperature at which the NOCT is defined [20°C]
The solar radiation at which the NOCT is defined [0.8 kW/m2]
The solar transmittance of any cover over the PV array [%]
The solar absorptance of the PV array [%]
The solar radiation striking the PV array [kW/m2]
The electrical conversion efficiency of the PV array [%]
The coefficient of heat transfer to the surroundings [kW/m2°C]
The PV cell temperature [°C]
The ambient temperature [°C]
Number of batteries in the battery bank
Nominal voltage of a single battery [V]
Nominal capacity of a single battery [Ah]
Minimum state of charge of the battery bank [%]
Average primary load [kWh/d]
The battery bank autonomy
The zenith angle [°]
The angle of incidence [°]
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The azimuth of the surface [°]
The latitude [°]
The solar declination [°]
The hour angle [°]
Gon The extraterrestrial normal radiation [kW/m2]
Gsc The solar constant [1.367 kW/m2]
The day of the year [a number between 1 and 365]
Go The extraterrestrial horizontal radiation [kW/m2]
Gon The extraterrestrial normal radiation [kW/m2]:
The extraterrestrial horizontal radiation averaged over the time step [kW/m2]
The hour angle at the beginning of the time step [°]
The hour angle at the end of the time step [°]
The global horizontal radiation on the earth's surface averaged
over the time step [kW/m2]
The extraterrestrial horizontal radiation averaged over the time step [kW/m2]
b The beam radiation [kW/m2]
d The diffuse radiation [kW/m2]
The slope of the surface [°]
The ground reflectance, which is also, called the albedo [%]
The efficiency of the PV array at its maximum power point [%]
B Lapse rate [0.00650 K/m]
z Altitude [m]
R Gas constant [287 J/kgK]
Standard temperature [288.16 K]
g gravitational acceleration [9.81 m/s2]
Standard pressure [101,325 Pa]
Hub height of the wind turbine [m]
The anemometer height [m]
The most frequent wind speed
The wind speed which carries the maximum amount of wind energy
The surface roughness length [m]
Wind speed at the hub height of the wind turbine [m/s]
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ln (..) The natural logarithm
The air density in kg/m3and is given as = 1.225 kg/m3.
d Diurnal pattern strength (a number between 0 and 1)
f hour of peak wind speed (an integer between 1 and 24)
Mean wind speed of each month
The required battery bank capacity in (Ah)
The capacity of the selected battery in (Ah)
The number of batteries that needs to be in parallel.
The DC system voltage (Volt)
The battery voltage (Volt)
The number of battery that needs to be in series
The required battery bank capacity in (Ah)
The capacity of the selected battery in (Ah)
The number of batteries that needs to be in parallel.
The lifetime throughput of a single battery
The annual throughput (the total amount of energy that cycle through
The battery bank in one year)
The float life of the battery (the maximum life regardless of throughput).
Real interest rate [%] and
N Number of years.
Represent the maximum continues power load consumes.
The maximum power that can be supplied by the inverter.
Total annualized cost [$/year]
AC primary load served [kWh/year],
The deferrable load served [kWh/year].
Initial capital cost of the component
CRF() Capital recovery factor
Project lifetime
CNPC Total net present cost of the stand-alone power system [$]
Cost of power from the grid [$/kWh],
Capital cost of grid extension [$/km],
O&M cost of grid extension [$/yr/km]
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Total annualized cost [$/year]
Total primary and deferrable load [kWh/yr]
Shape factor
Gamma function
List of Abbreviations and Acronyms
PV Photovoltaic
HOMER Hybrid Optimization Model for Electric Renewable
NREL National Renewable Energy Laboratory
COE Costs Of Energy
CO2 Carbon monoxide
KWh kilo Watt hour
GHG Greenhouse gas
RE Renewable energy
RAPS Remote area power supply
AC Alternating current
DC Direct current
TWh Terra watt hours
Tcal Terra calorie
ICS Inter connected system
SCS Self contain system
UEAP Universal Electricity Access Program
EEPCO Ethiopian Electric Power Corporation
SMSE Surface Meteorology and Solar Energy database
SWERA Solar and Wind Energy Resource Assessment
NMSA National Meteorological Service Agency
GIS Geographic Information Systems
PDF Probability density function
DOD Depth of discharge
MPPT Maximum Power Point Tracking
NPC Net present cost
O&M Operation and maintenances
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Table of contents
ABSTRACT ............................................................................................................................................... iv
Acknowledgements ................................................................................................................................. v
LIST OF NOMENCLATURE ..................................................................................................................... vi
List of Abbreviations and Acronyms ...................................................................................................... ix
Table of contents .................................................................................................................................... x
LIST OF TABLES ......................................................................................................................................xiii
1.Introduction ......................................................................................................................................... 1
1.1 Problem Statement ....................................................................................................................... 1
1.1.1 Rural energy context ....................................................................................................... 3
1.1.2 Electricity provision in rural areas ................................................................................... 3
1.1.3 Off grid electricity from hybrid system ........................................................................... 5
1.2 National and Regional Overviews ........................................................................................... 5
1.2.1 National overviews ................................................................................................................ 5
1.2.2 Regional overviews ......................................................................................................... 7
1.3 EEPCo’s Background ...................................................................................................................... 7
1.3.1 Generation Facilities .............................................................................................................. 9
1.3.2 Transmission and Substation Facilities .................................................................................. 9
1.4 Objective of the study ................................................................................................................. 10
1.5 Scope of the study ...................................................................................................................... 11
1.6 Present Status of Electric Supply for Keberi Dehar and Degehabur towns ................................ 11
1.7 Methodology ......................................................................................................................... 12
1.7.1 Problem Identification ......................................................................................................... 12
1.7.2 Renewable Energy Resources Assessment ................................................................... 13
1.7.3 Power supply Options Identification ............................................................................. 13
1.7.4 Overall System Design and Analysis .............................................................................. 13
1.8 Structure of thesis ....................................................................................................................... 16
2. Wind power system ......................................................................................................................... 17
2.1 Introduction ................................................................................................................................ 17
2.2 History ......................................................................................................................................... 17
2.3 Location of Degehabuar and Kebri Dehar town ......................................................................... 18
2.4 Wind resource assessment for Degehabur and Keberedehar town ........................................... 19
2.4.1 Estimation of the frequency distribution and long term average Wind Speed of Degehabur and Kebedehar town .................................................................................................. 22
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2.4.2 Wind Power density distributions and mean power density ........................................ 28
2.5 Wind Turbines ............................................................................................................................. 30
2.5.1 Different Types of Turbines ................................................................................................. 30
2.5.2 Wind Turbines Components ................................................................................................ 32
2.5.3 General Workings .......................................................................................................... 34
2.5.4 Wind system design ............................................................................................................. 34
2.5.3 Wind turbine in hybrid system ...................................................................................... 35
2.5.4 Wind Turbines Efficiency and Power Curve .................................................................. 35
2.6 Wind Speed Height Correction ................................................................................................... 38
2.7 Wind Power ................................................................................................................................. 40
2.7.1 Swept Area .................................................................................................................... 41
2.8 Annual wind energy production and capacity factor .................................................................. 42
3. PHOTOVOLTAIC POWER SYSTEMS .................................................................................................... 43
3.1 Introduction ................................................................................................................................ 43
3.2 History ......................................................................................................................................... 43
3.3 Photovoltaic ................................................................................................................................ 45
3.3.1 PV electricity ................................................................................................................. 45
3.3.2 General working principles Photovoltaic Cells .............................................................. 46
3.3.3 Solar Module Power Characteristics and Operating issue ............................................ 46
3.3.4 Photovoltaic Cells and Efficiencies ................................................................................ 47
3.3.5 PV installation ............................................................................................................... 49
3.3.6 Photovoltaic Modules ................................................................................................... 50
3.3.7 Photovoltaic Manufactures ........................................................................................... 50
3.4 Solar resource ............................................................................................................................. 51
3.4.1 Degehabur and Kebri Dehar Solar Resources ............................................................... 52
3.5 Synthesize Hourly solar data from monthly average radiation ...................................................... 54
3.6 Calculates the global radiation incident on the PV array ............................................................ 60
3.6.1 Calculates the PV Cell Temperature and PV array power output ................................................ 61
4. Batteries, PV controller, Inverters and Energy Consumption ........................................................... 64
4.1 Introduction ................................................................................................................................ 64
4.1.1 Batteries ................................................................................................................................... 64
4.1.2 Battery Electricity ................................................................................................................. 65
4.1.3 General working ................................................................................................................... 66
4.1.4 Storage capacity ................................................................................................................... 66
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4.1.5 Battery modeling ................................................................................................................. 67
4.1.7 Battery Sizing ....................................................................................................................... 70
4.1.7 Batter life time ..................................................................................................................... 72
4.1.8 Battery Design ...................................................................................................................... 73
4.1.9 Battery in hybrid system ...................................................................................................... 73
4.2 PV Controllers ................................................................................................................................ 74
4.2.1 MPPT Charge Controllers ..................................................................................................... 74
4.2.2 General working princples ................................................................................................... 75
4.3 Inverters ...................................................................................................................................... 75
4.3.1 General working ................................................................................................................... 76
4.3.2 Inverter Sizing ...................................................................................................................... 76
4.4 Energy consumption for Kebridehar and Degehabur towns ...................................................... 77
4.4.1 Introduction ......................................................................................................................... 77
4.5 Load forecast for Degehabur and Kebri Dehar ........................................................................... 79
4.5.1 Methodology ........................................................................................................................ 79
-Residential Consumption ................................................................................................................. 79
4.5.2 Energy Requirement and Peak Power Demand ............................................................ 80
4.5.3 Forecast Results ............................................................................................................ 81
5. Hybrid energy systems ...................................................................................................................... 82
5.1 Introduction ................................................................................................................................ 82
5.2 Stand Alone Hybrid System ......................................................................................................... 82
5.2.1 Typical Stand Alone Hybrid Components and Efficiencies................................................... 83
5.2.2 Proposed Stand Alone Sizing Optimization Procedure ........................................................ 84
5.3 Economic Evaluation of the Hybrid System ................................................................................ 85
5.3.1 Annual real interest rate ...................................................................................................... 85
5.3.2 Levelized cost of energy ....................................................................................................... 86
5.3.3 Net present cost (NPC) ......................................................................................................... 86
5.4 Breakeven Grid Extension Distance ............................................................................................ 89
5.5 System architecture .................................................................................................................... 89
6.1 General ........................................................................................................................................ 93
6.2. Simulation results ...................................................................................................................... 94
6.2.1 Optimization results ............................................................................................................. 94
6.3 Comparison with “diesel only” for Kebri Dehar and Degehabur towns ..................................... 97
6.5 Sensitivity results ...................................................................................................................... 100
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6.5.1 Cost of energy sensitivity to diesel price – Kebri Dehar and Degehabur towns ................ 100
6.6 Comparison of the Grid extension with standalone (Off Grid) and diesel-only system ........... 102
7. Conclusion and Recommendation .............................................................................................. 104
7.1 Conclusions ............................................................................................................................... 104
7.2 Recommendation and Further work .................................................................................. 106
Bibliography ........................................................................................................................................ 106
List of Appendixes ............................................................................................................................... 110
Appendix–A ......................................................................................................................................... 110
LIST OF TABLES
TABLE 1.1: ENERGY CONSUMPTION AND POPULATION SIZE OF KEBRI DEHAR AND
DEGEHABUR ............................................................................................................................................... 11
TABLE 2.1 PREVAILING WIND DIRECTIONS REGION ON EARTH ...................................................... 19
TABLE 2.2 TYPICAL SHAPE FACTOR VALUES ....................................................................................... 24
TABLE 2.3: WIND POWER DENSITY FOR DEGEHABUR AND KEBEREDEHAR TOWNS ............ 28
TABLE 2.4: WIND CLASS CATEGORY BY WIND SPEED AND POWER DENSITY ........................ 30
TABLE 2.5: REPRESENTATIVE SURFACE ROUGHNESS LENGTHS DIFFERENT TERRAIN
(SOURCE: HOMER) .................................................................................................................................... 39
TABLE 2.6: TECHNICAL DATA OF EOLTEC CHINOOK 17-65 WIND TURBINE ............................... 42
TABLE 2.7: PREDICTED ANNUAL AND MONTHLY ENERGY PRODUCTION FROM A SINGLE
EOLTEC CHINOOK 17-65 WIND TURBINE FOR THE TOWNS ....................................................... 43
TABLE 3.1: SOLAR MODULE POWER AT STC RATING AND PRICE ................................................ 51
TABLE 3.2: PV MODULE CHARACTERISTICS FOR STANDARD TECHNOLOGIES ...................... 62
TABLE 4.1: MANUFACTURES DATA SHEET AND THE PRICES ........................................................ 65
TABLE 4.2: MPPT CHARGE CONTROLLERS MANUFACTURES ........................................................ 74
TABLE 4.3: INVERTERS MANUFACTURES .............................................................................................. 76
TABLE 4.4: TOTAL ANNUAL ENERGY CONSUMPTION FOR DEGEHABUR AND KEBRI DEHAR
TOWNS .......................................................................................................................................................... 79
TABLE 5.1: AVERAGE EFFICIENCY OF HYBRID SYSTEM COMPONENTS .................................... 84
TABLE 5.2: SYSTEM COST VALUES THAT USED IN SIMULATIONS ................................................ 87
TABLE 5.3: GRID EXTENSION COST FOR KEBRI DEHAR AND DEGEHABUR TOWNS ............. 89
TABLE 5.4: KEY MODEL INPUT ASSUMPTIONS FOR MODEL ........................................................... 91
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TABLE 6.1: COMPARISON OF NET PRESENT COST, ENERGY COST AND GREEN HOUSE
GAS EMISSION DIESEL-ONLY OPTION WITH HYBRID SYSTEM ................................................ 97
TABLE 6.2: ECONOMIC PERFORMANCE OF THE HYBRID STAND ALONE SYSTEM FOR
DEGEHABUR TOWN .................................................................................................................................. 98
TABLE 6.3: ECONOMIC PERFORMANCE OF THE HYBRID STAND ALONE SYSTEM FOR
KEBRIDEHAR TOWN................................................................................................................................. 99
`TABLE 6.4: ENERGY COST COMPARISON FOR GRID EXTENSION WITH HYBRID AND
DIESEL-ONLY SYSTEM .......................................................................................................................... 103
LIST OF FIGURESFIGURE 1.1: PERCENTAGE OF ELECTRIFIED/NON-ELECTRIFIED RURAL POPULATION ......... 4
FIGURE 1.2: SYSTEM COMPONENT OF A CONCEPTUAL RENEWABLE HYBRID POWER
SYSTEM ........................................................................................................................................................... 5
FIGURE 1.3: MAP OF SOMALI REGION (MAPSOF, 2010) ................................................................. 7
FIGURE 2.1: WORLD WIND ENERGY - TOTAL INSTALLED CAPACITY (MW) (WORLD WIND
ENERGY 2009), 2009) ................................................................................................................................ 18
FIGURE 2.2: A GIS MAP SHOWING GEOGRAPHIC DISTRIBUTION OF WIND RESOURCES OF
ETHIOPIA (SOURCE: SWERA) ............................................................................................................... 21
FIGURE 2.3 MONTHLY AVERAGED WIND SPEED AT 50 M ABOVE THE SURFACE OF THE
EARTH (M/S) FOR DEGEHABUR AND KEBERDEHAR TOWN. (SOURCE: NASA) .................. 22
FIGURE 2.4: RAYLEIGH DENSITIES FUNCTION FOR VARIOUS MEAN WIND SPEED.
(SHENCK) ..................................................................................................................................................... 23
FIGURE 2.5 PROBABILITY DENSITY VS. WIND SPEED AT HUB HEIGHT FOR KEBEREHAR
TOWN ............................................................................................................................................................. 25
FIGURE 2 6: PROBABILITY DENSITY VS. WIND SPEED AT HUB HEIGHT IN DEGEHABUR
TOWN ............................................................................................................................................................. 25
FIGURE 2.7 WIND SPEED DAILY PROFILE FOR KEBEREDAR ........................................................... 27
FIGURE 2.8: WIND SPEED DAILY PROFILE FOR DEGEHABUR TOWN ........................................... 27
FIGURE 2.9: HORIZONTAL AXIS WIND TURBINES (HAWT) ARE EITHER UPWIND MACHINE
OR DOWN WIND MACHINES .................................................................................................................. 32
FIGURE 2.10: CUT-VIEW OF A WIND TURBINE. (SOURCE: DOE/NREL) .......................................... 32
FIGURE 2.11: DIFFERENT TYPE WIND TURBINES POWER CURVES BEING CONSIDERED FOR
THE SELECTED WIND FARM.................................................................................................................. 36
FIGURE 2.12: POWER OUTPUT OF EOLTEC CHINOOK 17-65 WIND TURBINES WITH STEADY
WIND SPEED CHARACTERISTICS. ...................................................................................................... 37
FIGURE 3.1: SOLAR MODULE RETAIL PRICE INDEX ........................................................................... 44
FIGURE 3.2: PV DIAGRAM .............................................................................................................................. 45
FIGURE 3.3: HOW PHOTOVOLTAIC CELLS WORK (CLEAN ENERGY ASSOCIATES) ............... 46
.FIGURE 3.4: I-V CURVES SHOWING THE EFFECT OF SOLAR ISOLATION AND
TEMPERATURES ON PV PANEL PERFORMANCE .......................................................................... 47
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FIGURE 3.6: MONTHLY SOLAR RADIATION AND CLEARNESS INDEX FOR KEBRIDEHAR
AND DEGEHABUR TOWNS (SOURCE: NASA) .................................................................................. 53
FIGURE 3.7: GLOBAL DAILY SOLAR RADIATIONS ON HORIZONTAL SURFACES FOR KEBRI
DEHAR TOWN ............................................................................................................................................. 55
FIGURE 3.8: GLOBAL DAILY SOLAR RADIATIONS ON HORIZONTAL SURFACES FOR
DEGEHABUR TOWN .................................................................................................................................. 55
FIGURE 3.9: DIAGRAM OF THE SOLAR RADIATION CALCULATION ON PANEL SURFACE ... 56
FIGURE 3.10: CALCULATES THE GLOBAL RADIATION INCIDENT ON THE PV ARRAY WITH
TRACKING AND WITHOUT TRACKING SYSTEM ............................................................................. 61
FIGURE 4.1: KINETIC BATTERY MODEL CONCEPTS ........................................................................... 68
FIGURE 4.2: CAPACITY CURVE FOR DEEP-CYCLE BATTERY MODEL SURRETTE4KS25P .... 69
FIGURE 4.3: LIFETIME CURVE FOR DEEP-CYCLE BATTERY MODEL SURRETTE4KS25P ..... 70
FIGURE 4.4: HOURLY LOAD PROFILES FOR KEBRI DEHAR TOWN................................................ 78
FIGURE 4.5: HOURLY LOAD PROFILES FOR DEGEHABUR TOWN .................................................. 78
FIGURE 4.6: ENERGY AND POWER FORECAST FOR KEBERDEHAR TOWN ............................... 81
FIGURE 4.7: ENERGY AND POWER FORECAST FOR DEGEHABUR TOWN ................................. 81
FIGURE 5.1 PV/BATTERY/WIND STAND ALONE SYSTEM ..................................................................... 84
FIGURE 5.2: EQUIPMENT TO CONSIDER AND HYBRID SYSTEM CONFIGURATION FOR
DEGEHABUR TOWNS ............................................................................................................................... 90
FIGURE 5.3: EQUIPMENT TO CONSIDER AND HYBRID SYSTEM CONFIGURATION FOR
KEBRI DEHAR TOWN................................................................................................................................ 91
FIGURE 5.4: SIZES CONSIDERED FOR COMPONENTS FOR KEBRIDEHAR TOWN HOMER
MODEL RUN ................................................................................................................................................. 92
FIGURE 5.5: SIZES CONSIDERED FOR COMPONENTS FOR DEGEHABUR TOWN HOMER
MODEL RUN ................................................................................................................................................. 92
FIGURE 5.6: ARCHITECTURE OF HOMER SIMULATION AND OPTIMIZATION .............................. 93
FIGURE 6.1: OVERALL OPTIMIZATION RESULTS TABLE SHOWING SYSTEM
CONFIGURATIONS SORTED BY TOTAL NET PRESENT COST FOR KEBRIDEHAR TOWN.
......................................................................................................................................................................... 94
FIGURE 6.2: OVERALL OPTIMIZATION RESULTS TABLE SHOWING SYSTEM
CONFIGURATIONS SORTED BY TOTAL NET PRESENT COST DEGEHABUR TOWN. ......... 95
FIGURE 6.3: MONTHLY AVERAGE ELECTRIC PRODUCTION FOR KEBRI DEHAR TOWN........ 96
FIGURE 6.4: MONTHLY AVERAGE ELECTRIC PRODUCTION FOR DEGEHABUR TOWN .......... 96
FIGURE 6.5: LIFECYCLE COSTS OF HYBRID SYSTEM BY COMPONENTS FOR DEGEHABUR
TOWN ............................................................................................................................................................. 99
FIGURE 6.6: LIFECYCLE COSTS OF HYBRID SYSTEM BY COMPONENTS FOR KEBRIDEHAR
TOWN ........................................................................................................................................................... 100
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FIGURE 6.7: COST OF ENERGY (COE) OF OPTIMIZED HYBRID VS. DIESEL-ONLY UNDER
DIFFERENT DIESEL PRICE SCENARIOS. ......................................................................................... 101
FIGURE 6.8: NET PRESENT COST (NPC) OF OPTIMIZED HYBRID VS. DIESEL-ONLY UNDER
DIFFERENT DIESEL PRICE SCENARIOS .......................................................................................... 101
FIGURE 6.9: COMPARISON OF GRID EXTENSION WITH STANDALONE SYSTEM OF KEBRI
DEHAR TOWN ........................................................................................................................................... 103
FIGURE 6.10: COMPARISON OF GRID EXTENSION WITH STANDALONE SYSTEM OF
DEGEHABUR TOWN. ............................................................................................................................... 103
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1.Introduction
The oil price volatility, growing concerns of global warming, and depleting oil/gas reserves
and due to the contradiction between gradual growth of the global energy demand,
renewable energy such as solar energy, wind energy, bio-energy, and hydropower might
become a new manner in which we produce energy for sustainable development.
Photovoltaic (PV) and wind energy systems are the most promising candidates of the future
energy technologies, and it has been widely noticed that stand alone and grid connected PV
and wind energy markets have grown rapidly. Energy generation system reliability has been
considered as one of the most important issues in any system design process. However,
natural energy resources are unpredictable, intermittent, and seasonally unbalanced.
Therefore, a combination of two renewable energy sources may satisfy bigger share of
electricity demand and offer reliable and consistent energy supply. The Hybrid PV and Wind
Electricity System is well suited to conditions where sun light and wind have seasonal shifts,
for example, in summer the sun light is abundant but windless, while in winter wind resource
increased that can complement the solar resource. The reliability of the stand-alone hybrid
PV-wind system in producing energy has been proven by earlier studies. In the last two
decades solar energy and wind energy has become an alternative to traditional energy
sources. These alternative energy sources are non-polluting, free in their availability and
renewable. But high capital cost, especially for photovoltaic, made its growth a slow one. The
best way to attempt to decrease the cost of these systems is by making use of hybrid designs
that uses both wind/photovoltaic.
The purpose of this study is to investigate alternative power supply options for Degehabur
and Kebidehar towns by replacing the conventional diesel powered electric supply which are
towns detached from main electricity grid system in Ethiopia.
1.1 Problem Statement
In spite of the huge hydroelectric potential of Ethiopia, severe power cuts in recent years have
a heavy impact on the country’s economy Ethiopia. It is known that the development of any
country depends on the amount of energy consumed. Energy consumption is proportionally
to the level of economic development. According to current figures only about 33% of the
population is estimated to have access to electricity and the per capita energy consumption is
40.59kWh, which is the lowest in the world and almost biomass. This had a direct impact on
deforestation. For lighting systems, in rural areas, kerosene is used which produces and
emission of pollutants. Though Ethiopia has a tremendous amount of hydro power potential,
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because of the high initial cost, it is able to harness only 3 % of its potential so far. Moreover
the cyclic drought in the country was affected the hydrological situation and causing
“Electrical Energy Draught”.
In the Degehabur and Kebri Dehar towns in Ethiopia, access to electricity seems to be a
‘never ending’ problem. Urban communities of Ethiopia have yet to achieve reliable
electricity services, while people in rural areas like Keberi Dehar and Degehabur are still
dreaming of connecting to national grid limes. In 2010, these towns still not connected in the
national grid system. Despite its strong economy, the lack of electricity supply has
contributed to social issues such as poverty, poor health services, low education, and gender
inequity.
Furthermore, the environmental challenges with regard to greenhouse gas (GHG) emissions
from fossil fuel burning in diesel power stations, as the main power generators in Degehabur
and Kebri Dehar towns, are obvious. Finally, the lack of studies, expertise and experiences in
dealing with rural electrification programs, are some of the Ethiopia has potential to build a
mixed-power system strategy by introducing renewable energy (RE) to the existing (Diesel-
only)power generation systems. This dissertation explores the ways of harnessing the
promising sources of renewable energy in Degehabur and Kebridehar towns including wind
and solar photovoltaic (PV) energies as a contribution to replace the existing diesel only
electricity generation power plant the towns which located detached from the national grid
system. For the towns, they have being enriched with higher level of solar radiation as well as
a second class wind speeds are a prospective candidate for deployment of solar PV /wind
hybrid energy systems. Hybrid energy standalone (Off-Grid) system is an excellent solution
for electrification of remote rural areas where the grid extension is difficult and not
economical viable. Such system incorporates a combination of one or several renewable
energy sources such as solar photovoltaic and wind energy. So sun and wind energy can
bring an important contribution to a sustainable and decentralize energy mix for Ethiopia.
Hence the use of wind and photovoltaic systems are only worth to generate electricity for
island net systems which cannot join the main grid. As of 2009, the total transmission and
distribution losses is around 28%.The total system losses are comprise technical and non-
technical losses. Decentralized energy (Off-Grid) system also big contribution to reduce
energy losses comes to be associated with transmission and distribution line system.
Main Report Final Master Thesis
1.1.1 Rural energy context
Energy, next to water, transport, education, training and other factor impacting the
development, forms of part a number of services often urgently needed in remote villages to
contribute to rural development and the creation of job opportunity.
The price of conventional energy sources in remote areas, such as candles, paraffin, gas, coal,
battery, is often more expensive than in urbanized areas due to the remoteness of the retailers
,rural people their goods from, and the corresponding overheads. Moreover, the cost per
energy service, for example lighting, is more expensive for rural in habitant than their urban
counter parts who often have access to grid electricity.
There are also other factors associated with conventional energy supply in remote areas, such
as the, often long, transport required to obtain these energy supplies and the dangers in their
use or storage. For example, women might have to walk for up to four hours each day to
collect sufficient wood to cook for their family or heat the house. Many health problems are
reported related to burns from the use of paraffin and respiratory conditions due to the
constant smoke exposure. Cutting of wood also aggravate deforestation.
1.1.2 Electricity provision in rural areas
The provision grid electricity in rural area is often associated with higher cost to the grid
supplier than off grid RAPS (remote area power supply) electricity technology option would
be..Grid electrification in rural areas in many case cases is financially inefficient particularly
due to low consumption take-up in the remote area.
As of 2009 figure indicate that, 85% of Ethiopians were living in rural areas, which 12
million households had no access to electricity. It estimate that in 2009 ,85% (see figure 1.1)
the rural population will still be unelectrified due to the high cost for grid extensions to very
remote extension to very remote towns and villages whereby average monthly households
electricity consumption can be as low as some 20 to 35 kWh.
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Main Report Final Master Thesis
villages. Off-grid technology is option single source and hybrid, can in some case be an
economic alternative to remote grid extension
1.1.3 Off grid electricity from hybrid system
Off grid electricity can be generated by single-source system using solar photovoltaic panel,
wind turbine generators, micro-hydro power plant or fuel-powered combustion engine
generator sets, or by combining one or more types of these electricity generating sources in a
so-called hybrid system (see figure 1.2).hybrid system can supply power to AC or DC load or
both. It may require AC, DC or both types of buses power conversion devices are used to
transform power between DC and AC buses.
Figure 1.2: System component of a conceptual renewable hybrid power system
1.2 National and Regional Overviews
1.2.1 National overviews
Ethiopia is located in the eastern part of Africa between 3o to 15o north and 33o to 48o east
(approximately 820 km from north to south and 130 km east to west) with a surface area of
1.1 million square kilometers, it is the third largest country in Africa. It is the second most
populous country in Sub Saharan Africa with an estimated population of about 84.9 million,
which is mostly distributed in northern, central and southwestern highlands.
Ethiopia has a federal country composed of nine regional states. The country has a bicameral
parliamentary system, and government headed by a prime minister. Addis Ababa is the
capital of the country, and is the seat of many international and regional organizations, like
the African Union, and the UN ECA (Economic Commission for Africa). (Planning Power
system, 2008)
The country follows an agricultural led industrialization strategy, and is achieving
encouraging results. The economy has been growing at a rate of more than 10% for the last
Main Report Final Master Thesis
six years consecutively, and large number of development projects is underway. The
agriculture sector is the leading source of foreign exchange for Ethiopia. Coffee distantly
followed by hides and skins, oil seeds and recently cut-flower are the major agricultural
export commodities. At present the per capita income in Ethiopia is less than USD 100.
According to EEPCO current data with only 8% of households connected and 33% of the
population having access to electricity from national grid, access to electricity in Ethiopia is
one of the lowest by any standards. Despite the fact that 80% of the population of Ethiopia
live in rural areas, electricity supply from the grid is almost entirely concentrated in urban
areas. Among other things, dispersed demand and very low consumption level of electricity
among rural consumers, limited grid electricity penetration to rural population to less than
1%. Based on the hitherto electricity expansion practices in the country, access to electricity
does not seem to be the reality of the near future for the greater percentage of the rural
population. However, the recent government’s strategy under Universal Electricity Access
Program (UEAP) ambitiously plans to increase access to electricity from the current 33% to
50% by the year 2015 by connecting 7500 new towns and villages to the grid. The UEAP
does not only aim to increase access, but also aims to raise the level of national per capita
consumption of electricity from the current 35.87 kWh to 128 kWh by the year 2015.
The Government of Ethiopia is aware of the fact that the national utility alone through
Continuous grid extension cannot accelerate rural access to electricity. In the struggle to
improve rural access to electricity, the government has recently streamlined its strategies and
embarked upon removal of barriers and constraints to accelerated off-grid rural
electrification.
The Rural Electrification Strategy provides opportunities for an increasing participation of
the private sector in the supply of electricity to un-electrified rural population. This has
included the design of institutional and financing framework for private sector-led rural
electrification, which is expected to remove barriers and facilitate private sector participation
in the provision of off-grid electricity supply (generation, transmission, distribution and
marketing).
The National energy policy of the country emphasizes the need for equitable development of
the energy sector in parallel with other social and economic developments. Specific policy
lines include the attainment of self-sufficiency through the development of indigenous
resources with minimum environmental impact and equitable distribution of electricity in all
regions. The policy envisages the development of hydro, geothermal, natural gas, coal, wind
Main Report Final Master Thesis
and solar energy resources based on their techno-economic viability, social and
environmental acceptability.
1.2.2 Regional overviews
The Somali Region is one of nine regions of the Federal Republic of Ethiopia. Located in the
eastern Ethiopian lowlands bordering Djibouti, Somalia (including Somaliland) and Kenya,
the region is almost entirely inhabited by people of Somali ethnicity (95.6 per cent according
to Ethiopia’s Central Statistics Agency). They speak a common language, Somali, and share a
rich cultural heritage that spans Somalis living in Kenya, Ethiopia and Somalia. Ethiopia’s
Central Statistics Agency estimated the region’s population at just over 4.44 million in 2007,
which accounts about 6% of the country with a high sex ratio of 125 males to 100 females
[census, 2007], though some consider that an underestimate, as a proper census has not been
conducted for over a decade and population growth is rapid. Somalis are either the third or
fourth largest ethnic group in Ethiopia. (International, 2006)
Figure 1.3: Map of Somali region (Mapsof, 2010)
Somalia region is divided by nine zones which are Deghabur, Korahe (Keberdehar), Shinile,
Warder, Gode, Jigjiga, Afder, liben and Fik.
1.3 EEPCo’s Background
The Ethiopian Electric Power Corporation (EEPCO) is a statutory corporation owned by the
Government of Ethiopia, which was set up by regulation on 7th of July 1997 for the purpose
of generation, transmission and sale of electricity nationwide. EEPCO operates two power
supply systems, namely the main interconnected system (ICS) and the self-contained system
(SCS). (Planning Power system, 2008)
Main Report Final Master Thesis
The main ICS, which serves the major towns and industrial centers, has a total installed
capacity of 1559.3 MW. This installed capacity is contributed by hydropower installations
having a total installed capacity of 1390.6 MW and thermal stations of about 168.7 MW. The
thermal stations are stand-by Diesel stations at different places in different parts of the
country (22.2 MW), Kaliti (11.2 MW), Awash Town (28 MW), Dire Dawa (40 MW), Adama
(30 MW) and Bishefetu (30 MW) which are required to mitigate the power shortage during
dry periods when the generations from hydro plants is at its minimum. The Aluto-Langano
geothermal station has an installed capacity of 7.3 MW, which is, at present, non-operational
due to low pressure of the thermal fuels (Planning Power system, 2008).
The SCS supplies isolated load centers, which are far from the ICS, mostly using Diesel as a
source of generation. Currently this system has an aggregate installed capacity of about 20.01
MW, of which 13.86 MW are being generated from Diesel stations. The rest 6.15 MW are
being generated from small hydro power plants located at Sor, Yadot and Dembi. (Planning
Power system, 2008)
EEPCO currently provides electricity to a total of about 1,400,923 customers in
approximately 1500 towns and communities in Ethiopia, which is only a small proportion of
the country from the total of about 74 million inhabitants. According to current figures only
about 33% of the population is estimated to have access to electricity and the per capita
energy consumption is 43.53 kWh, which is one of the lowest in the world. Out of the total
number of customers 95% are within the ICS and the remaining 5% within the SCS (Planning
Power system, 2008)
Access to electricity can make real difference to lives of people. Although electricity alone
will not reduce poverty, the lack of access to this modern energy is a severe constraint to
development. Improving access to electricity is thus essential for poverty reduction.
(Planning Power system, 2008)
To reduce the level of poverty one should enhance income generating means and bring
change in quality of life of people. The ultimate objective of electrification should thus be
provision of electricity to a large number of rural town and village dwellers on sustainable
basis, and to support income generating activities. To enhance income generating capacity
means provision of electric energy for driving electric motors necessary for small scale
manufacturing, pump sets for irrigation, motors for mills, etc. (Planning Power system, 2008)
Universal Electricity Access Program (UEAP) is launched by the Government of Federal
Democratic Republic of Ethiopia to meet the demand of agricultural sector (irrigation pumps,
prevention of farm products, etc.), industrial and commercial sector, rural water supply
Main Report Final Master Thesis
installations, residential consumptions, education and health sectors. The program, while
broadening the national electrification coverage and increasing people’s access to electricity
from existing 33% to 50% in the coming five years, will underpin the ADLI strategy and
poverty reduction strategy of the government. In other words, the UEAP targets electricity
supply to towns, villages, social service giving centers and irrigation facilities in all Regional
states of the country. The concept of UEAP involves provision of power from least cost
source meeting required reliability standards to enhance capacity of wealth generation.
(Planning Power system, 2008)
The project is designed around the principles of least cost expansion through technical and
institutional innovations, and rapid growth of access to electricity supplies and to assist
customers in using electricity for income generating activities. (Planning Power system,
2008).
1.3.1 Generation Facilities
The existing ICS hydroelectric power plants are Koka, Awash II, Awash III, Finchaa, Melka
Wakena, Tis Abay I & II,Gilgel Gibe-I,Tekeze and Gilgel Gibe-II Besides the on-
rehabilitation geothermal plant at Aluto Langano there are standby diesel units at Alemaya,
Dire Dawa, Mekele, Adigrat, Axum, Lalibela, Sekota, Adwa, Korem, Nekemt, Ghimbi, Bizet
and Shire including the new emergency diesel units at Kaliti, Awash Town, Dire Dawa,
Adama and Bishofetu which are part of the ICS. Most of the diesel units serve on standby
basis. (planning, PTP, 2008)
The Generation facilities in the ICS are distributed throughout the country and are located far
away from the big load. The eleven hydro generating stations, six diesel stations and main
thermal stations with an aggregate installed capacity of 1559.3 MW
1.3.2 Transmission and Substation Facilities
Ethiopia’s widely distributed population has led to the development of an extensive
transmission network. The Ethiopian electric grid system consists of five principal levels of
transmission voltages: 400, 230, 132, 66 and 45 kV. The 400 and 230 kV high voltage (HV)
transmission lines are the backbone of the system connecting the generating stations of
Finchaa, Melka Wakena, Gilgel Gibe-I, Gilgel Gibe-II,Tekeze to the major load centers
(Addis Ababa) at Gefersa, Kaliti and Sebeta substations respectively. These substations are
also interconnected through double circuits of 132 kV and single circuits of 230 kV making a
complete ring at 132 kV and a partial ring at 230 kV around Addis Ababa. The 230-kV
Main Report Final Master Thesis
system further extends from Addis Ababa about 400km eastward to Dire Dawa, south to
Melka Wakena and about 1000 km towards the west and north. (planning, PTP, 2008)
There are a number of 132 kV lines in the system either being the major distributors of
electricity from the 230 kV system or the major interconnecting lines of generating stations to
the system as that of Koka, Awash-II & III and Tis Abay-II. The 66 and 45 kV transmission
lines are also used to distribute bulk powers transmitted mainly by 132 and 230 kV
transmission lines. The 45 kV systems are being phased-out in favor of the 66 kV systems.
(planning, PTP, 2008)
The existing transmission system comprises a total of about 8,747 km of transmission lines,
2,053 km of which are at the 230-kV level, 3,983 km are at the 132-kV level, 2,235 km are at
the 66-kV and 476 km are at the 45-kV voltage level in the ICS system and the rest 245 km in
SCS (planning, PTP, 2008)
1.4 Objective of the study
The basic objective of the research described in this thesis to investigate alternative power
supply options for Degehabur and Keberdehar towns to improve the sustainable power supply
by replacing existing conventional diesel powered electric supply remotely located towns
detached from the main electricity grid in Ethiopia.
While trying to achieve this main objective, we will attempt to fulfill the following goals:
Develop a data base of published data on wind speed and solar radiation in the
Degehabur and Kebri Dehar towns.
Select a set of photovoltaic modules and wind turbines suitable to generate electricity
using the wind and solar resource available in the selected towns
Propose an optimization procedure to determine the amount and type of PV modules,
storage battery and wind turbines needed, under stand alone conditions, to satisfy a
predetermined demand at minimum cost.
Perform an economic analysis to compute the net present value of the renewable
energy systems proposed
Conducted on Economic evaluation of the systems and compare different option.
To create strength of reliable power supply for Degehabur and Keberedehar towns
and to get electricity access from potential renewable energy resource through their
own alternative supply
Main Report Final Master Thesis
Make conclusion on to replace existing diesel generator and reliable power supply at
Degehabur and Keberedehar town with solar (photovoltaic)/wind power/battery
hybrid technology.
1.5 Scope of the study
The scope of this study is to assess the technical and economical feasibility to replace the
existing diesel generator of detached towns from national grid in Ethiopia. The study will
investigate different renewable energy option to incorporate the existing diesel-only system.
This Study shall collect and analyze the data and information in the following fields among
others, examine and select the most suitable Power Generation and Supply Systems,
recommend necessary measures necessary measures that configure a system to accommodate
2011 electrical energy demand for the two towns. The study only focuses on solar energy and
wind energy resource assessment of among different renewable energy resource in the towns.
It compares estimates of the cost of electricity produced from renewable energy and the
present cost of fossil fuel (diesel) based electricity generated in Degehabur and Kebri Dehar
towns.
1.6 Present Status of Electric Supply for Keberi Dehar and Degehabur
towns
Presently, Degehabur and Kebridehar towns get diesel (SCS) supply from EEPCO. They
have diesel generators with an installed capacity of 400 and 375 kW each for Degehabur and
Kebridehar towns, respectively, which are located in eastern parts of Ethiopia. These towns
have not yet connected to a national grid as well as there is no transmission line passing
through it (See Appendix-A, Figure A.1).KebiDehar and Degehbur towns are located 160
and 210 kilometer, respectively from the nearest national grid In the table 1.2, indicated that
capita energy consumption per person of these towns still get low along with the working
hours of generators are limited to 6-10 hours per day. The power supply were insufficient the
normal daily blackout is experienced in the study area are around 11 hours, and in a worst
case situation could reach 13 hours a day .In addition towns, which are supplied from diesel,
do not have the freedom to get sufficient electric supply and as a result there is a suppressed
demand in study areas. This is due to the diesel generators are limited capacity with fairly
high fuel, operation and maintenance cost. Conventional diesel generator would be unreliable
energy supply system as well as environmental concerns in the towns. Table 1.1: Energy consumption and population size of Kebri Dehar and Degehabur
Main Report Final Master Thesis
Name of Power station
Generator Capactiy
(KW)
Generated Energy (KWH)
Fuel Consumption
(kg) ServiceHours
Population Size
Capita energy consumption perperson(Kwh)
Degehabour 400 1,025,960 187,544 2,995 68,000 15
Kebri Dehar 375 514,930 161,678 4,716 57,000 9
Source: EEPCo
The average fuel efficiency of diesel generator is around 4 kWh/liter, to meet its electricity
requirements. Table 1.2 indicted that the total working hours of diesel generators 2995 hours
for Degehabur and 4716 hours for Kebridehar town per year while almost more than 50% the
rest of year, they didn’t get electricity at all and still have suffered in the darkness.
However, biomass energy is, and will remain, an important source of energy because most of
the people of the towns depend on traditional fuels or biomass energy, namely wood,
bamboo, twigs, wood shavings, agricultural residues such as straw, charcoal and cow dung
for their domestic consumption. For the vast majority of the population size of in these towns,
the main source of energy for cooking comes from such biomass fuel such as wood fuels,
crop residue and cow dung. Deforestation and burning of biomass significantly contribute to
greenhouse gas emissions. In addition to carbon dioxide emissions, wood burning also creates
the products of incomplete combustion (PICs) which have a global warming potential as
great as carbon dioxide itself.
At the local level, receding forests add to the hard work of women who have to travel longer
distances in search of fuel or, in extreme situations, are forced to switch to inferior fuels such
as roots, weeds, leaves, etc. An estimated 80% of rural women aged 10-59 years are affected
by fuel-wood scarcity in Ethiopia. Inefficient combustion of bio fuels in traditional cook
stoves produces smoke which can cause a variety of health problems such as conjunctivitis,
acute respiratory infections, upper respiratory irritation, etc
1.7 Methodology
Different methodologies have been applied to address each objective of this study. Each
methodology was selected to suit the seven phases used to undertake this research. The detail
methodology is presented in Figure 1.4
1.7.1 Problem Identification
The problem identification involved a literature survey in collecting general information
about Keberi Dehar and Degehabur towns such as geography, climate, population, current
Main Report Final Master Thesis
electricity status of the towns and future demand, and cost of energy (COE) was collected.
The main focus of the survey was on the renewable energy sources available, electricity
supply crisis in the selected town come from conventional diesel generator power plant as
well as there are no transmission passing through these island.
1.7.2 Renewable Energy Resources Assessment
The potential solar resource, wind power resource for Kebei Dehar and Degehabur towns
were assessed. The wind speed, solar insolation and clearness index for a year long period
was obtained from the NASA Surface Meteorology and Solar Energy database (SMSE).wind
and solar map of Ethiopian was collected from SWERA.A detail information about diesel
generator obtained from Ethiopian Electric Power Corporation. Monthly mean annual
temperature value collected from Ethiopian Meteorological Agency.
1.7.3 Power supply Options Identification
Feasible options of generating electricity in the selected towns were proposed based on
available power generating technologies and local energy resource potentials. The paramount
feature of this task was power extraction from renewable resources. The available
technologies were identified through a literature survey based on best practices in off-grid
power systems applications
1.7.4 Overall System Design and Analysis
The following is the sequence of system design used in this dissertation.
Step 1: Wind power system design
Detail wind power energy generation design conducted on the part including wind resource
assessment, Estimation of the frequency distribution and long term average wind Speed as
well as synthesis of wind speed daily profiles. Computed wind Power density distributions
and predication monthly and annual mean power density, analyzed different power curves of
wind turbines and optimization annual wind energy output of single turbines for the selection
of appropriate wind turbines types of the two towns
Step 2: Photovoltaic power systems
Solar power design including detail solar resource assessment of the Keberi Dehar and
Degehabur towns, calculation, estimation of design of PV installation, Synthesize Hourly
solar data and calculates global radiation incident on the PV array from monthly average
radiation, Calculates the global radiation incident on the PV array with tracing system to
maximizing the power generation from solar PV modules, analyze the PV Cell Temperature
and PV array power output for each towns
Main Report Final Master Thesis
Step 3: conducted on batteries design, selection maximum point tracker, Inverters design as
well as Energy Consumption and load forecasting of the two towns
In this step which includes Battery Design and modeling, better converter design, PV
controller design and analyzed daily energy profiles along with annual energy consumption.
Load forecast in planning horizon has been carried out with ACRS excel spread sheet model
of the rural electrification project employed for this purpose..
Step 4: Hybrid energy systems
Detail analysis and design of a combination of one or several renewable energy sources such
as solar photovoltaic, battery and wind energy as well as use diesel-only as for comprising for
hybrid system. A hybrid system uses a combination of energy producing components that
provide a constant flow of uninterrupted power, Stand Alone Hybrid System, Economic
Evaluation of the Hybrid System.
Step 5: Optimization of the model using HOMER software
Validation of the model .This is accomplished by comparing modeled results with data
collected in EEPCO for the existing energy system. For the hybrid energy systems, a
literature review highlighting the use of HOMER for hybrid system feasibility and sizing was
conducted. The input data are wind speed, solar radiation, clearness index, fuel price, wind
turbines cost, converter cost, PV panel cost, wind power curve, efficiency of solar panel, fuel
price generator cost, nominal operating cell temperature, primary and deferrable load (refer
detail input of the software in Appendix-E). In order to simulate and sense the behavior of
chosen power sources, all sources will be simulated in conjunction with each other. This will
be done using the simulation tool HOMER, provided by NREL, National Renewable Energy
Laboratory. A simulation tool can never reflect the true results of a project. It is however a
useful tool when comparing different system arrangements in terms of economical and
technical feasibility. A deeper presentation of the HOMER simulation tool will be provided
in connection to the simulation. The result of the simulations will then form a basis where
conclusions and proposals can be drawn concerning system performance and reliability.
Step 6: Conclusion & Recommendation
After detail analysis of the collected data a new alternative solution for the towns proposed.
The analysis of the simulation results was based on simulation output information and its
logical relation with inputs and underlying power system design. Refer figure 1.8 below, the
thesis methodology and sequence of step as well as design to achieve the general and specific
objective of the study.
Main Report Final Master Thesis
Figure 1.4: Workflow and general outline of Research methodology
Main Report Final Master Thesis
1.8 Structure of thesis
This thesis paper includes seven chapters and four appendices, which are organized as
follows:
Chapter 1: Introduction overviews the rationale for this study. It includes rural energy
context and Electricity provision in rural areas, EEPCO background, objectives of the study,
methodology adopted; scope of the study, Present Status of Electric Supply for selected
towns, and the structure of the thesis.
Chapter 2: Wind power system comprises Introduction, Wind resource assessment,
Estimation of the frequency distribution and long term average Wind Speed, Wind Power
density distributions and mean power density, different Types of Turbines, general working
principles, power curve and turbines efficiency, Wind Speed Height Correction Annual wind
energy production and capacity factor
Chapter 3:Photovoltaic Power System comprises Introduction, PV electricity , General
working principles Photovoltaic Cells , Solar Module Power Characteristics and Operating
issue Photovoltaic Cells and Efficiencies , PV installation , Solar resource assessment of the
selected towns ,i Calculates the global radiation incident on the PV array , Calculates the PV
Cell Temperature and PV array power output.
Chapter 4: Batteries, PV controller, Inverters and Energy Consumption comprises
Introduction, Batteries Electricity, general working principles, storage capacity , battery
modeling , battery sizing ,Batter life time, Battery Design , Battery in hybrid system , PV
Controllers , Inverters , Inverter Sizing , Energy consumption for Kebridehar and Degehabur
towns and load forecasting
Chapter 5: Hybrid Energy Systems comprises Introduction, Stand Alone Hybrid System
Typical Stand Alone Hybrid Components and Efficiencies, Proposed Stand Alone Sizing
Optimization Procedure, Economic Evaluation of the Hybrid System, Breakeven Grid
Extension Distance, and System architecture.
Chapter 6: Results and Discussion comprises General, Simulation results Comparison with
“diesel only” system with hybrid system of the selected towns, Sensitivity results with
different diesel price scenarios, Comparison of the Grid extension with standalone system
(Off Grid).
Chapter 7: Conclusion and Recommendation presents conclusions that have been derived
from this study, followed by recommendations for further study and for practical
Main Report Final Master Thesis
implementation of a proposed option. This chapter concludes with a few brief final. Different
data tables and graphs are presented in the appendices
2. Wind power system
2.1 Introduction
Winds are produced by uneven solar heating of the earth’s land and sea surfaces. Thus, they
are a form of “solar” energy. On average, the ratio of total wind power to incident solar
power is on the order of two present, reflecting a balance between input and dissipation by
turbulence and drag on the surface.
Wind is the movement of air caused by the irregular heating of the Earth's surface. It happens
at all scales, from local breezes created by heating of land surfaces that lasts some minutes, to
global winds caused from solar heating of the Earth. Wind power is the transformation of
wind energy into more utile forms, typically electricity using wind turbines (Gipe, 2004).
2.2 History
Wind has always been an energy source used by several civilizations many years ago. The
first use of wind power was to make possible the sailing of ships in the Nile River some 5000
years ago. Many civilizations used wind power for transportation and other applications. The
Europeans used it to crush grains and pump water in the 1700s and 1800s. The first wind mill
to generated electricity in the rural U.S. was installed in 1890 (Patel, 2006). However, for
much of the twentieth century there was small interest in using wind energy other than for
battery charging for distant dwellings. These low-power systems were quickly replaced once
the electricity grid became available. The sudden increases in the price of oil in 1973
stimulated a number of substantial Government-funded programs for research, development
and demonstrations of wind turbines and other alternative energy technologies. In the United
States this led to the construction of a series of prototype turbines starting with the 38
diameter 100kW Mod-0 in 1975 and culminating in the 97.5m diameter 2.5MW Mod-5B in
1987. Similar programs were pursued in the UK, Germany and Sweden (T. Burton, 2001).
Today, even larger wind turbines are being constructed such as 5MW units. Wind generated
electricity is the fastest renewable growing energy business sector (Gipe, 2004).Growth in the
use of larger wind turbines, as made small wind turbines increasingly be attractive for small
applications such as, powering homes and farms. Wind power has become a very attractive
renewable energy source because it is cheaper than other technologies and is also compatible
with environmental preservation. Wind power showed a growth rate of 31.7 %, the highest
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rate since 2001. The trend continued that wind capacity doubles every three years. All wind
turbines installed by the end of 2009 worldwide are generating 340 TWh per annum,
equivalent to the total electricity demand of Italy, the seventh largest economy of the world,
and equaling 2 % of global electricity consumption (World Wind Energy 200).
Worldwide capacity reached 159,213 MW, out of which 38,312 MW were added in 2009 is
approximately 73,904MW. Figure 2.1[World Wind Energy 2009] shows the total installed in
the last few years and provide a prediction for 2010.
Figure 2.1: World Wind Energy - Total Installed Capacity (MW) (World Wind Energy 2009),
2009)
2.3 Location of Degehabuar and Kebri Dehar town
Degehabur and Keberedahr towns located within Ethiopia Coordinates and Somalia region:
8° 13 N, 43° 34 E and 6° 44 N, 44° 16 E respectively. The prevailing wind is the wind that
blows most frequently across a particularly region. Different regions on Earth have different
prevailing wind directions which are dependent upon the nature of the general circulation of
the atmosphere and the latitudinal
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Table 2.1 Prevailing Wind Directions region on Earth
Latitude Direction Common Name
90-60°N NE Polar Easterlies60-30°N SW Southwest Antitrades 30-0°N NE Northeast Trades
0-30°S SE Southeast Trades30-60°S NW Roaring Forties90-60°S SE Polar Easterlies
Source:(Climate)
The prevailing wind directions are important when sitting wind turbines, since we obviously
want to place them in the areas with least obstacles from the prevailing wind directions.
The prevailing wind of these towns comes from the northeast trade winds. We therefore need
not be very concerned about obstacles to the west or Southwest of wind turbines, since
practically no wind energy would come from those directions.
The monthly average wind direction for a given month of the two towns, averaged for that
month over the 10-year period (July 1983 - June 1993) and Wind direction values are for 50
meters above the surface of the earth. These value are presented in Appendix-B, table B.1.
2.4 Wind resource assessment for Degehabur and Keberedehar town
Wind resource is the most important element in projecting turbine performance at a given
place. The energy that can be extracted from a wind stream is proportional to the cube of its
velocity, meaning that doubling the wind velocity increases the available energy by a factor
of eight. Also, the wind resource itself rarely is a constant or has a steady flow. It varies with
year, season, time of day, elevation above ground, and form of terrain. Proper location in
windy sites, away from large obstructions, improves wind turbines performance.
Wind speed generally decreases as one move from higher latitudes towards the equator. The
energy transported to a higher altitude gets stronger as the latitude increases (i.e. as the area
decreases flow of energy density increases). However, the local effects might be quite
important - presence of geographic structures such mountains, valleys and coastal areas may
enhance wind speed. Ethiopia being located near the equator, its wind resource potential is
very much limited. There are few promising windy areas in Ethiopia located alongside the
main east African Rift Valley, the North Eastern escarpment of the country near Tigray
regional state and the eastern part of the country (near North east of the Somali regional
state).
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Wind data has been collected and documented by National Meteorological Service Agency
(NMSA) primarily for a purpose of aviation. This data is not of much use for estimation of
the resource as most of the met-stations do not qualify the required standard for wind speed
measurements. Most of the met station measurements for wind speed were taken at heights
lower than the accepted standard of 10 m and over half were taken at just 2 m above ground
level. The energy output from wind is very much dependent on wind speed. Estimation of the
resource is however not a precise art. Identification of locations for wind energy generation
depends on several factors other than the speed of the wind. Physical accessibility of
locations, proximity to electricity grid, exclusion of designated areas such as national parks
and visual impacts on areas of outstanding beauty are some of the factors that need to be
taken into consideration while estimating the potential of the resource (Development, 2007).
The estimation considers the whole land area of the country that practically fall under various
wind resource categories without excluding land areas that could possibly be eliminated for
reasons of accessibility, economics or environmental. This estimation provides the bigger
picture of the country in terms of locating windy areas. The practicable potential is certainly
lower than the first estimation as more land will be eliminated with further screening
(Development, 2007).
Areas estimated to have Moderate and higher (Class 3 and above) wind resource are
primarily located in the highlands featuring a sudden change in altitude from the neighboring
land masses. These areas are basically the escarpments along the Great Rift Valley extending
to the Southern, Eastern, North Eastern parts of the country, and the Central highlands. The
strongest wind resource with energy density per annual above 800 W/m2 is located on the
ridge of the highlands in the central part of the rift valley (Development, 2007).
See figure 3 wind map of Ethiopia with including projects area of at a height of 50m above
the ground.
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Figure 2.2: A GIS map showing geographic distribution of wind resources of Ethiopia (Source: SWERA)
The wind resource classifications, Class 1 to Class 7, are indicated by color-codes as
indicated in the GIS map above– Class 7 indicating the strongest wind regions. Each color
code has an assigned range of values to represent annual wind power density in W/m2.
In addition to wind map from SWERA, there is another wind speed data obtained from
NASA is presented in figure 2.3 below. From these wind resources data, we can have an
initial idea of about wind speed resource and their energy potential of the selected sites. Both
wind map and wind speed data seem to have correlated. Wind resources data are significant
for the long term wind power forecasting to establish a reliable hybrid energy system design
for the two towns. The data is presented in the Figure 2.1 was ten years monthly average
wind speed of the two towns.
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Figure 2.3 Monthly Averaged Wind Speed at 50 m above the Surface of the Earth (m/s) for Degehabur and Keberdehar town. (Source: NASA)
Referred Figure 2.3 above, the windiest month of years was recorded in July and the lowest
wind speed was recorded on the month of April and average wind speed of Kebredehar a bit
higher than Degehabur.
2.4.1 Estimation of the frequency distribution and long term average Wind Speed
of Degehabur and Kebedehar town
In probability theory and statistics, the Weibull distribution is a continuous probability
distribution. It is named after Waloddi Weibull who described it in detail in 1951, although it
was first identified by Fréchet (1927) and first applied by Rosin & Rammler (1933) to
describe the size distribution of particles. In probability theory, a probability density function
(abbreviated as PDF, or just density) of a continuous that describes the relative likelihood for
this random variable to occur at a given point in the observation space (Wikipedia, 2010).
The probability of a random variable falling within a given set is given by the integral of its
density over the set. In most locations worldwide, the distribution of wind speeds keeps fairly
close to a Weibull or (simplified) Rayleigh distribution of wind speeds, shown below figure
2.4. There are non-Rayleigh locations where the curve takes on other shapes, but these are
relatively rare. The distribution shown here is relatively common.
Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec
Degehabur 5.75 5.39 4.51 3.43 4.59 7.27 7.64 7.11 5.64 3.88 4.71 5.49
Keberedehar 5.98 5.72 4.65 3.68 5.88 8.19 8.4 7.96 6.51 4.26 4.12 5.49
0
1
2
3
4
5
6
7
8
9w
ind
spee
d in
(m/s
) Degehabur
Keberedehar
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Figure 2.4: Rayleigh Densities Function for Various Mean Wind speed. (Shenck)
Notes: the k=2 form of the Weibull PDF, commonly known as the Rayleigh density function.
If the probability density is known, alternatively, the mean wind speed can be determined
from
2-1
The wind speed probability distributions and the functions representing them mathematically
are the main tools used in the wind-related literature. Their use includes a wide range of
applications, from the techniques used to identify the parameters of the distribution functions
to the use of such functions for analyzing the wind speed data and wind energy economics.
Two of the commonly used functions for fitting a measured wind speed probability
distribution in a given location over a certain period of time are the Weibull and Rayleigh.
The probability density function of the Weibull distribution is given by (Celik, 2003),
2-2
Where: -
Thus the cumulative distribution is the integral of the probability density function. The
cumulative probability function is(sustainable energy among option):
) 2-3
is the wind speed
Where k > 0 is the shape parameter and c >0 is the scale parameter of the distribution.
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The shape factor will normally range from 1 to 3. These typical values are known from
experience and multiple observations of sites where wind speed measurements have been
taken. These wind types are categorized as inland, coastal, and trade wind (off-shore) sites.
Table 2.2 shows typical values for the shape factor (RETSCREEN).
Table 2.2 Typical Shape Factor Values
Types of wind Shape factor (k) Inland Winds 1.5 to 2.5 Coastal Winds 2.5 to 3.5 Trade Winds 3 to 4
If Weibull k is not known, use k = 2 for inland sites, use 3 for coastal sites, and use 4 for
island sites and trade wind regimes
If Eq. (3) is solved together with Eq. (4) making the substitution of =(v/c)k for v, the
following is obtained for the mean wind speed,
2-4
2-5
For k=2, the following is obtained from Eq.2-1
for Degehabur
town where as average wind speed is 5.91m/s and scale factor 6.68 m/s for Keberedehar
town.
For this thesis A Weibull factor of 2 (k=2) since the selected towns for inland sites were used
to develop probability density function (PDF) hourly profile of the wind speeds for a
hypothetical year. Figure 2.8 and 2.9 shows the probability distribution function of the
baseline wind resources for Kebri Dehar and Dehehabur with the best-fit line smoothing
function overlaid. The detail probability density function of wind speed of throughout the
years for the two towns are presented in Appendix-B, table B.2 and table B.3.
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Figure 2.5 Probability density vs. wind speed at hub height for Keberehar town
Note: Mean Annual Average = 5.45 m/s
Figure 2 6: Probability density vs. wind speed at hub height in Degehabur Town
Note: Mean Annual Average = 5.45 m/s
One of the most distinct advantages of the Rayleigh distribution is that the probability density and the cumulative distribution functions could be obtained from the mean value of the wind speed.
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Moreover, the diurnal pattern strength is a measure of how strongly the wind speed tends to
depend on the time of day. Because the wind is typically affected by solar radiation, most
locations show some diurnal (or daily) pattern in wind speed.
In order to measure the strength of the diurnal pattern, it can calculate the average diurnal
profile. Each of the 24 values of the average diurnal profile represents the annual average
wind speed for that hour. It then fits a cosine function to this average diurnal profile The
cosine function fitted to the average diurnal pattern is of the form (NREL, 2008):
2-6
The anemometer height at which data was collected is 50 m according to the data source,
NMSA. Typical values for diurnal pattern strength range from 0 to 0.4 (NREL, 2008); by
varying the values within the range, repeatedly running the software and checking the results
against the measured data, a value of 0.25 has been selected. The autocorrelation function is a
measure of the tendency of what a wind speed is likely to be, given what it was earlier
(NREL, 2008). For complex topography the autocorrelation factor is (0.70 - 0.80) while for a
uniform topography the range is higher, (0.90 - 0.97). A typical range for the autocorrelation
factor is 0.8 – 0.95 (NREL, 2008). An average value of 0.85 is used here because the selected
towns are of averagely uniform topography. The typical range for the time of peak wind
speed, which is the time of day that tends, on average, to be the windiest throughout the year,
is 14:00-16:00 (NREL, 2008). This has also been observed in the available raw data for some
of the months. In addition to this, the software has been run for different times between 14:00
and 18:00, the results have been checked against the measured data and the time of 15:00 has
been chosen for the calculations.
The figure below indicate that the wind speed variation with 24 hours. As you observed in the
figure the highest wind speed occur during around 15:00 each consecutive month and it is
just the sun directly overhead at solar noon. Figures 2.1 and 2.3 show daily wind speed
profiles of Kebri Dehar and Degehabur respectively. The detail value of daily wind speed
variation of pattern is presented in Appendix-B, table B.3 and table B.4.
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Figure 2.7 Wind speed daily profile for Keberedar
Figure 2.8: Wind speed daily profile for Degehabur town
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2.4.2 Wind Power density distributions and mean power density
The monthly average wind speed using Weibull distributions is determined as in Eq.2-4:
The power of the wind per unit area is given as:
2-7
The average power density for each month is calculated using actual probability density
distribution for the specified month, which is calculated using Eq.2-8, and is given as:
2-8
Where, the subscript m stands for the month and n is the number of records for the specified
month.
The average power density using Weibull probability distribution is calculated as follows:
2-9
From the above equation for k=2, the following is obtained
is the gamma function and given as:
For k=2, the following is obtained from Eq.2-5
From Eq. 2-5 for k=2 and
Finally power density each month is calculated as follow:
2-10
From the equation 2-10, we get the wind power density values each month for two towns.
This figure is obtained in table 2.3 below. Table 2.3: wind Power density for Degehabur and Keberedehar towns
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For Degehabur town For Keberdehar town
Month
Monthly average
windspeed
Scale factor
Power density(W/m2)
Monthly average
windspeed
Scalefactor
Power density(W/m2)
Jan 5.75 6.49 222.50 5.98 6.75 250.28 Feb 5.39 6.08 183.27 5.72 6.45 219.03 Mar 4.51 5.09 107.36 4.65 5.25 117.67 Apr 3.43 3.87 47.23 3.68 4.15 58.33 May 4.59 5.18 113.18 5.88 6.63 237.93 Jun 7.27 8.20 449.70 8.19 9.24 642.95 Jul 7.64 8.62 521.92 8.4 9.48 693.68
Aug 7.11 8.02 420.66 7.96 8.98 590.29 Sep 5.64 6.36 209.97 6.51 7.35 322.90 Oct 3.88 4.38 68.36 4.26 4.81 90.48 Nov 4.71 5.31 122.29 4.12 4.65 81.85 Dec 5.49 6.19 193.66 5.49 6.19 193.66
Monthly annual
average 5.45 6.15 189.46 5.91 6.67 241.59
The power densities values consider in the table 2.4 is calculated by using Eq 2.4 and Eq
2.10.It is clearly indicated that a figure inside the table 2.4, the power density for Dehehabur
is not fairly constant and shows a large month to month variation. The minimum power
densities occur in April and October, with 47.23 and 68.36 W/m2, respectively. It is
interesting to note that the highest power density values occur in the summer months of June,
July and August, with the maximum value of 521.92 W/m2 in July. The power densities in
the remaining months are between these two groups of low and high.
Power density is also varies with monthly average wind speed. Monthly average wind speed
of Kebredehar is a bit higher than average monthly wind speed of Deghabur.In the table 2.3
show that the minimum power densities occur in April and November, with 58.33 and 81.85
W/m2, respectively. Likewise, Degehabur highest power density values occur in the summer
months of June, July and August, with the maximum value of 693.68 W/m2 in July and the
power densities in the remaining months are between these two groups of low and high..
Estimates of wind power density are presented as wind class, ranging from 1 to 7. The speeds
are average wind speeds over the course of a year, although the frequency distribution of
wind speed can provide different power densities for the same average wind speed. See table
2.4 below.
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Table 2.4: wind class category by wind speed and power density
Class 10 m (33 ft) 30 m (98 ft) 50 m (164 ft) Wind power
density (W/m2)
Speed m/s (mph)
Windpowerdensity (W/m2)
Speed m/s (mph)
Windpower density (W/m2)
Speed m/s
(mph)
1 0 - 100 0 - 4.4 0 - 160 0 - 5.1 0 - 200 0 - 5.6 (0 - 9.8) (0 - 11.4) (0 -
12.5)2 100 - 150 4.4 - 5.1 160 - 240 5.1 - 5.9 200 - 300 5.6 - 6.4
(9.8 - 11.5) (11.4 - 13.2)
(12.5 - 14.3)
3 150 - 200 5.1 - 5.6 240 - 320 5.9 - 6.5 300 - 400 6.4 - 7.0 (11.5 - 12.5) (13.2 -
14.6) (14.3 - 15.7)
4 200 - 250 5.6 - 6.0 320 - 400 6.5 - 7.0 400 - 500 7.0 - 7.5 (12.5 - 13.4) (14.6 -
15.7) (15.7 - 16.8)
5 250 - 300 6.0 - 6.4 400 - 480 7.0 - 7.4 500 - 600 7.5 - 8.0 (13.4 - 14.3) (15.7 -
16.6) (16.8 - 17.9)
6 300 - 400 6.4 - 7.0 480 - 640 7.4 - 8.2 600 - 800 8.0 - 8.8 (14.3 - 15.7) (16.6 -
18.3) (17.9 - 19.7)
7 400 - 1000 7.0 - 9.4 640 - 1600
8.2 - 11.0 800 - 2000 8.8 - 11.9
(15.7 - 21.1) (18.3 - 24.7)
(19.7 - 26.6)
Source: (wikipedia, 2010)
Refer table 2.3 and 2.4, specified that Degehabur annual average wind speed and power
density distribution categorized in first wind class whereas Keberedehar categorized in the
second class. But wind class each month of both towns varies from first to sixth wind class.
2.5 Wind Turbines
2.5.1 Different Types of Turbines
A wind turbine is a machine that converts the kinetic energy from the wind into mechanical
energy. If the mechanical energy is used directly by machinery, such as a pump or grinding
stones, the machine is usually called a windmill. If the mechanical energy is then converted
to electricity, the machine is called a wind generator (Gipe, 2004).
There are a number of different wind turbine types available. The horizontal axis turbine,
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HAWT is by far the most common type of turbine. They come in two different types: the
upwind, which face the wind (tower behind rotor) and the downwind arrangement that works
away from the wind (tower in front). Another kind of turbine is the vertical axis, VAWT
arrangement that uses drag and lift as the driving forces; the horizontal also uses drag and lift,
but in other proportions.
The advantages with upwind turbines are that the tower does not act as an obstacle for the
wind hitting the rotor. Despite this, the flow behind the passing blade is affected by the tower
and causes a slight drop in power. When the blade passes the tower it also decreases the drag
on the construction which can cause an on / off bending process causing fatigue stress. This
has of course been taking into account when designing the turbine. The upwind design needs
a control system that helps the nacelle turn straight to the wind. In downwind turbines, the
tower shades a rotor blade each time it passes by and causes greater power losses compared
to the upwind design. An advantage with downwind turbines is that the nacelle is self-
adjusting and is not in need of a control system. One drawback with this is the problem with
untwisting the cable inside when the nacelle has turned same direction repeatedly. The
VAWT´s are not as commercial and economically competitive as the HAWT´s. Some of the
VAWT types suffer from low efficiency due to design difficulties as well as the problem with
operation close to the ground. Parts of the vertical turbines will therefore receive low quality
winds causing power losses. To keep the construction upright it also needs to be supported
with guy cables attached to the ground. The vertical turbine is not in need of yaw control,
which of course is an advantage and the wind always hits the turbine tangentially (Boyle,
1996).
The modern wind turbine is a sophisticated piece of machinery with aerodynamically
designed rotor and efficient power generation, transmission and regulation components. The
size of these turbines ranges from a few Watts (Small Wind Turbines) to several Million
Watts (Large Wind Turbines). The modern trend in the wind industry is to go for bigger units
of several MW capacities in places where the wind is favorable, as the system scaling up can
reduce the unit cost of wind-generated electricity. Most of today's commercial machines are
horizontal axis wind turbines (HAWT) with three bladed rotors.
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Figure 2.9: Horizontal axis wind turbines (HAWT) are either upwind machine or down wind machines
(a) Upwind machine (b) Or down wind machines (c). Vertical axis wind turbines (VAWT) accept wind from any direction (Masters, 2004.)
2.5.2 Wind Turbines Components
The most common turbine type is the horizontal axis wind turbine. A cut-view (Figure 2.10)
helps the reader to get familiar with the components of a wind turbine.
Figure 2.10: Cut-view of a wind turbine. (Source: DOE/NREL)
Anemometer:
Measures the wind speed and transmits wind speed data to the controller.
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Blades:
Most turbines have either two or three blades. Wind blowing over the blades causes the
blades to "lift" and rotate.
Brake:
A disc brake, which can be applied mechanically, electrically, or hydraulically to stop the
rotor in emergencies.
Controller:
The controller starts up the machine at wind speeds of about 8 to 16 miles per hour (mph) and
shuts off the machine at about 55 mph. Turbines do not operate at wind speeds above about
55 mph because they might be damaged by the high winds.
Gear box:
Gears connect the low-speed shaft to the high-speed shaft and increase the rotational speeds
from about 30 to 60 rotations per minute (rpm) to about 1000 to 1800 rpm, the rotational
speed required by most generators to produce electricity. The gear box is a costly (and heavy)
part of the wind turbine and engineers are exploring "direct-drive" generators that operate at
lower rotational speeds and don't need gear boxes( DOE/NREL)
Generator:
It usually an off-the-shelf induction generator that produces 60/50-cycle AC electricity.
High-speed shaft:
It drives the generator.
Low-speed shaft:
The rotor turns the low-speed shaft at about 30 to 60 rotations per minute.
Nacelle:
The nacelle sits atop the tower and contains the gear box, low- and high-speed shafts,
generator, controller, and brake. Some nacelles are large enough for a helicopter to land on.
Pitch:
Blades are turned, or pitched, out of the wind to control the rotor speed and keep the rotor
from turning in winds that are too high or too low to produce electricity.
Rotor:
The blades and the hub together are called the rotor.
Tower:
Towers are made from tubular steel (shown here), concrete, or steel lattice. Because wind
speed increases with height, taller towers enable turbines to capture more energy and generate
more electricity.
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Wind direction:
This is an "upwind" turbine, so-called because it operates facing into the wind. Other turbines
are designed to run "downwind," facing away from the wind.
Wind vane:
Measures wind direction and communicate with the yaw drive to orient the turbine properly
with respect to the wind.
Yaw drive:
Upwind turbines face into the wind; the yaw drive is used to keep the rotor facing into the
wind as the wind direction changes. Downwind turbines don't require a yaw drive; the wind
blows the rotor downwind (DOE/NREL)
Yaw motor:
Powers the yaw drive.
2.5.3 General Workings
The blade, using aerodynamic lift, capture energy from wind in order to turn the shaft. In
small wind turbines the shaft usually drives the generator directly. The generator converts the
mechanical energy into electricity. The shaft power causes coils to spin past alternate poles of
magnets allowing electric current to flow. If a permanent magnet device is being used the
opposite occur: current flow as magnets spin past coil windings. Most small wind turbines
use a permanent magnet alternator. Large wind turbines usually use either induction
generator or a synchronous generator. In addition, in large wind turbines the shaft connected
to the generator via a gearbox those steps up the rotational speed for the generator.
In off-grid application it is difficult to keep the frequency of the resulting current constant, as
it depends on wind speed which is highly variable. Therefore the current is usually rectified
to give DC.
Most wind turbines have two or three blade. Two blade machines are somewhat less
expensive. Three bladed machines suffer less mechanical stress and are less vulnerable to
fatigue problem. The Yaw bearing allows a wind turbine to rotate in order to face to the wind
from any direction. A tower support wind turbine and places it above any obstruction.
2.5.4 Wind system design
If the generator is undersized, the turbine will reached peak power at relatively low wind
speed and stay until the cut out speed reached. If the turbine is oversized, then power will
increase until the cut out speed reached.
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The energy output of a wind turbine can be calculated by determining the frequency
distribution local wind speed and then computing the expected range of power outputs for
each wind speed by using power curve.
The wind turbine load and hence speed governed electrically by voltage controller and
mechanical by counterweights which reduce the pitch of the blade in the event of excess wind
speed or energy production
2.5.3 Wind turbine in hybrid system
Wind turbine single-source systems tend to produce highly variable and therefore unreliable
power supply due to the irregular wind speeds. If the wind turbine is combined with other
sources a hybrid system the produced energy can become more regular improving system
performance and cost effectiveness.
2.5.4 Wind Turbines Efficiency and Power Curve
The theoretical limit of power extraction from wind, or any other fluid was derived by the
German aerodynamicist Albert Betz. Betz law, [Betz, 1966], states that 59% or less of the
kinetic energy in the wind can be transformed to mechanical energy using a wind turbine. In
practice, wind turbines rotors deliver much less than Betz limit. The factors that affect the
efficiency of a turbine are the turbine rotor, transmission and the generator. Normally the
turbine rotors have efficiencies between of 40% to 50%. Gearbox and generator efficiencies
can be estimated to be around 80% to 90%. Also efficiency of a turbine is not constant. It
varies with wind speeds. Many companies do not provide their wind turbine efficiencies.
Instead they provide the power curve.
A power curve is a graph that represents the turbine power output at different wind speeds
values. The advantage of a power curve is that it includes the wind turbines efficiency. The
power curve is normally provided by the turbine’s manufacture. Figure 2.6 presents four
types of a wind turbine power curve. From the first two types turbines, note that at speeds
from 0 to 2.9m/s the power output is zero. This occurs because there is not sufficient kinetic
energy in the wind to move the wind turbine rotor where as for the second two types of
turbines that which are WES18 and WES30 cut-in speed are 4 and 5m/s respectively.
Normally the manufactures provide a technical data sheet where the startup wind speed of the
turbine is given. In general lower start up wind speeds result in higher energy coming from
the turbine. the power curve provide in the turbines manufacturer, the EOLTEC types of
turbines is still rotate with a lower speed (that is cut-in speed is 3m/s) compare of WES types
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of turbines (the cut-in speed are 4 and 5m/s) There is also another important data which the
turbines is operating without any mechanical failure and this parameter is called the cut-out
speed. From the figure 2.6 observed that the cut-out speed of EOLTEC types of turbine is
around 20m/s whereas WES types of turbine is 25m/s.
Figure 2.11: Different type wind turbines power curves being considered for the selected wind farm
0
50
100
150
200
250
300
1 3 5 7 9 11 13 15 17 19 21 23 25 27
Pow
er in
(kW
)
Wind Speed in (m/s)
EOLTEC Power Output
WES 18 Power Output
WES 30 Power Output
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Figure 2.12: Power output of EOLTEC CHINOOK 17-65 Wind Turbines with steady wind speed characteristics.
The hourly output power of a WTG can be easily obtained from the simulated hourly wind
speeds using Equation (2.12). The simulated output power of a 65 kW wind generator with
operating parameters of cut-in, rated and cut-out wind speeds of 2.3 m/s, 11 m/s and 20 m/s.
The output power of the WTG is between 0 and its power rating of 65 kW. Major technical
data for an EOLTEC CHINOOK 17-65 Wind Turbines including the power curve are given
in Appendix-C. From the above characteristic curve, there are three important points at which
much attention is paid for the speeds and the corresponding turbine output powers for every
wind turbine. These are the cut-in speed, rated output speed and cut-out speed. The important
terms characterizing the turbine power-speed (Figure 2.12) characteristics are described
below:
• Cut-in speed – at very low wind speeds, there is insufficient torque exerted by the wind on
the turbine blades to make them rotate. However, as the speed increases, the wind turbine will
begin to rotate and generate electrical power. The speed at which the turbine first starts to
rotate is called the cut-in speed and is typically between 3 and 4 meters per second
(WindPowerProgram).
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• Rated output power and rate output wind speed – as the wind speed rises above the cut-
in speed, the level of electrical output power rises rapidly. However, typically somewhere
between 12 and 17 meters per second, the power output reaches the limit that the electrical
generator is capable of. This limit to the generator output is called the rated power output and
the wind speed at which it is reached is called the rated output wind speed. At higher wind
speeds, the design of the turbine is arranged to limit the power to this maximum level and
there is no further rise in the output power. How this is done varies from design to design but
typically with large turbines, it is done by adjusting the blade angles so as to keep the power
at the constant level (WindPowerProgram)
• Cut-out speed – as the speed increases above the rate output wind speed, the forces on the
turbine structure continue to rise and, at some point, there is a risk of damage to the rotor. As
a result, a braking system is employed to bring the rotor to a standstill. This is called the cut-
out speed and is usually around 25 meters per second (WindPowerProgram) .
• A furling speed ( ) is approximately twice that of the rated speed .This means the
turbine control system is able to maintain a constant power output over an eight to one range
of wind power input.
As the scale and shape parameter have been calculated, two meaningful wind speeds—the
most probable wind speed and the wind speed carrying maximum energy—can easily be
obtained. The most probable wind speed denotes the most frequent wind speed for a given
wind probability distribution and the wind speed carrying maximum energy represents the
wind speed which carries the maximum amount of wind energy (Akpinar, 2004). They can be
expressed as:
2-10
2-11
2.6 Wind Speed Height Correction
For idealized smooth plane surface, the average wind speed increases with height
approximately as the 1/7th power:
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2-12
Where the wind speed at the desired height is , is the wind speed measured at
a known height , and is a coefficient known as the wind shear exponent. The wind shear
exponent varies with pressure, temperature and time of day. A commonly use value use is
one-seventh (1/7) and which is more applicable over open land surfaces.
Thus, a wind turbine with hub elevation of 50m will, relatively a height of 30m, sees an
average wind speed some 7.6% higher. Because available power varies as velocity cubed, the
higher position can increase turbine power by 24.5%, an appreciable improvement. As a
result, selection of the tower height is a major cost-benefit tradeoff. Other factors complicate
this chose, for example: Topography and vegetation alter the wind speed. Crest of treeless
hills are advantageous, however, the flow above hills does not follow the 1/7th power law
There also another formula that wind speed on height correction. As you know wind speed
always affected by local factor which are hills, building and topography where the wind
turbine install. This formula is best estimation of the wind speed at hub height. For this thesis
it uses logarithmic law of wind speed correction since it include local factor which affect the
wind speed. The most general equation to calculate wind speed at hub height is as follow,
2-13
The surface roughness length is a parameter that characterizes the roughness of the
surrounding terrain. The table below contains representative surface roughness lengths taken
from Maxwell, McGowan, and Rogers (NREL, 2008): Table 2.5: Representative surface roughness lengths different terrain (source: HOMER)
Terrain Description z0
Very smooth, ice or mud 0.00001 mCalm open sea 0.0002 m Blown sea 0.0005 m Snow surface 0.003 m Lawn grass 0.008 m Rough pasture 0.010 m Fallow field 0.03 m Crops 0.05 m Few trees 0.10 m Many trees, few buildings 0.25 m Forest and woodlands 0.5 m Suburbs 1.5 m City center, tall buildings 3.0 m
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2.7 Wind Power
The power (P) in the wind is a function of air density ( ), the area intercepting the wind (A),
and the instantaneous wind velocity (V), or the speed. Increasing these factors will increase
the power available from wind. Equation 2-14 shows the relationship between these
parameters but all this parameters is included on the power curve of any wind turbines.
2-14
Where P is the power output in (watts), is the air density in (kg/m³), A is the area where
wind is passing (m²) and V is the wind speed in (m/s).
To calculate the output of the wind turbine in a particular hour, it follows a three-step
process:
It takes that hour's wind speed from the wind resource data and adjusts it to the hub height
using either the logarithmic profile or the power law profile, as described in Wind Shear
Inputs.
It refers to the wind turbines power curve to calculate the power output under standard
conditions of temperature and pressure.
It multiplies that value by the air density ratio. It calculates the air density ratio using in Eq 2-
15 (NREL, 2008) :
2-15
The air density under standard conditions (sea level, 15 degrees Celsius) is 1.22kg/m3
The average power output from a wind turbine is the power produced at each wind speed
times the fraction of the time that wind speed is experienced, integrated over all possible
wind speeds.
The electric power output of a WTG in the up state depends strongly on the wind regime as
well as on the performance characteristics and the efficiency of the generator. Given the
hourly wind speed variations, the next step is to determine the power output of the WTG as a
function of the wind speed. This function is described by the operational parameters of the
WTG. The parameters commonly used are the cut-in wind speed (at which the WTG starts to
generate power), the rated wind speed (at which the WTG generates its rated power) and the
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cut-out wind speed (at which the WTG is shut down for safety reasons). The hourly output of
a WTG can be obtained from the simulated hourly wind speed by applying Equation 2-
16.The following equations for the electrical power output of a model wind turbine:
2-16
The coefficients a and b are given by
The relationship can also be illustrated graphically as shown in Figure 2.12 and is often
referred to as the “Power Curve”. Actual power curve for a particular WTG shown in the
figure 2.12 can be obtained from the manufacturer.
The Rayleigh distribution is a special case of the Weibull distribution with k = 2 and is often
sufficiently accurate for analysis of wind power systems. This value of k should be used if the
wind statistics at a given site are not well known. If Weibull k is not known, use k = 2 for
inland sites, use 3 for coastal sites, and use 4 for island sites and trade wind regimes Wind
turbine power output daily profile for Kebridehar and Degehabur towns is presented in
Appendix-C, table C.1 and C2.
2.7.1 Swept Area
As shown in equation 2-2, the output power is also related to the area intercepting the wind,
that is, the area swept by the wind turbines rotor. Double this area and you double the power
available. For the horizontal axis turbine, the rotor swept area is the area of a circle:
2-17 Where D is the rotor diameter in meters. The relationship between the rotor’s diameter and
the energy capture is fundamental to understanding wind turbine design. Relatively small
increases in blade length or in rotor diameter produce a correspondingly bigger increase in
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the swept area, and therefore, in power. Nothing tells you more about a wind turbines
potential than rotor diameter. The wind turbine with the larger rotor will almost invariably
generate more electricity than a turbine with a smaller rotor, not considering generator
ratings.
2.8 Annual wind energy production and capacity factor
The average power output of a turbine is a very important parameter of a wind energy system
since it determines the total energy production and the total income. It can be obtained by
multiplying the power produced at each wind speed and the fraction of the time that wind
speed has been experienced, integrated overall wind speeds.
The capacity wind turbines any site can be given as:
2-18
The capacity factors for Kebri Dehar and Degehabur towns are 22.8% and 17.8%
respectively.
The annual energy production wind turbines given as,
E= 2-19
The selected wind turbine must match the wind characteristics at the site and it should yield
an optimum energy with a high capacity factor (CF) to meet the electrical energy demand.Table 2.6: Technical Data of EOLTEC CHINOOK 17-65 Wind Turbine
Technical Data of EOLTEC CHINOOK 17-65 Wind Turbine
Rated power 65 kW @ 10 m/s Cut-in wind speed 2.3 m/s Cut-out wind speed 20 m/s Rated wind speed 11 m/s Survival speed 50 m/s Number of rotor blades 3Rotor diameter 17 m Swept area 227 m2 Rotor speed (variable) 25-75 rpm Power control Active blade pitch control Hub height 32-40 m (40 m is used for simulations)
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Predicted annual and monthly energy production from a single EOLTEC CHINOOK 17-65
Wind Turbine for the towns presented in table 2.6 below. Table 2.7: Predicted annual and monthly energy production from a single EOLTEC CHINOOK 17-65 Wind Turbine for the two towns
Degehabur ( annual wind speed 5.45 m/s) Kebri Dehar ( annual wind speed 5.91 m/s)
EOLTEC CHINOOK 17-65 EOLTEC CHINOOK 17-65
Predicted energy production Predicted energy production
Average output power 10.95 kW Average output power 13.80 kW
Daily energy production 262.7 kW.h Daily energy production 331.2 kW.h
Monthly energy production 7,990 kW.h Monthly energy production 10,074 kW.h
Annual energy production 95,884 kW.h Annual energy production 120,893 kW.h
Source Manufacturer excel sheet
The most common generator used in wind turbines is the induction generator. Asynchronous
generator became popular in medium-size and some households size wind turbines for
several reasons: they are readily available, robustness and mechanical simplicity, they are
inexpensive and they can supply utility-compatible electricity without sophisticated
electronic inverters.
Doubly Fed Induction Generator also the future technology. This technology is under
research and development phase and very promising with mechanical simplicity and cost as
well as which is easily connect to utility line.
Homer wind turbines types data base it has limited types of technology incorporate with this
software and only being considered three types wind turbines technology for this study.
The total annual energy production wind turbines of the two towns will be discuss on the
chapter six in result and discussion sub topic.
3. PHOTOVOLTAIC POWER SYSTEMS
3.1 Introduction
Photovoltaic (PV) solar cells made of semiconductors materials generates electrical power,
measured in Watts or Kilowatts, when they are illuminated by photons. Many PV have been
in continuous outdoor operation on Earth or in space for over 30 years (A. Luque, 2003).
3.2 History
The photovoltaic history starts in 1839 when a French physicist Alexander Edmond
Becquerel discovered the photovoltaic effect while experimenting with an electrolytic cell
made up of two metal electrodes. When the cells were exposed to light the generation of
electricity increased (USDE, 2004). In 1954 Bell Laboratories produced the first silicon cell.
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It soon found applications in U.S. space programs for its high power-generation capacity per
unit weight. Since then it has been extensively used to convert sunlight into electricity for
earth-orbiting satellites. Having matured in space applications, PV technology is now
spreading into terrestrial applications ranging from powering remotes sites to feeding utility
grids around the world. Economically speaking in the past the PV cost was very high. For
that reason, PV applications have been limited to remote locations not connected to utility
lines. But with the declining prices in PV, the market of solar modules has been growing at
25 to 30% annually during the last 5 yr (Patel, 2006).
Figure 3.1: Solar Module Retail Price Index
The figure indicated the figure 3.1, as of September 2010; there are now 546 solar module
prices below $4.00 per watt (€2.92 per watt) or 42.6% of the total survey. This compares with
527 price points below $4.00 per watt (€3.12 per watt) in September (Solarbuzz, 2010).
The lowest retail price for a multicrystalline silicon solar module is $1.97 per watt (€1.44 per
watt) from a US retailer. The lowest retail price for a monocrystalline silicon module is also
$2.21 per watt (€1.61 per watt), from a German retailer (Solarbuzz, 2010)
Note, however, that "not all models are equal." In other words, brand, technical attributes and
certifications do matter.
The lowest thin film module price is at $1.40 per watt (€1.02 per watt) from a United States-
based retailer. As a general rule, it is typical to expect thin film modules to be at a price
discount to crystalline silicon (for like module powers). This thin film price is represented by
a 60 watt module (Solarbuzz, 2010).
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3.3 Photovoltaic
The solar cells that are used on calculators and satellites are photovoltaic cells or modules.
This PV module consists of many PV cells wired in parallel order to increase current and in
series to produce a higher voltage. Use of 36 cell modules are the industry standard for large
power production. When we speak of a PV panel it means any number of PV modules and
when we speak of array it means any number of PV panels. Individual PV cells are typically
only a few inches in diameter, but multiple cells can be connected to one another in modules,
modules can be connected in arrays, and arrays can be connected in very large systems. See
figure 3.2.
Figure 3.2: PV Diagram
3.3.1 PV electricity
PV panel convert to sunlight to DC electricity. The PV generated electricity is ‘silent’, low in
maintenance and does not need in fuel or oil supplies. However, PV energy is available when
enough irradiance is accessible. PV panel is available in wide variety of rating up to
100Wp.In some cases, panel up to 300Wp each are manufactured. There is also AC PV
panels by including an inverter into the panel set-up to enable easy and modular AC bus
connection. A slight economy scale can often be noted for the different panel sizes up to
100Wp, however after that the size cost will increase circa linearly with size. The main
disadvantage PV is its high capital costs even though it is hope that the panel costs might
come down the future cost. PV can be cost-effective for small power requirements in areas
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remote from the existing grid. According to recent figure show that PV panel last depending
on their types over 15-30 years.
3.3.2 General working principles Photovoltaic Cells
PV cells convert sunlight directly into electricity by taking advantage of the photoelectric
effect. Cells are constructed from semiconductor materials coated with light-absorbing
materials. When photons in sunlight strike the top layer of a PV cell, they provide sufficient
energy to knock electrons through the semiconductor to the bottom layer, causing a
separation of electric charges on the top and bottom of the solar cell. Connecting the bottom
layer to the top with a conductor completes an electrical circuit and allows the electrons to
flow back to the top, creating an electric current and enabling the cycle to repeat with more
sunlight (Clean Energy Associates). Figure 3.3 illustrates how photovoltaic cells work.
Figure 3.3: How Photovoltaic Cells Work (Clean Energy Associates)
3.3.3 Solar Module Power Characteristics and Operating issue
PV panels have a specific voltage-current relationship, which is depicted in an IV-curve. The
maximum power point (MPP) operation is where the maximum panel output power is
obtained with a given irradiation and temperature.
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Manufactures typically provides I-V curves speciation at different levels of irradiance
keeping other variables such as temperature and wind speed constant figure3.2.PV panel
generates at constant irradiation levels roughly constant current from short circuit current to
just before the current value near the open circuit voltage. If the irradiance increases, the PV
panel output increase linearly. The maximum power point voltage stays nearly unaffected by
the level of irradiance, and open circuit voltage changes only slightly (Jimenez-98).
To account for the effect of panel temperature, manufactures will usually I-V curves for
various temperatures keeping irradiance level constants. The open circuit voltage (current is
zero) decreases with increasing temperature, while short circuit (voltage is zero) increase
only slightly, leading to decreased power production of the panel (Jimenez-98).
An I-V curve as illustrated in figures 3.4 is simply all of a module’s possible operating points,
(voltage/current combinations) at a given cell temperature and light intensity. Increases in
cell temperature increase current slightly, but drastically decrease voltage.
Maximum power is derived at the knee of the curve. Check the amperage generated by the
solar array at your battery’s present operating voltage to better calculate the actual power
developed at your voltages and temperatures (Kyocera, 2009).the detail technical
specification solar PV module indicated in Appendix-D.
.Figure 3.4: I-V curves showing the effect of solar isolation and temperatures on PV panel performance
3.3.4 Photovoltaic Cells and Efficiencies
PV cells are made up of semiconductor material, such as silicon, which is currently the most
commonly used. Basically, when light strikes the cell, a certain portion of it is absorbed
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within the semiconductor material. This means that the energy of the absorbed light is
transferred to the semiconductor. The energy knocks electrons loose, allowing them to flow
freely. PV cells have one or more electric fields that act to force electrons that are freed by
light absorption to flow in a certain direction. This flowing of electrons is a current and by
placing metal contacts on the top and bottom of the PV cell we can draw that current off to be
used externally. For example, the current can power a calculator. This current, together with
the cell's voltage, which is a result of its built-in electric field or fields, defines the power in
watts that the solar cell can produce (Patel, 2006)
There are currently five commercial production technologies for PV cells:
• Single Crystalline Silicon: This is the oldest and more expensive production technique, but
it's also the most efficient sunlight conversion technology available. Cells efficiency averages
between 11% and 16%
• Polycrystalline or Multi-crystalline Silicon: This has a slightly lower conversion efficiency
compared to single crystalline and manufacturing costs are also lower. Cells efficiency
averages between 10% and 13%.But Kyocera’s advanced cell processing technology and
automated production facilities have produced multi-crystalline solar cells with efficiencies
of over 16.5%.
• String Ribbon: This is a refinement of polycrystalline silicon production. There is less work
in its production so costs are even lower. Cells efficiency averages 8% to 10%
• Thin Film “copper-indium-diselenide”: This is a promising alternative to silicon cells.
They are much more resistant to effect of shade and high temperatures, and offer the promise
of much lower cost. Cells efficiency averages 6% to 8%
• Amorphous: Made when silicon material is vaporized and deposited on glass or stainless
steel. The cost is lower than any other method. Cells efficiency averages 4% to 7% Cells
efficiency decreases with increases in temperature. Crystalline cells are more sensitive to heat
than thin films cells. The output of a crystalline cell decreases approximately 0.5% with every
increase of one degree Celsius in cell temperature. For this reason modules should be kept as
cool as possible, and in very hot condition amorphous silicon cells may be preferred because
their output decreases by approximately 0.2% per degree Celsius increase (Antony et al.
2007).
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3.3.5 PV installation
The tilt angle of a PV array can be adjusted optimize various system objectives, such as
maximizing annual, summer or winter energy production. Using adjustable fixed mounts and
adjusting the title angle periodically through the year can further increase energy production
(Jimenez-98).fixed mount lower in cost than tracking mounts.
For best year round power output with the least amount of maintenance, you should set the
solar array facing true south at a tilt angle equal to your latitude with respect to the horizontal
position. If you plan to adjust your solar array tilt angle seasonally, a good rule of thumb is:
- Latitude minus 15° in the summer
- Latitude in the spring/fall
- Latitude plus 15° in the winter
To capture the maximum amount of solar radiation over a year, the solar array should be
tilted at an angle approximately equal to a site’s latitude, and facing within 15º of due south.
To optimize winter performance, the solar array can be tilted 15º more than the latitude angle,
and to optimize summer performance, 15º less than the latitude angle. At any given instant,
the array will output maximum available power when pointed directly at the sun
(KYOCERA, 2004)
To compare the energy output of your array to the optimum value, you will need to know the
site’s latitude, and the actual tilt angle of your array-which may be the slope of your roof if
your array is flush-mounted. If your solar array tilt is within 15º of the latitude angle, you can
expect a reduction of 5% or less in your system’s annual energy production. If your solar
array tilt is greater than 15º off the latitude angle, the reduction in your system’s annual
energy production may fall by as much as 15% from its peak available value. During winter
months at higher latitudes, the reduction will be greater (KYOCERA, 2004).
When installing PV panels the racks are mounted on a roof or pole and then the panels are
mouthed on racks. Care must be taken to ensure the panels will not shaded during the day as
even partial shading of a panel will often reduce its power output to near zero. The PV array
can then be connected to DC loads, directly or via battery and / or regulator. DC appliances
can be slightly more expensive than AC appliances for which also DC/AC inverter need to be
installed.
When the PV modules are installed in parallel they can be segregated into separate sets to
fine-tune the battery charging current. However, this is only feasible for big systems. Because
one PV module is not working properly any more can take out a whole string, PV panels need
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to be kept clean, free overshadowing, and electrical connections need periodic inspection for
loose connections and corrosion.
3.3.6 Photovoltaic Modules
A PV module is composed of interconnected photovoltaic cells encapsulated between a
weather-proof covering (usually glass) and back plate (usually a plastic laminate). It will also
have one or more protective by-pass diodes. The output terminals, either in a junction box or
in a form of output cables, will be on the back. Most have frames. Those without frames are
called laminates. In some, the back plate is also glass, which gives a higher fire rating, but
almost doubles the weight.
The cells in the modules are connected together in a configuration designed to deliver a
useful voltage and current at the output terminals. Cells connected in series increases the
voltage output while cells connected in parallel increases the current. A group of several PV
modules are connected together are called a solar array.
3.3.7 Photovoltaic Manufactures
Photovoltaic’s modules are available in a range of sizes. Those used in grid tied or stand
alone systems range from 80W to 300W. The performance of PV modules and arrays are
generally rated according to their maximum DC power output (watts) under the Standard
Test Conditions (STC). Standard Test Conditions are defined by a module (cell) operating
temperature of 25ºC (77 F), an incident solar irradiant level of 1000 W/m² and under Air
Mass 1.5 spectral distribution. Since these conditions are not always present PV modules and
arrays operate in the field with performance of 85 to 90 percent of the STC rating. Tables 3-2
present the PV modules specification used in this thesis. All the data was taken from the
manufacture’s data sheet. Price of each module where obtained in August 2010 from the
vendors.
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Table 3.1: Solar Module Power at STC Rating and Price
Solar Module Brand
Photo conversion
efficiency(%)Watt at
1000W/m2 US$/unit US$/watt Solar panel vendorKyocera Solar (KD-210GX-LP) 19 210 483.00 2.30 http://www.advancepower.netEvergreen (ES-A-200-fa3 ) 18 200 675.00 3.38 http://www.altersystems.comEvergreen (ES-190-RL) 18 190 560.00 2.95 http://www.altersystems.comMitsubishi ( PV-UE125MF5N ) 16 125 $580.00 4.64 http://www.altersystems.comSILRAY SOLAR PANELS 16 180 387.00 2.15 http://www.advancepower.netGE Solar Panels 17 165 730.95 4.42 http://www.altersystems.comSanyo Solar Panel (HIP-190BA3) 17 190 889.00 4.68 http://www.altersystems.comSharp Solar Panel (NE-170U1) 16 170 545.00 3.20 http://www.altersystems.comSharp Solar Panel (NU-U230F3 ) 17 230 725.00 3.15 http://www.altersystems.comYingli Solar Panel (YL175) 17 175 525.00 3.00 http://www.altersystems.com
Today’s photovoltaic modules are extremely safe and reliable products, with minimal failure
rates and projected service lifetimes of 20 to 30 years. Most major manufacturers offer
warranties of twenty or more years maintaining a high percentage of the initial rated power
output.
3.4 Solar resource
Solar energy is available everywhere on Earth, in varying amounts. Solar radiation that
reaches the earth’s surface in an unbroken line is called direct, while sunlight scattered by
clouds, dust, humidity and pollution is called diffused. The sum of the direct and diffuse
sunlight is called global-horizontal insolation. Concentrating solar technologies, which use
mirrors and lenses to concentrate sunlight, rely on direct radiation, while PV cells and other
solar technologies can function with diffused radiation.
Solar radiation provides a huge amount of energy to the earth. The total amount of energy,
which is irradiated from the sun to the earth's surface, equals approximately 10,000 times the
annual global energy consumption. On average, 1,700 kWh per square meter is insolated
every year (Patel, 2006).
The light of the sun, which reaches the surface of the earth, consists mainly of two
components: direct sunlight and indirect or diffuse sunlight, which is the light that has been
scattered by dust and water particles in the atmosphere. Photovoltaic cells not only use the
direct component of the light, but also produce electricity when the sky is overcast. To the
average total solar energy received over the year, rather than to refer to instantaneous
irradiance.
The daily radiation of Somalia region is very high although there are zonal and seasonal
variations. Solar radiation potential in Degehabur and Kebri Dehar are estimated to be 5.0 to
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7.5 KWh/M2. As majority of the population in the region live in dispersed area solar energy
resources could be the most appropriate electricity resources. See Figure 3.3 below solar map
of Ethiopia including project area of the thesis.
Figure 3.5: solar maps Annual Daily Solar Radiation of Ethiopia (Including project area)
(Source: SWERA).
In order to capture as much solar energy as possible, the photovoltaic cell must be oriented
towards the sun. If the photovoltaic cells have a fixed position, their orientation with respect
to the south (northern hemisphere), and tilt angle, with respect to the horizontal plane, should
be optimized. For regions nearer to the equator, this tilt angle will be smaller, for regions
nearer to the poles it will be larger. A deviation of the tilt angle from the optimum angle, will
lead to less power to be capture by the photovoltaic system.
Degehabur and Kebri Dehar are located at the Latitude 8º 13' N and longitude 43º 34' W and
the Latitude 6º 45' N and longitude 44º 17' W, meaning that the tilt angle for the Degehabur
and Kebri Dehar should be 8º 13' N and 6º 45' N respectively.
3.4.1 Degehabur and Kebri Dehar Solar Resources
Solar resources is an important factor for know how many power can be generated by a
photovoltaic system. Solar radiation data was obtained from the NASA SMSE satellite
measurements. The NASA SMSE database was derived from the meteorology and solar
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Main Report Final Master Thesis
3.5 Synthesize Hourly solar data from monthly average radiation
To synthesize data, you must enter twelve average monthly values of either solar radiation or
clearness index and builds a set of 8,760 solar radiation values, or one for each hour of the
year. To create the synthesized values using the Graham algorithm, this results in a data
sequence that has realistic day-to-day and hour-to-hour variability and autocorrelation
(NREL, 2008).
Since measured hourly solar radiation data is seldom available, it is often necessary to use its
capability to generate synthetic hourly solar data from monthly averages. The synthetic data
display realistic day-to-day and hour-to-hour patterns. If one hour is cloudy, there is a
relatively high likelihood that the next hour will also be cloudy. Similarly, one cloudy day is
likely to be followed by another cloudy day.
The figure 3.2 and figure 3.3 show that daily horizontal solar radiation for Degehabur and
Keberi Dehar towns respectively. Total daily solar radiation is considered as the most
important parameter in the performance prediction of renewable energy systems, particularly
in sizing photovoltaic (PV) power and solar heating systems. However, measuring and
recording equipment for solar radiation are costly. Therefore, numbers of stations in the
developing countries are very limited and insufficient for use to overcome this problem, some
mathematical models relating solar radiation have been proposed, the sunshine duration is
considered to be a good predictor of global solar radiation. Homer simulation software is
better solution for this problem
The global solar radiation determines the energy state of the active surface and the lower
atmosphere layers. The values of global solar radiation are determined in the first place by the
sun height and by the cloudiness. Substantial influence on its values makes the albedo, which
characterizes the reflection properties of the active surface. According to the figure 3.2 and
3.3 indicated that the global solar radiation increases from the sunrise till noon and decreases
till sundown. With the increase of the atmospheric haze the global solar radiation decreases
especially for large sun heights. Because of cloudiness influence during the warm part of the
year the global solar radiation after noon is lower compared to before noon at one and the
same sun height. Daily amounts of solar radiation are minimal in July and maximal in
February. The limits, in which the daily amounts of the global solar radiation are changing,
are small in winter. This is due to the small sun height and the considerable cloudiness. In
summer, when sun height is large, the variability of the solar radiation and cloudiness are
Main Report Final Master Thesis
larger, the annual amounts of global solar radiation are varying in larger limits. The data
presented in Appendix-B, Table B.5 and table B.6, and summarized in figure 3.8 and 3.9
Figure 3.7: Global daily solar radiations on horizontal surfaces for Kebri Dehar town
Figure 3.8: Global daily solar radiations on horizontal surfaces for Degehabur town
The flow charts of which synthetic hourly horizontal radiation and calculates the global radiation incident on the PV array is as follows:
Main Report Final Master Thesis
The major procedures in the program for generating synthetic hourly radiation are shown in
Figure 3.9
Figure 3.9: Diagram of the solar radiation calculation on panel surface
The procedures in Figure 3.10 can be briefly described as follows:
1. Calculate the radiation at the horizontal surface based on the day of the year and the site
latitude and then establish a clearness index.
2. The clearness index is then used to calculate the direct, diffuse and random components of
the radiation on a horizontal surface.
3. The total radiation is then calculated from the direct, diffuse and random values.
4. Finally the radiation on the surface of the panel is determined.
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It requires monthly average meteorological data at a specific site location as its input for the
simulation of the solar radiation process at that site. The necessary data is the monthly
average values of solar radiation on the horizontal surface and the ambient temperature
Declination Angle
The declination is the angular position of the sun at solar noon, with respect to the plane of
the equator. Its value in degrees is given by Cooper’s equation (NREL, 2008):
°
The time of year affects the solar declination, which is the latitude at which the sun's rays are
perpendicular to the earth's surface at solar noon (NREL, 2008).
Where: is the day of the year
The equation of time accounts for the effects of obliquity (the tilt of the earth's axis of
rotation relative to the plane of the ecliptic) and the eccentricity of the earth's orbit. HOMER
calculates the equation of time as follows (NREL, 2008):
Where B is given by:
Where n is the day of the year, starting with 1 for January 1st and 365 for December 31st
Now, for a surface with any orientation, we can define the angle of incidence, meaning the
angle between the sun's beam radiation and the normal to the surface, using the following
equation (NREL, HOMER user manual, 2007):
An incidence angle of particular importance, which we will need shortly, is the zenith angle,
meaning the angle between a vertical line and the line to the sun. The zenith angle is zero
when the sun is directly overhead and 90° when the sun is at the horizon. Because a
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horizontal surface has a slope of zero, we can find a equation for the zenith angle by setting
= 0° in the above equation, which yields (NREL, 2008):
Extraterrestrial Normal Radiation and clearness index
It states that the amount of solar radiation arriving at the top of the atmosphere over a
particular point on the earth's surface. It assumes that the output of the sun is constant in
time. But the amount of sunlight striking the top of the earth's atmosphere varies over the
year because the distance between the sun and the earth varies over the year due to the
eccentricity of earth's orbit. To calculate the extraterrestrial normal radiation, defined as the
amount of solar radiation striking a surface normal (perpendicular) to the sun’s rays at the top
of the earth's atmosphere, it uses the following equation (NREL, HOMER user manual,
2007):
Gon Gsc
Since HOMER simulates on a time step by time step basis, we integrate the above equation
over one time step to find the average extraterrestrial horizontal radiation over the time step
(NREL, 2008):
The above equation gives the average amount of solar radiation striking a horizontal surface
at the top of the atmosphere in any time step. The solar resource data give the average amount
of solar radiation striking a horizontal surface at the bottom of the atmosphere (the surface of
the earth) in every time step. The ratio of the surface radiation to the extraterrestrial radiation
is called the clearness index. The following equation defines the clearness index (NREL,
HOMER user manual, 2007):
Beam and diffuse radiation
The correct prediction of the power generated by PV arrays requires the determination of the
intensity of the global solar radiation on the surface of the arrays at a specific site location.
The total global radiation is normally composed of two components namely the direct and the
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diffuse radiation. The direct component is the radiation received from the sun without having
been scattered by the atmosphere, while the diffused component is the radiation received
from the sun after its direction has been changed due to scattering. The contribution of the
direct and diffuse components to the total radiation mainly depends on the cloud cover
(Beckman, 1980). Now let us look more closely at the solar radiation on the earth's surface.
Some of that radiation is beam radiation, defined as solar radiation that travels from the sun
to the earth's surface without any scattering by the atmosphere. Beam radiation (sometimes
called direct radiation) casts a shadow. The rest of the radiation is diffuse radiation, defined
as solar radiation whose direction has been changed by the earth's atmosphere. Diffuse
radiation comes from all parts of the sky and does not cast a shadow. The sum of beam and
diffuse radiation is called global solar radiation, a relation expressed by the following
equation (NREL, HOMER user manual, 2007):
The distinction between beam and diffuse radiation is important when calculating the amount
of radiation incident on an inclined surface. The orientation of the surface has a stronger
effect on the beam radiation, which comes from only one part of the sky, than it does on the
diffuse radiation, which comes from all parts of the sky (NREL, 2008).
However, in most often cases you get only monthly the global horizontal radiation, not its
beam and diffuse components. The only necessary data to fill missing hourly solar is global
horizontal radiation for that reason, HOMER expects you to enter global horizontal radiation
in HOMER's Solar Resource Inputs window. That means that in every time step, HOMER
must resolve the global horizontal radiation into its beam and diffuse components to find the
radiation incident on the PV array. The well knows uses correlation of Erbs et al. (1982),
which gives the diffuse fraction as a function of the clearness index as follows (NREL,
HOMER user manual, 2007) :
3.1
For each time step, it uses the average global horizontal radiation to calculate the clearness
index, then the diffuse radiation. It then calculates the beam radiation by subtracting the
diffuse radiation from the global horizontal radiation.
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3.6 Calculates the global radiation incident on the PV array
Now the final step to calculate the global radiation striking the tilted surface of the PV array.
This parameter is very important since the predication of solar array output which supplies
electric demand of the two towns. The HDKR model is the well know model to calculates the
global radiation incident on the PV array, which assumes that there are three components to
the diffuse solar radiation: an isotropic component which comes all parts of the sky equally, a
circumsolar component which emanates from the direction of the sun, and a horizon
brightening component which emanates from the horizon. Before applying that model we
must first define three more factors (NREL, HOMER user manual, 2007).
The following equation defines Rb, the ratio of beam radiation on the tilted surface to beam
radiation on the horizontal surface:
The anisotropy index, with symbol Ai, is a measure of the atmospheric transmittance of beam
radiation. This factor is used to estimate the amount of circumsolar diffuse radiation, also
called forward scattered radiation. The anisotropy index is given by the following equation
(NREL, 2008):
The final factor we need to define is a factor used to account for 'horizon brightening', or the
fact that more diffuse radiation comes from the horizon than from the rest of the sky. This
term is related to the cloudiness and is given by the following equation (NREL, 2008):
The HDKR model calculates the global radiation incident on the PV array according to the
following equation (NREL, 2008):
3.2
It uses this quantity to calculate the cell temperature and the power output of the PV array
In two axis tracking ,Referring figure 3.4 below, Degebabur town monthly daily average
solar radiation incidence on the PV array improved from range of 30 to 39 percent instead of
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the panel installed the latitude angle (fixed mounted). The tracked array rises up to quickly to
full power and stays there on a clear sunny day. The fixed array only maintains the maximum
power for a few hours in the middle of the day. The tracked array will be greater in wattage
than the fixed mount arrays but it cost higher. The same is true for Keberidehar town and
slight difference the values improved same as Degehabur. The data presented in Appendix-B
through table B.7 to table B.10 and summarized in figure 3.12 for the two towns.
Figure 3.10: Calculates the global radiation incident on the PV array with tracking and without tracking system
3.6.1 Calculates the PV Cell Temperature and PV array power output
The PV cell temperature is the temperature of the surface of the PV array. During the night it
is the same as the ambient temperature, but in full sun the cell temperature can exceed the
ambient temperature by 30°C or more. The PV Array outputs depend of the temperatures of
each time step. It is negative effect is PV array output, meaning that the PV array out is
decreasing when the panel temperature increasing. It starts by defining an energy balance for
the PV array, using the following equation from Duffie and Beckman (1991) (NREL,
HOMER user manual, 2007):
3.3
The above equation states that a balance exists between, on one hand, the solar energy
absorbed by the PV array, and on the other hand, the electrical output plus the heat transfer to
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the surroundings. We can solve that equation for cell temperature to yield (NREL, HOMER
user manual, 2007):
3.4
It is difficult to measure the value of ( ) directly, so instead manufacturers report the
nominal operating cell temperature (NOCT), which is defined as the cell temperature that
results at an incident radiation of 0.8 kW/m2, an ambient temperature of 20°C, average wind
speed of 1 m/s ,and no load operation (meaning = 0) with the cell or module in an
electrically open circuit state, the wind oriented parallel to the plane of the array, and all sides
of the array fully exposed to the wind (NREL, HOMER user manual, 2007).
The temperature coefficient of power indicates how strongly the PV array power output
depends on the cell temperature, meaning the surface temperature of the PV array. It is a
negative number because power output decreases with increasing cell temperature. Nominal
operating cell temperature (NOCT) and the temperature coefficient of power are depending
on PV Module Type. Table 3.2 below show that NOCT and p Module Characteristics for
Standard Technologies Table 3.2: PV Module Characteristics for Standard Technologies
PV Module Type r (%) NOCT(°C)
Average Value of p
(%/°C) Polycrystalline silicon 17.00 47.00 -0.48
Monocrystalline silicon 13.50 45.00 -0.46
Monocrystalline/amorphous silicon hybrid 16.40 48.00 -0.30
Thin film amorphous silicon 5.50 46.00 -0.20 Thin film CIS 8.20 47.00 -0.60
Source: Homer user manual and Kyocera PV manufacturer
Note: In this thesis work the author has used the Kyocera Polycrystalline-silicon module cell
due to its higher conversion efficiency as well as lower capital cost than the others. The detail
Kyocera PV module technical specification is presented in Appendix-D
We can substitute these values into the above equation and solve it for to yield the
following equation (NREL, HOMER user manual, 2007):
Main Report Final Master Thesis
If we assume that is constant, we can substitute this equation into the cell temperature
equation to yield (NREL, HOMER user manual, 2007):
3.5
It assumes a value of 0.9 for in the above equation, as Duffie and Beckman (1991)
suggest. Since the term is small compared to unity, this assumption does not introduce
significant error (NREL, HOMER user manual, 2007).
It assumes that the PV array always operates at its maximum power point, as it would if it
were controlled by a maximum power point tracker. That means HOMER assumes the cell
efficiency is always equal to the maximum power point efficiency: (NREL, HOMER user
manual, 2007)
But depends on the cell temperature . It assumes that the efficiency varies linearly with temperature according to the following equation (NREL, HOMER user manual, 2007):
3.6
The temperature coefficient of power is normally negative, meaning that the efficiency of
the PV array decreases with increasing cell temperature. The maximum temperature data of
the two towns are presented in Appendix-A, table A.1.
We can substitute this efficiency equation into the preceding cell temperature equation and
solve for cell temperature to yield (NREL, HOMER user manual, 2007):
3.7
The final step is to Calculates the PV Array Power Output by using equation 3.8 below:
3.8
is the cell temperature under standard test conditions [25°C]
.The maximum installed power capacity of PV Array 600 KW and 700 KW for Kebridehar
and Degehabur towns respectively. PV Derating Factor is 80% and the ground reflectance
Main Report Final Master Thesis
20% used for the simulation input. The ground reflectance data obtained from NASA. The
ground reflectance (also called albedo) is the fraction of solar radiation incident on the
ground that is reflected. A typical value for grass-covered areas is 20%. Snow-covered areas
may have a reflectance as high as 70% (NREL, 2008). This value is used in calculating the
radiation incident on the tilted PV panels, but it has only a modest effect. The solar radiation
incident on the PV array in the current time step of the two towns are indicated in section 3.6
Appendix-B, table B.8 and table B.11.By using Eq 3.8, above, we can computed the Daily
PV Array power outputs of the two towns and presented in Appendix-C, table C.3 and
C.4.This PV Array output power is the contribution hybrid energy generation to meet the
required demand of the selected towns.
4. Batteries, PV controller, Inverters and Energy Consumption
4.1 Introduction
A battery is a device that stores Direct Current (DC) electrical energy in electrochemical form
for later use. The amount of energy that will be storage or deliver from the battery is managed
by the controller or the inverter. The inverter converts the DC electrical energy to Alternative
Current (AC) electrical energy, which is the energy that most residential homes use
4.1.1 Batteries
Electrical energy is stored in a battery in electrochemical form and is the most widely used
device for energy store in a variety of application. The conversion efficiency of batteries is
not perfect. Energy is lost as heat and in the chemical reaction, during charging or recharging.
Because not all battery’s can be recharged they are divided in two groups. The first group is
the primary batteries which only converts chemical energy to electrical energy and cannot be
recharged. The second group is rechargeable batteries. Rechargeable batteries are used for
hybrid wind / PV system.
The internal component of a typical electrochemical cell has positive and negative electrodes
plates with insulating separators and a chemical electrolyte in between. The cells store
electrochemical energy at a low electrical potential, typically a few volts. The cell capacity,
denoted by C, is measured in ampere-hours (Ah), meaning it can deliver C A for one hour or
C/nA for n hours (A. Luque, 2003).
Many types of batteries are available today like for example: Lead-acid, Nickel cadmium,
Nickel-metal, Lithium-ion, Lithium-polymer and Zinc air. Lead-acid rechargeable batteries
continue to be the most used in energy storage applications because of its maturity and high
performance over cost ratio, even though it has the least energy density by weight and
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volume. These lead acid batteries come in many versions. The shallow- cycle version is the
one use in automobiles, in which a short burst of energy is drawn from the battery to start the
engine. The deep-cycle version, on the other hand, is suitable for repeated full charge and
discharge cycles. Most energy store applications require deep-cycle batteries (Patel, 2006).
Table 4.1 show the lead acid batteries used in this thesis. These specifications are taken from
manufactures data sheet and the prices were obtained in January 2010. Table 4.1: manufactures data sheet and the prices
Capacity Capacity Capacity
No
.
Flooded Lead-Acid battery
Price Volts C@100H(AH)
C@72H (HA)
C@20H(AH)
Supplier
1 MK 8L16 266 6 420 370 Alternative Energy Store
2 Surrette 12-Cs-11Ps
1178 12 503 475 357 Alternative Energy Store
3 Surrette 2Ks33Ps
791 2 2480 2349 1765 Alternative Energy Store
4 Surrette 4-CS-17PS
856 4 770 726 546 Alternative Energy Store
5 Surrette 4-Ks-21Ps
972 4 1557 1468 1104 Alternative Energy Store
6 Surrette 4-Ks-25Ps
1497 4 1900 1800 1350 Alternative Energy Store
7 Surrette S-460 340 6 460 441 350 Alternative Energy Store
8 Surrette S-530 375 6 530 504 400 Alternative Energy Store
9 Trojan L16H 6 420 Alternative Energy Store
10 Trojan T-105 6 225 Alternative Energy Store
11 US Battery US185
12 195 Alternative Energy Store
12 US Battery Us2200
6 225 Alternative Energy Store
4.1.2 Battery Electricity
Battery is a electro-chemical devices that is store energy in chemical form. They are used to
excess energy in the later use. Most batteries used in the hybrid are of the depth of the lead –
acid types. They are several other appropriate types (nickel-cadmium, nickel-Iron, Iron-air
and sodium-sulfur) but these are generally either too expensive or too unreliable for practical
application as most of them are still experiment stage. The lead-acid battery widely used and,
although complex, is well known. Its major limitation is that it must be operated within strict
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boundaries as it is susceptible to damage under a certain condition- such as overcharging,
undercharging and remaining for long periods a low state of charge (Jimens-
98),(Slabbert,Seeling and Hochmuse-97). Battery cost can form a minor part of the system
initial costs, but adverse condition, battery maintenance and replacement can become a
significance portion of system lifecycle cost and can prove to be expensive a long run. If the
operating condition is favorable, however, these batteries can last up till 15 years in an
autonomous. Indivual batteries used in renewable energy and hybrid systems are in capacities
ranging from 50 ampere-hours at 12 volts to thousand of ampere-hours at two volts (i.e. from
0.5 kWh to several kWh)
4.1.3 General working
Batteries consist of one or more 2V-cells wired in series. Each cell consists of plates that
immersed in an electrolyte. When a discharging a chemical reaction between the plates and
electrolyte produce electricity. This reaction reversed when the battery charged.
The thickness of the battery’s plates determines the maximum depth of discharge beyond
which the battery suffers damage. Shallow cycle batteries, such as car batteries, have thin
plates and are design to produce a large current for short period of time. These should not be
a deeper discharge than 10-20% depth of discharge after which the battery ruined easily
(Jimenez-98).shallow cycle batteries are usually not suited for hybrid and renewable system
but often used anyway in small home systems in developing countries due to a lack of any
alternatives. Deep cycle batteries have thick, often tubular plates and can be often be
discharged up to 70%-80%. However, this types of battery cannot be quickly charged and
discharge (Jimenez-98).
4.1.4 Storage capacity
The storage capacity of the battery is generally is given in ampere-Hours or after the with
multiplication the battery’s nominal voltage in kWh. The value for the storage capacity
depends on its operation, age and treatment. The storage capacity is increased when the
battery charging and discharging rates are slow. Most battery manufacturer give the storage
capacity for a given discharge time, usually 20 or 100 hours. Some of the energy used to
charge the battery is lost which accounted for by the round trip efficiency (typically 50%-
80%).
The capacity of a battery is defined as the amount of energy that can be withdrawn from it
starting from a fully-charged state. But the capacity of a battery depends on the rate at which
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energy is withdrawn from it. The higher the discharge current, the lower the capacity. One
can create a capacity curve by measuring a battery's capacity at several different constant
discharge currents.
For in this thesis Surrette4KS25P of battery type is selected since the capacity and life time of
the battery is suited for this project.
4.1.5 Battery modeling
Validated battery modeling is essential for accurate predictions of the ability of the renewable
system to meet the load demand, especially in the autonomous case. A common technique is
to estimate the state of charging (SOC) of the battery in Ampere-hours or the percentage to
express its condition. A battery said to have a certain capacity in Ah (100% SOC) and the
amount of charge taken from it under operation (% depth of discharge) will leave it at a new
% SOC
Unfortunately a quantity such as SOC is not directly measurable. As an alternative approach
the battery states of voltage can be used to give an indication of the SOC in order to judge the
condition of battery. For this thesis uses the Kinetic Battery Model (Maxwell and McGowan,
1993) to determine the amount of energy that can be absorbed by or withdrawn from the
battery bank each time step. The kinetic battery model, so named because it is based on the
concepts of electrochemical kinetics, models a battery as a two tank system. The first tank
contains "available energy", or energy that is readily available for conversion to DC
electricity. The second tank contains "bound energy", or energy that is chemically bound and
therefore not immediately available for withdrawal.
The battery bank is a collection of one or more individual batteries. The models a single
battery as a device capable of storing a certain amount of dc electricity at fixed round-trip
energy efficiency, with limits as to how quickly it can be charged or discharged, how deeply
it can be discharged without causing damage, and how much energy can cycle through it
before it needs replacement. It assumes that the properties of the batteries remain constant
throughout its lifetime and are not affected by external factors such as temperature.
The key physical properties of the battery are its nominal voltage, capacity curve, lifetime
curve, minimum state of charge, and round-trip efficiency. The capacity curve shows the
discharge capacity of the battery in ampere-hours versus the discharge current in amperes.
Manufacturers determine each point on this curve by measuring the ampere-hours that can be
discharged at a constant current out of a fully charged battery. Capacity typically decreases
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with increasing discharge current. The lifetime curve shows the number of discharge–charge
cycles the battery can withstand versus the cycle depth. The number of cycles to failure
typically decreases with increasing cycle depth. The minimum state of charge is the state of
charge below which the battery must not be discharged to avoid permanent damage. In the
system simulation, it does not allow the battery to be discharged any deeper than this limit.
The round-trip efficiency indicates the percentage of the energy going into the battery that
can be drawn back out (PAUL GILMAN and PETER LILIENTHAL)
Figure 4.1: Kinetic battery model concepts
To calculate the battery’s maximum allowable rate of charge or discharge, it uses the kinetic
battery model, which treats the battery as a two tank system, as illustrated in Figure 4.1.
According to the kinetic battery model, part of the battery’s energy storage capacity is
immediately available for charging or discharging, but the rest is chemically bound. The rate
of conversion between available energy and bound energy depends on the difference in
‘‘height’’ between the two tanks. Three parameters describe the battery. The maximum
capacity of the battery is the combined size of the available and bound tanks. The capacity
ratio is the ratio of the size of the available tank to the combined size of the two tanks. The
rate constant is analogous to the size of the pipe between the tanks (PAUL GILMAN and
PETER LILIENTHAL)
The kinetic battery model explains the shape of the typical battery capacity curve, such as
shown in Figure 4.2. At high discharge rates, the available tank empties quickly, and very
little of the bound energy can be converted to available energy before the available tank is
empty, at which time the battery can no longer withstand the high discharge rate and appears
fully discharged. At slower discharge rates, more bound energy can be converted to available
energy before the available tank empties, so the apparent capacity increases. It performs a
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curve fit on the battery’s discharge curve to calculate the three parameters of the kinetic
battery model. The line in Figure 4.2 corresponds to this curve fit.
Modeling the battery as a two-tank system rather than a single-tank system has two effects.
First, it means the battery cannot be fully charged or discharged all at once; a complete
charge requires an infinite amount of time at a charge current that asymptotically approaches
zero (PAUL GILMAN and PETER LILIENTHAL). Second, it means that the battery’s
ability to charge and discharge depends not only on its current state of charge, but also on its
recent charge and discharge history. A battery rapidly charged to 80% state of charge will be
capable of a higher discharge rate than the same battery rapidly discharged to 80%, since it
will have a higher level in its available tank. It tracks the levels in the two tanks each hour,
and models both these effects (PAUL GILMAN and PETER LILIENTHAL) .
Figure 4.2: Capacity curve for deep-cycle battery model Surrette4KS25P
Figure 4.2 shows a lifetime curve typical of a deep-cycle lead–acid battery. The number of
cycles to failure (shown in the graph as the lighter-colored points) drops sharply with
increasing depth of discharge. For each point on this curve, one can calculate the lifetime
throughput (the amount of energy that cycled through the battery before failure) by finding
the product of the number of cycles, the depth of discharge, the nominal voltage of the
battery, and the aforementioned maximum capacity of the battery. The lifetime throughput
curve, shown in Figure 4.3 as black dots, typically shows a much weaker dependence on the
cycle depth. It makes the simplifying assumption that the lifetime throughput is independent
of the depth of discharge. The value that it suggests for this lifetime throughput is the average
of the points from the lifetime curve above the minimum state of charge, but the user can
modify this value to be more or less conservative (PAUL GILMAN and PETER
LILIENTHAL).
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The assumption that lifetime throughput is independent of cycle depth means that it can
estimate the life of the battery bank simply by monitoring the amount of energy cycling
through it, without having to consider the depth of the various charge–discharge cycles. It
calculates the life of the battery bank in years as (NREL, Homer user manual, 2008):
Figure 4.3: Lifetime curve for deep-cycle battery model Surrette4KS25P
The higher the DOD, the lower will be the cycles and the lifetime of the batteries (can be
seen from Figure 4.3).
4.1.6 Battery regulators
Battery regulator used to control the operation of the batteries used in an off-grid/hybrid
system and thus protect them from unfavorable condition. The main functions are top-of-
charge regulation to prevent overcharging and load disconnection to prevent excessive
discharging. Additionally they may indicate the status of the system and may also give a
boost charge from time to time to avoid the stratification of the battery.
Regulators measure voltage levels an approximation to state of charge but this may vary with
charge/discharge currents, temperature compensation and ampere hour counting determined
state of charge more accurately. Set points are selected to maximizing battery life time.
4.1.7 Battery Sizing
Battery sizing consists in calculating the number of batteries needed for a hybrid renewable
energy system. This mainly depends on the days of autonomy desired. Days of autonomy are
the number of days a battery system will supply a given load without being recharged by a
PV array, wind turbine or another source. If the load being supplied is not critical then 2 to 3
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autonomy day are commonly used. For critical loads 5 days of autonomy are recommended.
A critical load is a load that must be used all the time.
Another important factor is maximum depth of discharge of the battery. The depth of
discharge refers to how much capacity will be use from the battery. Most systems are
designed for regular discharges of up to 40 to 80 percent. Battery life is directly related to
how deep the battery is cycled. For example, if a battery is discharged to 50 percent every
day, it will last about twice long as if is cycled to 80 percent, (PVDI 2007).
Atmospheric temperature also affects the performance of batteries. Manufacturers generally
rate their batteries at 25ºC. The battery’s capacity will decrease at lower temperatures and
increase at higher temperature. The battery’s life increases at lower temperature and
decreases at higher. It is recommended to keep the battery’s storage system at 25 ºC. At 25 ºC
the derating factor is one.
The following procedure shows how to calculate the number of batteries needed for a hybrid
energy system, (Sandia 2004). Equation 4-3 shows how to calculate the required battery bank
capacity for a hybrid renewable energy system. The depth of discharge of the battery (60% is
considered here for this study), is the days of autonomous (two day of autonomous is
considered here) and is the battery efficiency (80% in this case) yielding capacities of
5MWh/day and 4.6MWh/day for Keberi Dehar and Degeabur towns, respectively. The
nominal battery capacity is 1.25 times the calculated value. The charging/discharging of the
battery in the linear region (40% - 90% peak capacity) gives highest efficiency and controls
must be designed in this manner. The required battery bank capacity for Degehabur town is
But the nominal battery capacity is 1.25*94,697Ah=118371 Ah. Likewise, the nominal capacity of Kebri Dehar town is 1.25*87,121Ah=108,902Ah.
Where is the Amp-hour consume by the load in a day (Ah/Day), is the number
of autonomy days, is the maximum depth of discharge, is the derate factor and is
the required battery bank capacity in (Ah).
Equation 4-2 presents how to calculate the number of batteries to be connected in parallel to
reach the Amp hours required by the system
Main Report Final Master Thesis
The number of batteries that needs to be in parallel for Degehabur and Kebri Dehar towns is
62 and 57 respectively.
Equation 4-3 presents how to calculate the number of batteries to be connected in series to
reach the voltage required by the system. The system voltage of the selected towns is 400
volts then the number of batter to be connected in series is
The battery bank autonomy is the ratio of the battery bank size to the electric load. It
calculates the battery bank autonomy using the following equation:
the battery bank of antonmy of the two towns are the same. By using equation 4.7 we get 48
Hours.The total numbers of batteries needed is obtained multiplying the total number of
batteries in series and the total number of batteries in parallel as shown in equation 4-4.
The total number of batter need for Degehabur and Kebri Dehar towns is 2300 and 2050
repectively.the battery type of this project is Surrette 4KS25P (each battery, 4V, 1900Ah
capacity)
4.1.7 Batter life time
Battery life time is measured both interns of energy taken out from the battery and float life.
A battery dead when all available energy has been taken out or when the average battery has
been reduced to 80% of its original value.
The main factors affecting battery life time are grid corrosion, buckling of plates, sulfation,
and stratification of the electrolytes. These factors are causing loss of active materials and
internal short circuit. If less active materials is available in the ration of reaction components
is becoming non-optimal resulting in a drop of capacity and the charging efficiency reduced.
The Internal short circuits lead to harmful deep of discharge of the concerned cell and hence
ruin the whole battery.
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For many batteries, especially the lead acid types, as long as the battery state of charge is kept
within the manufacturer’s recommended limit, the lifetime cumulative energy flows vary
widely.
Typical float lives for a good quality lead acid batteries ranges between 5 and 15 years at
20 . High the ambient temperatures severely shorten a battery’s float life. A rule of thumb is
that every 10 increase in average ambient temperature will halve the battery float life.
4.1.8 Battery Design
When selecting a battery types, usually lead acid types of batteries are chosen. In general lead
acid batteries are more cost effective than NiCad batteries, but the latter may be the better
choice if the greater battery raggedness is an important consideration (Jimenez-98).
The selection battery voltage depends on inverter and generation controller equipment
generally available. They comes specific voltages from 2, 4, 6,12,24,48 up to 120 and
240VDC and thus batteries must be selected and combined in series to meet this voltage
requirement. The number of battery strings that can be connected in parallel is limited to
about five without rigorous monitoring and high maintenance cost. This means that once the
general battery bank capacity has been selected the size of the individual battery types must
be chosen accordingly.
When designing the system depth of discharge (DOD) a trade-off must be made between a
low DOD where the battery will be less affected by sulphation, but may face frequent load
interruption and will be cycle more often; and a high DOD where although the supply may be
more reliable and the cycling reduce, the battery lifetime may be shortened due to increased
sulphation.
4.1.9 Battery in hybrid system
Battery operation in a hybrid system as opposed to a single-source application may result in
certain advantages with respect to battery lifetime optimization. This can be attributed to the
fact that there is often more sophisticated control installed in a hybrid system due to the
interaction of many components. This requires better regulation of components and will
results in better treatment the battery. Moreover, there are more energy sources available
resulting in the battery not being utilized to as high a degree as in single-source systems.
Reduced cycling lead to increased lifetime and more time (and source) available for
recharging and boost charging. Batteries are costly and can often be sized smaller in hybrid
system than in a single-source system.
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4.2 PV Controllers
The photovoltaic controller works as a voltage regulator. The primary function of a
controller is to prevent the battery from being overcharged by a photovoltaic array system. A
charge controller constantly monitors the battery’s voltage. When the batteries are fully
charged, the controller will stop or decrease the amount of current flowing from the
photovoltaic array into the battery. The controllers average efficiencies range from 95% to
98%. For this thesis the efficiency that will be use for the analysis will be 95%, (A. Luque,
2003).
Charge controllers for PV system come in many sizes, typically from just a few amps to as
much as 80 amps. If high current are required, two or more controllers can be used.
When using more than one controller, it is necessary to divide the array into sub-arrays. Each
sub-array will be wired into the same battery bank. There are five different types of PV
controllers: shunt controller, single-stage series controllers, diversion controller, pulse width
modulation (PWM) controller and the maximum power point tracking controllers (MPPT).
The one we will be using in this thesis are the MPPT controllers.
4.2.1 MPPT Charge Controllers
The Maximum Power Point Tracking (MPPT) charge controllers are the best of today's PV
systems. As the names implies, this feature allows the controller to track the maximum power
point of the array throughout the day in order to deliver the maximum available solar energy
to the batteries or the system. The result is additional 15-30% more power out of an array
versus a PWM controller. Before MPPT was available as an option in controllers, the array
voltage would be pulled down to just slightly above the battery voltage while charging
battery. For example, in a 12V battery charging system, an array’s peak power point voltage
is around 17-18V. Without MPPT, the array would be forced to operate around the voltage of
the battery. These results in a loss of the power coming from the array. Table 4-2 present the
MPPT PV controllers be used in this study. Table 4.2: MPPT Charge Controllers Manufactures
MPPT Charge Controllers
Price
MaxOutput Nom. Battery
Max PV Open
Manufacture Model current
(A) Voltage (V)
Circuit Voltage Allowed (VOC)
Blue Sky Solar Solar Boost
3048DiL 470 30 12,24 140V
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Outback Solar Flexmax 80 667 80 12,24,36,48,60 150V Outback Solar Flexmax 60 597 60 12,24,36,48,60 150V
4.2.2 General working princples
Maximum power trackers are high- frequency DC-DC converters used to force the output of
PV arrays to their maximum instantaneous power. They can improve the efficiency. They can
couple to the battery regulators, directly to DC water pumps or to AC water pumps via an
inverter. Best result are achieved with direct DC pumps coupling where the potentially the
biggest operating mismatch occur. Smaller improvements are realized with battery coupling
as the natural battery/array operating point is usually close to the array MPP (Jimenez-98),
(Slabbert, Seeling-Hochmuth-97).
4.3 Inverters
An inverter converts the direct current (DC) electricity from sources such as batteries, solar
modules, or wind turbine to alternative current (AC) electricity. The electricity can then be
used to operate AC equipment like the ones that are plugged in to most house hold electrical
outlets. The normal output AC waveform of inverters is a sine wave with a frequency of
50Hz for Ethiopia grid system.
When AC appliances are used, an inverter is required between them and the battery/DC
supply system. The inverter is normally only single phase for small power rating. Three phase
inverters are more costly than single phase inverters.
The efficiency of converting the direct current to alternative current of most inverters today is
90 percent or more. Many inverters claim to have higher efficiencies but for this thesis the
efficiency that will be used is 95%. Table 4-3 presents inverters used in this thesis. All the
inverters have output voltage of 220V and produce a sine wave AC output signal of 50Hz.
All the inverters are grid-tied with battery backup. Meaning can do the work as standalone
inverters or grid tied inverters.
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Table 4.3: Inverters Manufactures
Inverter Manufacture Model
Power (W)
DC Input Voltage (VDC)
ACoutput
Voltage (VAC)
Nominal Frequency
(Hz) Price ($)
Xantrex XW6048 6,000 50 120/240 60 3,495 Xantrex XW4548 4,500 50 120/240 60 2,612 Xantrex XW4024 4,000 25 120/240 60 2,330
4.3.1 General working
The harmonic distortion of inverters is an important issue especially when the powering
components like refrigerators and computer and is an indication as to what extent the inverter
output wave form is non-sinusoidal. Inverter output wave form can be square wave, modified
sine wave. Square wave and quasi-wave inverters will introduce distortion as compared with
a 50Hz sine wave, but less expensive than sine wave inverters (Jimenez-98). They can
suitable power resistive load such as resistance heaters or incandescent lights. Modified sine
wave inverters produce a staircase square wave that more approximately a sine wave. They
can supply most electronic devices and motors. However, some sensitivity electronic may
require sine wave inverters. These inverters can produce utility grid power but cost than the
other types of inverters (Jimenez-98).
4.3.2 Inverter Sizing
Inverter sizing consists in calculating the number of inverters needed for the PV and wind
turbine system. In small hybrid systems one inverter will be enough to supply the power but
for a larger hybrid system more inverters may be needed. When you select an inverter you
must have a DC voltage equal to your inverter DC voltage and have an AC voltage and
frequency equal to your home and utility values.
Equation 4-8 shows how to calculate the number of inverters needed for a standalone hybrid
system
Number of Inverters required 4-8
The installed capacity of the inverter is 300KW to accommodate the peak load demand for
the selected towns. The total power output from battery through inverter to supply AC energy
demand and at the same time excess AC power production from wind turbines through
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inverters change to DC power source which charge the battery for the future use. Inverter
output power daily profile for Kebridehar and Degehabur towns are presented in Appndex-C,
table C.5 and C.6
4.4 Energy consumption for Kebridehar and Degehabur towns
4.4.1 Introduction
Energy consumption is the electrical power your loads consume in a period of time. It is
measured in kWh. Loads are usually the largest single influence on the size and cost of a PV
and wind turbine system. In order to reduce the cost of the PV and wind turbine system it is
necessary to use more efficient, lower demand appliance and to eliminate, partially or
completely, the use of other loads.
It is assumption was made for load profile of the two towns and the load profiles are the same
throughout the years since the scarcity of the data which was not taken during data collected
time. The primary electrical load data for Kebri Dehar and Degehabur towns are shown in
Fig.4.4 and Fig 4.5. The annual peak load of 350kW was observed on each month of the
years around 18:00 h. Fig. 2 describes the monthly average variation of load of the two towns
are the same. The higher demand exists between 18:00 and 20:00 PM and while relatively
smaller load requirements are found between 00:00h and 6:00h .The daily energy
consumption is relatively lower in most of the time during 24 h except around 18:00 h to
20:00 h. The minimum load of 145 KW and 140 KW for Degehabur and Kebri Dehar
respectively. The minimum load which occurs in the morning and at after mid night, whiles
the majority of the load occurs in the evening. This evening load, with a peak load of 343
KW for Degehabur and 290 KW for Kebridehar, would likely include Residential, street
light, commercial and mini industrial load .The total daily load averages 5 Mega watt-hours
per day and 4.6 Mega Watt-hours per day for Degehabur and Kebri Dehar towns respectively.
But the load profiles the towns are presented in Appendix B and summarized in Figure 4.4
and figure 4.5 below.
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Figure 4.4: Hourly load profiles for Kebri Dehar town
Figure 4.5: Hourly load profiles for Degehabur town
Deferrable load is electrical load that must be met within some time period, but the exact
timing is not important. Loads are normally classified as deferrable because they have some
storage associated with them. Water pumping is a common type for deferrable load - there is
some flexibility as to when the pump actually operates, provided the water tank does not run
dry. The peak deferrable load for Degehabur town is 150 kW, which is the rated power of the
pump. It would take the pump 6 hours at full power to fill the tank, so the storage capacity is
6 hours times 50 kW, which is 300 kWh. It would take the pump 6 hours at full power to
meet the daily requirement of water, so the average deferrable load is 6 hours per day times
50 kW, which is 300 kWh/day. For the case Kebri dehar town, it follows the same procedure
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but the only difference is that the power needed to fill tank with water for the daily
requirement so, it is around 100 Kwh/per day is required to fill this tank .The annual energy
consumption of the two of towns is presented in table 4.4 Table 4.4: Total annual energy consumption for Degehabur and Kebri Dehar towns
Name of town
Energy consumption
per day (Kwh/day)
Annual Deferrable load (Kwh)
Annual AC primary energy consumption
(Kwh)
total annual energy
Consumption (Kwh/yr)
Degehabur 5001 109,425 1,728,617 1,838,042
Kebri Dehar 4565 36,726 1,592,833 1,629,559
The deferrable load is second in priority behind the primary load, but ahead of charging the
batteries. There are two types of dispatch strategies that HOMER follows. Under the load
following strategy, HOMER serves the deferrable load only when the system is producing
excess electricity or when the storage tank becomes empty. Under the cycle charging
strategy, HOMER will also serve the deferrable load whenever a generator is operating and
able to produce more electricity than is needed to serve the primary load. Regardless of
dispatch strategy, when the level of the storage tank drops to zero, the peak deferrable load is
treated as primary load. The dispatch able power sources (generator, grid or battery bank)
will then serve as much as possible of the peak deferrable load (NREL, Homer user manual,
2008).
4.5 Load forecast for Degehabur and Kebri Dehar
4.5.1 Methodology
A forecast of the electricity demand of the towns is made based on a method known as
energy approach. In this approach the annual energy sales for residential and non-residential
customers are forecasted using appropriate growth rates and the total sum of each category is
converted to the peak demand requirement using loss rate and load factor. Other parameters
like population growth rates, customer growth (market penetration) and growth rates of
consumption per connection used in the forecast are described in the sections below.
-Residential Consumption
The domestic energy consumption is forecasted based on the population of the towns, market
penetration rates, and consumption per connection. First year population figure is projected
by an annual growth rate of 4.9%, until the end of the forecast period. This population figure
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is converted to total number of households using an assumed average number of occupants
per house.
- Market Penetration
At the first year of electrification all households may not be connected. Therefore, market
penetration rate is necessary. At the first year of interconnection 15% market penetration rate
(MP), for each town depending on its smallness and largeness is taken to change the total
number of households to potential residential customers. The MP of each town is made to
grow at a rate of 14.87% to reach an ultimate rate of 40 % in the first 12 years of
interconnection thereafter it is assumed to remain at this rate till the end of the forecast
period.
- Average Energy Consumption Per Residential Connection
The number of potential residential customers is changed to annual residential consumption
by assuming an average per household consumption, which starts with 303.7 kWh on the first
year. This average consumption per household is made to grow at a rate of 2.57% for the
whole forecast period.
- Non Residential Consumption
Consumption patterns in population centers with electrical supply were reviewed in the
Ethiopian Power System Expansion Master Plan study to determine relationship between
residential and nonresidential use. Nonresidential use Includes Commercial, street lighting
and small industrial activities. No large industrial activity is assumed for the towns under
study. Annual nonresidential consumption is estimated at 175.8 kWh for small commercial,
6.4 kWh for street lighting and 216.4 kWh for small industrial. There are no explicit forecasts
for the number of customers in each of these categories, therefore these average consumption
rates are based on the number of domestic customers. Total nonresidential consumption is
398.6kWh/year. Commercial Consumption per customer is assumed to rise at 2.98%/year,
while the annual growth in industrial consumption per customer is 1.65%. The domestic
growth rate (2.57%) was also adopted for the street lighting load.
4.5.2 Energy Requirement and Peak Power Demand
The annual energy requirement is calculated using a loss rate of 6% as expected to be
supplied from stand alone system. The peak power demand is calculated using a load factor
of 58%.
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5. Hybrid energy systems
5.1 Introduction
Hybrid energy system is an excellent solution for electrification of remote rural areas where
the grid extension is difficult and not economical. Such system incorporates a combination of
one or several renewable energy sources such as solar photovoltaic, battery and wind energy.
A hybrid system uses a combination of energy producing components that provide a constant
flow of uninterrupted power. Hybrid, wind turbine and photovoltaic modules, offer greater
reliability than any one of them alone because the energy supply does not depend entirely on
any one source. For example, on a cloudy stormy day when PV generation is low there's
likely enough wind energy available to make up for the loss in solar electricity (Science Direct,
2005).
Wind and solar hybrids also permit use of smaller, less costly components than would
otherwise be needed if the system depended on only one power source. This can substantially
lower the cost of a remote power system. The use of renewable energy sources presents a
tremendous potential for many applications and especially off-grid standalone systems. In
this context, one of the most promising applications of renewable energy technology is the
installation of hybrid energy systems (HES) in remote areas, where the grid extension is
costly and the cost of fuel increases drastically with the remoteness of the location (green,
2010).
Despite advances by hybrid power systems in improving reliability and reducing the overall
size of the power system, initial costs remain relatively high. It heaves the potential user to
reduce demand as much as possible to keep costs down. Advances in energy efficiency
permits users to meet their energy needs from smaller, less expensive power systems than
once was possible.
5.2 Stand Alone Hybrid System
The stand-alone hybrid power system is used primarily in remote areas where utility lines are
uneconomical to install due to the terrains right-of-way difficulties, or environmental
concerns. Building new transmission lines is expensive even without these constraints. A
130-kV line costs in Ethiopia more than $125,000 per kilometer. A stand-alone system would
be more economical for remote villages/towns than the rural towns are found many
kilometers far from the nearest transmission line.
Solar and wind power outputs can fluctuate on an hourly or daily basis. The standalone
system, therefore, must have some means of storing excess energy on a sunny day or a windy
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day for use on a rainy day or without wind. Alternatively, wind turbines and PV modules can
be used in a hybrid configuration with a Diesel engine generator in remote areas or with a
fuel cell in urban areas. For this thesis it only focuses on PV modules and wind turbine
configurations with storage battery system.
According to the World Bank, more than 2 billion people live in villages that are not yet
connected to utility lines (Lifelong Learning Programme Erasmus IP - RESchool, 2003).
These villages are the largest potential market for stand-alone hybrid systems using wind
turbines and PV modules for meeting their energy needs. Additionally, wind turbines and PV
modules systems create more jobs per dollar invested than many other industries. On top of
this fact they are bringing much needed electricity to rural areas and helps minimize
migration to already strained cities in most countries.
5.2.1 Typical Stand Alone Hybrid Components and Efficiencies
In this project, a parallel hybrid configuration (Figure 5.1) has been chosen due to its ability
in meeting the load optimally. Parallel hybrid configuration allows the system to decide
which component(s) to operate under a specific load. The wind turbine is coupled with
asynchronous and it operated variable wind speed. The wind turbine output directly
connected to AC bus through controller. During wind speed and solar radiation become low;
the inverter takes power from the battery, converts it to alternating current (AC) then supplies
the load. When solar and wind energy could be higher thus exports excess power to the
battery bank. In this instance, the inverter changes its function to become a battery charger.
But the maximum depth of discharge of the batteries is 60% and Controllers Keep the
batteries from overcharging and discharging rate. The maximum day autonomy is 48 hours,
meaning the batteries have a capacity to accommodate all required energy demand without
getting any power input from the system.
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Figure 5.1 PV/Battery/Wind Stand Alone System
Typical components for a standalone hybrid system are:
• Wind Turbine: Provides energy from the wind. It is variable wind speed generator coupled
with wind turbines.
• Solar modules: Provide energy from solar radiation.
• Inverters: it is an electronic circuit use to convert direct current (DC) to alternating current
(AC). Its average efficiency is 90%.
• Controllers (MPPT): Keep the batteries from overcharging and maintain the solar module at
the maximum power point output. Its average efficiency is 95%
• Batteries: Supply energy to the system when is needed and store it when is not needed. Its
average efficiency is 90%
• Wires: Electrically connect equipment together. Their average efficiency is 98%.
• Loads: Consume the power generated by the wind turbine and photovoltaic modules.
Since the subsystem, or the components, are sequential regarding the energy flow the overall
efficiency of the system is the product of individual components efficiency.
(Inverter Efficiency) (Controller Efficiency) (Wires Efficiency) (Battery Efficiency). 5.1
Where is the total stand alone system efficiency. Table 5.1 shows the average efficiency for inverter, controllers, batteries and wires used in this work. Table 5.1: Average Efficiency of hybrid system components
Using the values from table 5.1 above and equation 5.1, the total stand alone system Efficiency is:
0.80
The total efficiency of the system is approximately 80%. This means that 80% of all the
electricity produced is delivered to the loads and 20% is consumed by the wires and the
internal components, inverters, controllers and batteries.
5.2.2 Proposed Stand Alone Sizing Optimization Procedure
Hybrid system optimization modeling methodology
Inverter 0.94 Controller 0.96
Wires 0.98 Battery 0.90
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Designing optimized hybrid systems involves careful consideration of dozens of variables
including:
• Villages electricity load profile (kW for every hour of the day)
• Location-specific solar resource (taking into account that some days are cloudy and
some are sunny)
• Location-specific wind resource (monthly averages, diurnal variation)
• physical characteristics of batteries considered (capacity and voltage, cycle life,
round-trip efficiency, minimum state of charge, lifetime throughput, maximum charge
rate and maximum discharge rates)
• physical characteristics of solar panels (derating factor, slope, lifetime)
• physical characteristic of generators (output vs. fuel consumption curve, minimum
load ratio, lifetime operating hours)
• physical characteristic of wind turbines (power curve)
• Diesel fuel price
• initial, O&M and replacement costs of all components
The optimization and simulation tasks involve answering the questions,
“Which components does it make sense to include in the system design?”, “How many and of
what size each component should be used?” and “What will be the total costs involved?” The
large number of technology options and the variation in technology costs and availability of
energy resources make these decisions complex.
5.3 Economic Evaluation of the Hybrid System
5.3.1 Annual real interest rate
The annual real interest rate is one of the HOMER’s inputs which are also called the real
interest rate or just interest rate. It is the discount rate used to convert between one-time costs
and annualized costs. It is found in the Economic Inputs window. The annual real interest rate
is related to the nominal interest rate by the equation given below (NREL, HOMER user
manual, 2007):
In this equation, is the real interest rate, is the nominal interest rate (the rate at which
you could get a loan), and is the annual inflation rate.
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For Ethiopia, = 10% (19.09.2010) and = 6.0% (year 2009 annual inflation rate) are used.
With these values, according to Eq. (3) real interest rate is found around 4.0% as shown
below:
In HOMER simulations, 4.0% is used for real interest rate.
5.3.2 Levelized cost of energy
HOMER defines the levelized cost of energy (COE) as the average cost/kWh of useful
electrical energy produced by the system. To calculate the COE, HOMER divides the
annualized cost of producing electricity (the total annualized cost minus the cost of serving
the thermal load) by the total useful electric energy production. The equation for the COE is
as follows (NREL, HOMER user manual, 2007):
The total annualized cost is the sum of the annualized costs of each system component, plus
the other annualized cost.
The annualized cost of a component is equal to its annual operating cost plus its capital and
replacement costs annualized over the project lifetime. The annualized cost of each
component is equal to the sum of its: annualized capital cost, annualized replacement cost,
annual O&M cost and annual fuel cost (if applicable) (NREL, HOMER user manual, 2007).
It calculates the annualized capital cost of each component using the following equation:
5.3.3 Net present cost (NPC)
The present value of the cost of installing and operating the system over the lifetime of the
project (also referred to as lifecycle cost). Project lifetime in this study is considered as 25
years.
The total net present cost is HOMER’s main economic output. All systems are ranked
according to net present cost, and all other economic outputs are calculated for the purpose of
finding the net present cost. The net present cost is calculated according to the following
equation (NREL, HOMER user manual, 2007):
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Project lifetime [year] (25 years in this study).
The capital recovery factor is a ratio used to calculate the present value of an annuity (a series
of equal annual cash flows). The equation for the capital recovery factor is
The system costs which are given in Table5.3 will be used for HOMER simulations.
Personnel outgoings, transport cost, ground rent or price, tax and other cost are neglected in
the simulations. 10$ will be used for annual operating and maintenance costs of PV modules,
batteries and converters in simulations. Although, in ideal working conditions; PV panels,
batteries, inverters and charge regulators are inexpensive. Operating and maintenance costs
are indefinite in real working condition.
Costs of hybrid system include: components initial costs, components replacement costs,
system maintenance costs, fuel and/or operation costs, and salvage costs or salvage revenues.
Initial costs include purchasing the following equipments required by the hybrid system:
wind turbine, PV modules, batteries, diesel generator, charge controllers, bidirectional
inverter, management unit, cables, and other accessories used in the installation including
labors. Table 5.2: System cost values that used in simulations
Component Capital Cost ($)
Replacement Cost ($)
Operating and maintenance cost
($/year) Wind turbines+ tower
erection and foundation 1 kW 1500 1300 2% of Capital cost
PV modules including tracking system, installation 1 kW 6000 5000 $5
Batteries 1 Num 1700 1500 $10 Converters (Inverter + rectifier + charge
controller) 1 kW 900 900 $10 Diesel generators 1KW 500 400 0.05 ($/hr)
Wind turbine capital cost (including installation and tower) is considered as 1500 $/kW. For
every kW of PV modules, capital cost is assumed as 6000$. Surrette 4KS25P (1900 Ah)
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batteries are chosen in HOMER simulations. For every battery, 1700$ is suggested as capital
cost. Converters’ capital cost is assumed as 900$ for 1 kW. Converter cost includes inverter,
rectifier and charge controller cost. Diesel generators’ capital cost is assumed as 500$ for 1
kW. The fuel prices 1$/liter. Solar PV modules are chosen with two axis tracing system in
discussed with figure 3.4.
To determine optimum component sizes, the team used “HOMER: The Micro power
Optimization Model”, developed by the US National Renewable Energy Laboratory.
HOMER simulates the operation of a proposed system by making energy balance
calculations for each of the 8,760 hours in a year. For each hour, HOMER compares the
electricity demand in the hour to the energy that the system can supply in that hour, and then
calculates the flow of energy to and from each component of the system. This requires an
hour by- hour simulation of the solar and wind power available, as well as hour the by-hour
estimation of the electricity load. HOMER also decides for each hour on how to operate the
generators and whether to charge or discharge the batteries.
HOMER performs these energy balance calculations for each system configuration that the
software user specifies. Because we consider a range of different capacities for PV, batteries,
and inverters on two towns, there is thousands of different system configurations considered.
HOMER then determines whether each configuration is feasible, i.e., whether it can meet the
electric demand under the conditions that you specify, and estimates the cost of installing and
operating the system over the lifetime of the project. The system cost calculations account for
costs such as capital, replacement, operation and maintenance, fuel, and interest .After
simulating all of the possible system configurations, HOMER displays a list of
configurations, sorted by net present cost (sometimes called lifecycle cost).The total net
present cost of a system is the present value of all the costs that it incurs over its lifetime,
minus the present value of all the revenue that it earns over its lifetime. Costs include capital
costs, replacement costs, O&M costs, fuel costs, emissions penalties, and the costs of buying
power from the grid. Revenues include salvage value and grid sales revenue. For instance, if i
= 7% and N = 5 years, the capital recovery factor is equal to 0.2439. A $1000 loan at 7%
interest could therefore be paid back with 5 annual payments of $243.90. The present value
of the five annual payments of $243.90 is $1000.
The project life time was taken as 25 years and the annual real interest rate as 4%.each
components are own life time and it expecting to replace at the end of life time (refer
Appendix-E lifetime of each components of the hybrid system).
Main Report Final Master Thesis
The initial capital cost of a component is the total installed cost of that component at the
beginning of the project .The levelized cost of energy (COE), net present cost and initial cost
of the two towns are presented in chapter six.
5.4 Breakeven Grid Extension Distance
The distance from the grid which makes the net present cost of extending the grid equal to the
net present cost of the stand-alone system. Farther away from the grid, the stand-alone system
is optimal. Nearer to the grid, grid extension is optimal.
HOMER calculates the breakeven grid extension distance using the following equation:
5.4
Table 5.4 presented below the total distance of two towns far from the nearest gird and cost
associated with gird extension. Table 5.3: Grid extension cost for Kebri Dehar and Degehabur towns
Town of Name
Nearest substation
Voltage level
Unit cost per
km
TotalTransmission
line cost O and M cost Total cost
Kebridehar Gode 132 125,000 23,750,000 475,000 24,225,000
Degehabur Jijaga 132 125,000 20,000,000 400,000 20,400,000
The total capital costs of grid extension are 24.23 Million US dollar and 20.40 Million US
dollar, for Kebri Dehar and Degehabr respectively. Moreover, the breakeven distances from
the grid extension are 63 Kilometers and 77 Kilometers for Kebri Dehar and Degehabur
respectively, meaning which is the net present cost of grid extension equals the net present
cost of the stand-alone system. But both towns are located far from breakeven grid extension
and the detail for this we will discuss next chapter. If you go farther from this point
(breakeven grid extension distance) the stand alone is the optimal solution power supply of
the selected towns.
5.5 System architecture
Hybrid systems are fundamentally of two types: direct current (DC) bus and alternating
current (AC) bus. The key difference between the systems is that in a DC bus system, all
electricity from renewable energy sources must be produced nearby the battery bank (located
in the power house). In an AC bus system, electricity generation can occur anywhere along
the AC transmission system. Thus, solar panels can be distributed in several different
Main Re
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Main Report Final Master Thesis
Figure 5.3: Equipment to consider and hybrid system configuration for Kebri Dehar town
5.5.1 Key model input assumptions for thesis
The “optimal system” determined by HOMER depends on the input assumptions. Key
assumptions are summarized in the table below 5.4, and followed by a more detailed
discussion. Table 5.4: Key model input assumptions for model
Variable Value Data source O and M cost of PV $5/kW
Nominal interest rate 10% EEPCO
PV cost ( Including PV panels ,mounting hardware ,tracking
system, control system (maximum power point tracker)
,wiring and installation $6000/kW Green energy
Solar resource for Degehabur 6.34 kWh/day NREL datasetSolar resource for Kebridehar 6.19 kWh/day NREL dataset
Wind resource for Degehabur Annual average 5.45 m/s with monthly variation NREL dataset
Wind resource for KebrideharAnnual average 5.91 m/s with monthly variation NREL dataset
Wind turbine cost (65kW AC power)
97500/turbine including tower erection and
foundation Manufacturer
Battery cost (Types S4KS25P) $1700/Battery Green energy Converter cost $3600 for 4 kW Homer data base
Existing Diesel Generator 375 and 400 kW initial
cost $0 EEPCO
Diesel cost 1$/Liter (without subsidy)
Local interview
The sizes considered for each component are shown in Figure 5.2 and 5.3. These sizes were
iteratively determined to be sufficiently broad that HOMER did not indicate that the “search
space” of any particular item was possibly too small, while at the same time trying to reduce
the number of possible options in order to keep the computational requirements, and thus
model run time, at a manageable level.
Main Report Final Master Thesis
Figure 5.4: sizes considered for components for KebriDehar town HOMER model run
Figure 5.5: sizes considered for components for Degehabur town HOMER model run
Notes that: Eoltec is 65Kw wind turbine
Label stand for Diesel generator
S4KS25P is energy storage battery
Homer builds the search space, or set of all possible configuration, from this table and then
simulates the configuration and sorts them by net present cost.
Figure 5.6 shows the architecture of HOMER, which was taken from Fung et al. with a small
modification. There are three main parts of HOMER; inputs, HOMER simulation and
outputs.
Main Report Final Master Thesis
Figure 5.6: Architecture of HOMER simulation and optimization
6. Results and Discussion
6.1 General
In this chapter we use all concept, formulas and tables presented in previous chapters to
evaluate of hybrid renewable energy system, wind turbine and photovoltaic modules, for
Degehabur and Kebri Dehar towns. Two towns considered for this study; the town of Kebri
Dehar and Degehabur where the wind resource is moderate. The solar radiation of the towns
almost the same but slight difference. The energy demands of the two towns are different. In
each location it assumes to be serving a residential load and non residential load of a total
4.6MWh for Kebrid Dehar and 5.0 MWh for Degehabur towns per day. These load
comprised of street light, commercial and residential as well as mini industrial energy
consumption .In the economic analysis use a life time period of 25 years with an inflation rate
of 6% and nominal interest rate on the loan to finance the hybrid system of 10%.
For each location we use solar and wind data, and our optimization procedure to design
hybrid renewable power system. The author considers a standalone system and grid
connected system. For the stand alone system author seek to determine the most economic
combination of PV modules and wind turbines to serve the residential and non residential
Main Report Final Master Thesis
load. It assumes batteries have a life time of 12 years, thus a replacement of batteries is
considered at the end of year 12 and each component are to replace at the end of life time.
6.2. Simulation results
The simulation software provides the results in terms of optimal systems and the sensitivity
analysis. In this software the optimized results are presented categorically for a particular set
of sensitivity parameters like wind speed, maximum annual capacity shortage (MACS), net
present cost and fuel price in the present case.
The optimization and sensitivity results are presented in the forthcoming paragraphs.
6.2.1 Optimization results
The optimization results for Kebri Dehar and Degehabur towns summarized in figure 6.1 and
figure 6.2.Figure 6.1 and 6.2 below shows the results from HOMER modeling for Kebri
Dehar and Degehabur towns. The modeling simulates 8,760 hours (one year) of operation
and thousands of different system configurations. The system with the overall least cost of
energy is the one highest on the list. The first five columns of the HOMER results table
shows graphic icons representing which components are present in the optimized system. The
remaining columns show the optimized capacity of each component, the initial capital cost,
the total net present cost, the cost of energy (in $ per kWh), renewable energy fraction, total
liters of diesel consumed per year, and the number of hours diesel generator operates and life
time of the battery.
Figure 6.1: Overall optimization results table showing system configurations sorted by total
net present cost for Kebridehar town
Main Report Final Master Thesis
Fig 6.1 Optimization results for wind speed of 5.91 m/s daily radiation of 6.19 Kwh/m2 /day, diesel price of 1 $/L, wind operating reserve of 5% and maximum annual capacity shortage of 5% for Kebridehar town.
Figure 6.2: Overall optimization results table showing system configurations sorted by total net present cost Degehabur town.
Fig 6.2 Optimization results for annual wind speed of 5.45 m/s daily radiation of 6.34
kWh/m2 /day, diesel price of 1 $/L, wind operating reserve of 5%,solar operating reserve of
5% and maximum annual capacity shortage of 5% for Degehabur town.
Based on the HOMER modeling, the optimal system for Kebri Dehar town in figure 6.1 a
second row, a hybrid solar/wind /battery (no diesel system), with 600 kW of solar, a 6*65 kW
wind turbines ,2050 S4KS25P batteries (each 1900AH capacity) and 300 kW bi-directional
inverter are required power supplied for Kebridehar town . This “optimal” system uses 100%
renewable energy, and the cost of electricity is $0.422/kWh including depreciation on capital
and levelized O&M with net present cost of $10,283,954.
Likewise, based on the HOMER simulation results, the optimal system for Degehabur town
in figure 6.2 a second row, a hybrid solar/wind /battery (no diesel system), with 700 kW of
solar, a 8*65 kW wind turbines ,2300 S4KS25P batteries (each 1900AH capacity) and 300
kW bi-directional inverter are required power supplied for Degehabur town. This “optimal”
system uses 100% renewable energy, and the cost of electricity is $0.441/kWh including
depreciation on capital and levelized O&M with net present cost of $ 12,675,183.
The energy yield from different components of the wind/solar/battery hybrid system is shown
in Fig. 6.3 of the total primary energy requirement for Kebri Dehar town, the wind machines
produced 775,961 kWh (37% of the total energy served) while solar PV produced almost
63% of the energy i.e. 1,336,155 kWh. Although an excess energy of 291,476 kWh (13.8%)
Main Re
was prod
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Main Report Final Master Thesis
6.3 Comparison with “diesel only” for Kebri Dehar and Degehabur towns
In order to supply the same 24-hour electricity service using only diesel generators, (Figure
6.1 and 6.2) indicates that optimal hybrid system, the diesel-only system would require a 375
kW and 400 kW capacity diesel generators for Kebri Dehar and Degehabur towns
respectively, with the generator operating 8,760 hours/year. Referring figure 6.1, for Kebri
Dehar town, the diesel-only electricity supply, levelezed cost of energy is $0.564/kWh with
a net present cost of $14,995,565. In contrast, the optimal hybrid solution discussed above
provides electricity at $0.422/kWh with a net present cost of only $10,283,954. The optimal
solution thus saves the difference of about $4,711,611 over the lifetime of the project,
compared to an optimized “diesel only” option providing the same level of electricity service.
For the case of Degehabur town, the diesel-only system a levelized cost of energy is
$0.543/kWh with a net present cost of $16,395,988 and the optimal hybrid solution provides
electricity at $0.441/kWh with a net present cost of only $ 12,675,183. The optimal solution
thus saves the difference of about $ 3,720,805 over the lifetime of the project, compared to an
optimized “diesel only” option providing the same level of electricity service. Moreover, the
“diesel only” options (from both towns) produce total of around 3835 tons of CO2 per year,
whereas the hybrid system (100% renewable energy) has Zero direct CO2 and other green
houses gases emission to the atmosphere. Table 6.7 below, presented cost of energy, net
present cost and comparison of the green house gas contribution diesel-only and hybrid
system. Table 6.1: Comparison of net present cost, energy cost and green house gas emission diesel-only option with hybrid system
Name of Town Components
Net Present cost ($)
Cost of Energy ($/kWh
)
DieselConsumed per year (Liters)
Carbon dioxide emission (tons
per year)
Otheremission gas
1. Kebri Dehar Diesel only 14,995,565 0.564 692,144 1823 49
Wind/Solar/Battery 10,715,823 0.422 0 0 0
2. Degehabur Diesel only 16,395,988 0.543 763,938 2012 54
Wind/Solar/Battery 12,675,183 0.441 0 0 0
Main Report Final Master Thesis
Note that: other emission gases are carbon monoxide, unburned hydrocarbons, particulate matter, sulfur dioxide and Nitrogen oxides.
6.4 Economic analysis
The project life time was taken as 25 years and the annual real interest rate and the nominal
rate as 4% and 10%, respectively and each component are its own life time and it expecting
to replace at the end of life time.
The initial capital cost of a component is the total installed cost of that component at the
beginning of the project .The levelized cost of energy (COE), net present cost and initial cost
of the two towns are presented in the forthcoming paragraphs.
Table 4.9 and Figure 4.21 summaries the economic performance of the winning system for
Degehabur town. The capital cost constituted the largest portion of the total NPC at 67.20%,
followed by replacement cost (27.80%) and O&M costs (5.01%).
The component incurring the largest cost is the battery bank (54.97%) followed by the PV
modules (33.57%), wind turbines generator (8.08%) and inverter (3.38%) Table 6.2: Economic performance of the hybrid stand alone system for Degehabur town
Component Capital ($) Replacement ($)
O&M ($) Fuel ($)
Salvage ($) Total ($)
PV 4,200,000 0 54,677 0 0 4,254,677
WindTurbines
780,000 0 243,705 0 0 1,023,705
Batteries 4,140,229 3,734,399 359,308 0 -1,265,474 6,968,462
Converter 270,000 149,922 42,180 0 -33,761 428,341
System 9,390,229 3,884,321 699,870 0 -1,299,235 12,675,184
Levelized COE
US$0.441/kWh
The COE for the optimum system for Degehabur town found to be US$0.441/kWh. If
compared to the current electricity tariff of small residences in Ethiopia which is US$0.06
/kWh which is heavily subsidized, the COE of the RAPS system is 7.4 times higher.
However, if compared to the COE of a diesel generator only system at US$0.543/kWh, which
is a popular option for electrification of rural towns and village located far from national grid
system in Ethiopia today, the Remote Area Power Supply (RAPS) system offers a competitive
COE which is lower by 19%.Unfortunately, the capital cost of the hybrid system is far above
the generator only option. But the net present cost of diesel-only option found to be higher
than the optimal hybrid system
Main Report Final Master Thesis
Figure 6.5: Lifecycle costs of hybrid system by components for Degehabur town
Likewise, for Kebridehar towns Table 4.9 and Figure 4.21 summaries the economic
performance of the winning system for Kebridehar town. The capital cost constituted the
largest portion of the total NPC at 67.3%, followed by replacement cost (27.70%) and O&M
costs (5.05%).The component incurring the largest cost is the battery bank (55%) followed by
the PV modules (34%) ,wind turbines generator (7%) and inverter (4%). Table 6.3: Economic performance of the hybrid stand alone system for Kebridehar town.
Component Capital ($) Replacement ($)
O&M ($) Fuel($)
Salvage ($)
Total ($)
PV 3,600,000 0 46,866 0 0 3,646,866
Wind Turbines
585,000 0 182,778 0 0 767,779
Batteries 3,485,000 3,120,262 320,253 0 -1,057,362 5,868,153
Converter 270,000 149,922 46,866 0 -33,761 433,027
System 7,940,000 3,270,183 596,764 0 -1,091,122 10,715,826
Levelized COE
US$0.422/kWh
The COE for the optimum system for Kebridehar town found to be US$0.422/kWh. If
compared to the current electricity tariff of small residences in Ethiopia which is US$0.06
/kWh which is heavily subsidized, the COE of the RAPS system is 7.03 times higher.
However, if compared to the COE of a diesel generator only system at US$0.564/kWh, which
is a popular option for rural electrification in Ethiopia today, the Remote Area Power Supply
(RAPS) system offers a competitive COE which is lower by 25%.Unfortunately, the capital
cost of the hybrid system is far above the generator only option. But the net present cost of
diesel-only option found to be higher than the optimal hybrid system
Main Report Final Master Thesis
Figure 6.6: Lifecycle costs of hybrid system by components for Kebridehar town
6.5 Sensitivity results
The HOMER software simulates all the systems in their respective search space for each of
the sensitivity values. An hourly time series simulation is performed for one complete year. A
feasible system is defined as the hybrid system which meets the required load. The software
eliminates all infeasible systems and presents the results in ascending order of NPC. In the
present case wind speed (5.91 and 5.45 m/s, diesel price (1.0, 1.3 and 1.5 $/L). A total of
3600 sensitivity cases were tried for each system configuration. Overall 50 systems were
simulated for 600 sensitivities which mean a total of 4320 combinations were tried.
6.5.1 Cost of energy sensitivity to diesel price – Kebri Dehar and Degehabur towns
Costs of energy appear to vary in line with diesel prices (Figure 6.5) – not surprising
considering that diesel is the main energy source in the system. Base case cost of energy for
KebriDehar is $0.564/kWh $0.543/kWh for Kebri Dehar and Degehabur towns respectively
and if diesel remains at $1.0/liter. In the highest diesel price scenario ($1.5/liter) the cost of
energy is $0.771/kWh and 0.738/kWh for Kebri- Dehar and Degehabur towns respectively.
But the hybrid energy supply systems which show in the figure 6.5 the diesel price is not
affect the cost of energy meaning all energy supply comes from renewable energy resource.
The overall cost savings from a hybrid system compared with a diesel-only option increases
with increasing diesel price (Figure 6.7) since hybrid systems totally not fuel dependant.
Main Re
Figure 6.7price sce
6.5.2 Lif
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diesel pr
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Figure 6.8price sce
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ebri Dehar
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20,521,246,
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wn
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nd
gh
nd
Main Report Final Master Thesis
The hybrid life cycle costs of the two towns are keep constant since the diesel price is not
totally meaningful change on the system throughout project life time.
6.6 Comparison of the Grid extension with standalone (Off Grid) and
diesel-only system
The distance from the grid which makes the net present cost of extending the grid equal to the
net present cost of the stand-alone system. Farther away from the grid, the stand-alone system
is optimal. Nearer to the grid, grid extension is optimal. The unit cost of 132 kV single circuit
transmission line (steel lattices supported) with Optical Fiber Ground Wire (OPGW) is
125,000USD per km. The operating and maintenance cost of the transmission is 2% of capital
cost is around $2500/Km per year. Degebabur is located 160 Km and Kebri Dehar is located
190 km from nearest national grid system.
The total capital costs of grid extension are 24.23 Million US dollar and 20.40 Million US
dollar, for Kebri Dehar and Degehabr respectively. Moreover, the breakeven distances from
the grid extension are 63 Kilometers and 77 Kilometers for Kebri Dehar and Degehabur
respectively, meaning which is the net present cost of grid extension equals the net present
cost of the stand-alone system. Both towns are located very far from breakeven grid
extension If you go farther from this point (breakeven grid extension distance) the stand alone
is the optimal solution power supply of the selected towns. Figure 6.7 and figure 6.8 show the
net present cost comparison of standalone system with grid extension of Kebri Dehar and
Degehabur towns. Therefore, the standalone system is the optimal solution of power supply
for the two towns since the net present cost of grid extension much higher than standalone
Main Re
Figure 6.9
Figure 6.
Solar PV
than 63 K
and their
below in
1.172 and
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see table `Table 6.4
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6.4. 4: Energy c
Name of Towns
Kebri Deh
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rison of Grid
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and 77 Kilo
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ri Dehar and
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Diesel-Only PV/Wind/Batt
rid Extension
Diesel-Only PV/Wind/Batt
rid Extension
ith standalon
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To(k
9,8965,941
95,284
49,540 1,363
80,239
f Kebri Deha
of Degehabu
sion for dist
ehabur towns
respectively
Dehar and D
pectively. M
nsion arrang
(Solar PV/W
nd diesel-on
otal Demand kWh/Year)
1,702,951 1,625,057
1,702,951
1,934,455 1,839,797
1,934,455
r town
ur town.
tances greate
s respectivel
y. In table 6
Degehabur ar
oreover, eve
gement. Gri
Wind/Battery
ly system
Cost of Energy ($/kWh)
0.564 0.422
1.172
0.543 0.441
0.869
er
ly
.4
re
en
id
y)
Main Report Final Master Thesis
7. Conclusion and Recommendation
7.1 Conclusions
This study aimed to identify options and to design feasible systems to provide electricity for
Degehabur and Kebridear towns in Somalia region, Ethiopia by harnessing power from
renewable energy resources.
Two power supply options have been identified. The first option was a hybrid (standalone
Solar/wind/battery) system and the second option was to construct new transmission line
from nearest substation to selected towns. The HOMER simulation program developed by the
NREL has been used as the design tool for both options.
HOMER modeling results indicate that both Kebri Dehar and Degehabur towns electricity
needs could be met at considerable overall cost savings with a hybrid (wind/solar/Battery)
system compared with existing separate diesel generator systems. At existing diesel prices
and in a “base case” load scenario, the optimum system comprises a hybrid solar/wind/battery
system., based on the simulation result, the optimal system for Kebri Dehar town, a hybrid
solar/wind /battery (no diesel system), with 600 kW of solar, a 6*65 kW wind turbines, 2050
S4KS25P batteries (each 1900AH capacity) and 300 kW bi-directional inverter. This
“optimal” system uses 100% renewable energy, and the cost of electricity is $0.422/kWh
including depreciation on capital and levelized O&M with net present cost of $10,715,823.
Likewise, according to simulation results, the optimal system for Degehabur town, a hybrid
solar/wind /battery (no diesel system), with 700 kW of solar, a 8*65 kW wind turbines ,2300
S4KS25P batteries (each 1900AH capacity) and 300 kW bi-directional inverter has been
selected. This “optimal” system uses 100% renewable energy, and the cost of electricity is
$0.441/kWh including depreciation on capital and levelized O&M with net present cost of $
12,675,183.
The sensitivity Costs of energy appear to vary in line with diesel prices – not surprising
considering that diesel is the main energy source in the system. Base case cost of energy for
Kebri Dehar is $0.568/kWh and $0.541/kWh for Kebri Dehar and Degehabur towns,
respectively and if diesel remains at $1.0/liter. In the highest diesel price scenario ($1.5/liter)
the cost of energy was $0.771/kWh and 0.738/kWh for Kebri- Dehar and Degehabur towns,
respectively.
The sensitivity of life-cycle cost (net present cost) to different diesel price scenarios was
considered. Scenarios of high diesel price result in net present cost for Kebri Dehar town
approaching $ 20,521,246, whereas the lowest end scenario is just over $15,114,885.then for
Main Report Final Master Thesis
case of Degehabur town, scenarios of high diesel price result in net present cost approaching
$ 22,304,360, while the lowest end scenario is just over $16,337,213.
Though the optimum system configuration changes under different diesel price assumptions,
the hybrid system remains most economically feasible solution than the existing
arrangements (diesel-only), under all scenarios considered. The COE for Degehabur and
Kebridehar towns the above mention hybrid system, the COE of the RAPS system is 7 times
higher than a current electricity tariff which is heavily subsidized, but 25% lower than a
diesel only system’s COE for Kebridehar and 19% a diesel only system’s COE for
Degehabur towns.
Moreover, the “diesel only” options (from both towns) produce total of around 3835 tons of
CO2 per year, whereas the hybrid system (100% renewable energy) have illegible green
houses gases emission to the atmosphere.
The second option looked at power supplied from the nearest substation. This options also
performed better for grid extension for distances less than 78 and 64km for Keberidehar and
Degeabur towns ( both towns are located very far from this point) ,respectively and their
energy costs were computed as 1.172 and 0.869 $/kWh for Kebri Dehar and Degehabur
towns respectively. The total capital costs of grid extension are 24.23 Million US dollar and
20.40 Million US dollar, for Kebri Dehar and Degehabr respectively. Furthermore, the
breakeven distances from the grid extension are 63 Kilometers and 77 Kilometers for Kebri
Dehar and Degehabur respectively, meaning which is the net present cost of grid extension
equals the net present cost of the stand-alone system. If you go further from these points
(breakeven grid extension distance), a hybrid (stand-alone) system are optimal solution the
power supply the selected towns .But both towns are located 150 km from the nearest
national grid.
Degehabur and Kebridehar towns located 160 km and 190 km, respectively from existing
substation and a 132 kV voltage level is selected. The voltage selection criteria of
transmission lines are mainly based on the power to be transmitted and on the distance
between delivery and receiving ends. The power supplied from the nearest substation for both
towns total net present cost of $44.46 Million, whereas hybrid (solar/wind/battery) total net
present cost is $23 Million system. A grid extension power supply option almost $22 million
higher than standalone system throughout project life time. The grid extension of energy cost
for Kebri Dehar and Degehabur are 1.172 and 0.869 $/kWh for Kebri Dehar and Degehabur
Main Report Final Master Thesis
towns respectively. However, even the diesel only option performed better than grid
extension for distances greater than breakeven point.
Finally the Author proposed that standalone system (solar/wind/battery) is economically
feasible and environmentally friendly to replace the existing diesel-only power supply system
for Kebri Dehar and Degehabur towns.
7.2 Recommendation and Further work
The study recommends collecting wind speed data at the actual site at three
different heights using a wind mast of 40m for at least one complete year. This
data then must be used for final feasibility of the hybrid system.
This study shows only focus on two selected towns of Somalia region in
Ethiopia and it doesn’t cover all towns and villages around Somalia region.
So, the future researchers should expand this research work in other sites and
make the rural people beneficial with renewable energy resource.
In spite of the huge hydroelectric potential of Ethiopia, severe power cuts in
recent years have a heavy impact on the country’s economy.Solar thermal
technology recommended to be incorporated for the future grid connected
application to create a strength, reliability and maintaining sustainable energy
supply of the country. Somalia region has a great solar resource potential and
has not yet properly exploited this resource.
The Software HOMAR used for optimization in this study is found privately
not capacities solve different types of sensitivity analysis and other advanced
features, and it is commercially available for the future use of similar
assignments. Thus it is advisable if EEPCo purchases this software or other
comprehensive optimization software of highbred nature
Bibliography
(n.d.). Retrieved from http://www.ace.mmu.ac.uk/eae/climate/older/Prevailing_Winds.html.
Power system Planning. (2008). Rural Electrfication. June. MENDI – GIDAMI 132 KV POWER TRANSMISSION PROJECT.
A. Luque, S. H. (2003). (Handbook of Photovoltaic Science andEngineering).
Akpinar, E. K. (2004, July 3). sciencedirect. Retrieved from http://www.sciencedirect.com/science.
Alet. (2010). Alternative energy store. Retrieved from http://www.altestore.com/store.
Main Report Final Master Thesis
Archiba. ( 2001). VAWT Darrieus-windmill snapshot.
bank, W. Rural Energy and Development.
BBC. (2009). BBC home page. Retrieved from http://news.bbc.co.uk/2/hi/africa/country_profiles/1072164.stm.
Beckman, J. A. (1980). Solar engineering of thermal process, John Wiley and Sons Inc. New York.
Bekele, G. (2009). Wind energy potential assessment at four typical locations in Ethiopia.
Boyle, G. (1996). “Renewable Energy – Power for a sustainable future”; .
Canada, M. o. (2001). WIND ENERGY PROJECT ANALYSIS.
Celik, A. N. (2003, October 4). sciencedirect. Retrieved from http://www.sciencedirect.com/science.
Dalelo, A. RURAL ELECTRIFICATION IN ETHIOPIA:OPPORTUNITIES AND BOTTLENECKS.
Development, E. R. (2007). Solar and Wind Energy Utilization and Project Development Scenarios.
DEVINE, M. M. (2005). ANALYSIS OF ELECTRIC LOADS AND WIND- DIESEL ENERGY OPTIONS FOR REMOTE POWER STATIONS IN ALASKA,A Masters Project.
DWEA. (2003). Danish Wind Industry Association. June 2003. Guided Tour on Wind Energy. Retrieved from http://www.windpower.org/en/tour/index.htm.
EEA. (2002). Rural Electrification Symposium Proceedings,(Ethiopian Electric Agency) March 1-5,2002.
EEPCO. (2006). Master plan. Ethiopian Electric Power Corporation Master Plan, 2003.
Energy, U. d. (2010). Energy Efficiency and Renewable energy. Retrieved from http://www1.eere.energy.gov/windandhydro/wind_how.html.
Energy, W. W. (2009). World Wind Energy, Worldwide installed capacity and. Retrieved from http://www.wwindea.org.
Engineering and Consulting Firms Association, J. (2007). Pre-Feasibility Study for Rural Electrification Program by Renewable Energy In The Mountainous Region of Northern Samar in the Philippines.
General Guidelines for Writing Master’s Thesis Report (in English).
Gipe, P. (2004). Wind Power: Renewable Energy for Home, Farm, and Business).
green, C. (2010). Chelsea green . Retrieved from http://www.chelseagreen.com/content/tips-for-living-off-the-grid-using-a-hybrid-solarwind-system/.
Heimann, S. (2007). Renewable Energy in Ethiopia . Addis Ababa.
Heimann, S. (2007). Renewable Energy in Ethiopia. Addis Ababa.
Main Report Final Master Thesis
International, C. (2006). Grassroots Conflict Assessment Of the Somali Region, Ethiopia. Ethiopia: August.
Kassam, A. (2010). HOMER Software Training Guide for Renewable Energy Base Station Design.
KYOCERA. (2004). Retrieved from http://www.kyocerasolar.com/learn/modules.html.
Kyocera. (2009, October). Kyocera Solar module. Retrieved from http://www.kyocerasolar.com/pdf/catalog/Modules.pdf.
Mapsof. (2010). Retrieved from http://mapsof.net/ethiopia/static-maps/png/somali-region-and-towns.
Masters, G. M. (2004.). . Renewable and Efficient Electric Power Systems,page 310. John Wiley & Sons, Incorporated., Hoboken, . NJ, USA, .
MILANI, N. P. (2006). PERFORMANCE OPTIMIZATION OF A HYBRID WIND TURBINE-DIESEL MICROGRID POWER SYSTEM.
NREL. (2010). Formula for Estimating Energy Consumption.
NREL. (2007). HOMER user manual.
NREL. (2008). Homer user manual.
NREL. (1997). Sizing Wind/Photovoltaic Hybrids for Households in Inner Mongolia.
office, P. s. (2006). Ethiopian Electric Power master plan update. Addis Ababa.
Ortiz. (2006). Eduardo Ivan Ortiz Rivera “Modeling and analysis of solar distributed.
Patel, M. (2006). (Wind and Solar Power Systems), Second Edition, Taylor & Francis.
PAUL GILMAN and PETER LILIENTHAL. MICROPOWER SYSTEM MODELING WITH HOMER. National Renewable Energy Laboratory.
Planning Power system. (2008). Rural Electrfication. June. MENDI – GIDAMI 132 KV POWER TRANSMISSION PROJECT.
planning, p. s. (2008). Addis Ababa: MENDI – GIDAMI 132 KV POWER TRANSMISSION PROJECT,.
planning, p. s. (2008). MENDI – GIDAMI 132 KV POWER TRANSMISSION PROJECT. Addis Ababa.
Prasad, R. D. A Case Study for Energy Output using a Single Wind Turbine and a Hybrid System for Vadravadra Site in Fiji Islands.
Rehman, S. (2005). Feasibility study of hybrid retrofits to an isolated off-grid diesel power plant.
RETSCREEN. (n.d.). RETSCREEN International, Renewable Energy Project Analysis: Retscreen Engineering and Cases Textbook. Retrieved from Available: http://www.retscreen.net.
Main Report Final Master Thesis
Science Direct. (2005, December 1). Retrieved from http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V4S-4KBDWF5-1&_user=713833&_coverDate=06%2F30%2F2007&_rdoc=1&_fmt=high&_orig=search&_origin=search&_sort=d&_docanchor=&view=c&_searchStrId=1558012988&_rerunOrigin=google&_acct=C000039878&_version=.
Shenck, N. (n.d.). Wind theory I MIT LAB. Retrieved from http://alumni.media.mit.edu/~nate/AES/Wind_Theory_I.pdf.
Solarbuzz. (2010, October). Retrieved from http://www.solarbuzz.com/ModulePrices.htm.
State Energy Conservation Office (SECO). (2010). Retrieved from http://www.seco.cpa.state.tx.us/publications/renewenergy/solarenergy.php.
Svensson, M. H. (2004). Renewable Power for the Swedish Antarctic Station Wasa,Master of Science Thesis. Stockholm, Sweden.
T. Burton, D. S. (2001). Wind Energy Hanbook.
TFODE. (2009). Retrieved from http://enc.tfode.com/Shilabo.
UNDP Emergencies Unit for Ethiopia. ( 2000, March). Retrieved from http://www.reliefweb.int/mapc/afr_ne/cnt/eth/ethiopia_zones.html.
USDE. (2004). Department of Energy-National Renewable Energy Laboratory, “The history of Solar” NREL 2004".
W.Teste, J. (2005). Sustainable Energy Choosing Among Options. Massachusetts: The MIT press.
Weldemariam, L. E. (2010). GENSET-SOLAR-WIND HYBRID POWER SYSTEM OF OFF-GRID POWER STATION FOR RURAL APPLICATIONS.
Wikipedia. (2010, July 15). Retrieved 2010, from http://en.wikipedia.org/wiki/Wind_profile_power_law.
Wikipedia. (2010, November). Retrieved from http://en.wikipedia.org/wiki/Weibull_distribution.
Wikipedia, the free encyclopedia. (2010, March 5). Retrieved from http://en.wikipedia.org/wiki/Degehabur_Zone.
Wikipedia, the free encyclopedia. (2010, February 22). Retrieved from http://en.wikipedia.org/wiki/Korahe_Zone.
WindPowerProgram. (n.d.). Retrieved from http://www.wind-power-program.com/turbine_characteristics.htm.
World Wind Energy 2009). (2009). Retrieved from http://www.wwindea.org/home/index.php.
Yang, D. (2007). Performance Analysis of a Grid Connected Hybrid Photovolatic and Wind Electricity Generation System in Cold Climate.
Main Report Final Master Thesis
List of Appendixes
Appendix–A
Figure A.1 Location map of project area
Source:EEPCO
Main Report Final Master Thesis
Table A.1 Maximum Temp. in oC for Keberidehar and Degehabur town
For Kebri Dehar Town For Degehabur Town
Year Year Year Year
Month 2007 2008 Month 2007 2008
Jan 35.1 35.1 Jan 31.4 31.7 FEB 36.1 35.7 FEB 32 33.0
MAR 36.8 36.7 MAR 33.7 32.8 APR 36.0 34.5 APR 32.3 32.3 MAY 33.3 32.5 MAY 31.3 30.1 JUN 32.0 31.9 JUN 29.1 31.9 JUL 31.1 32.2 JUL 28.3 28
AUG 31.7 32.0 AUG 30.8 29.7 SEP 33.9 33.7 SEP 30.7 32.2 OCT 33.3 32.0 OCT 32.5 31.4 NOV 34.0 34.3 NOV 31.6 30.9
DEC 34.6 34.9 DEC 31.2 31.3
Average 34.0 34.8 Average 31.2 31.1
Annual Average 34.8 Annual Average 31.2
Source: NMSA
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Table A.3 Energy and Power Forecast For Degehabur town
RurDom RurComm RurLV RurStrL RurTotal
Year KWh KWh KWh KWh KWh
2009 601,933 348,436 428,905 12,685 1,391,959
2010 711,854 413,493 503,282 15,001 1,643,630
2011 839,480 489,103 589,490 17,691 1,935,764
2012 987,698 576,987 689,456 20,814 2,274,955
2013 1,159,465 678,917 805,136 24,434 2,667,952
2014 1,358,728 797,245 939,172 28,633 3,123,778
2015 1,589,838 934,569 1,094,463 33,503 3,652,373
2016 1,857,560 1,093,742 1,274,173 39,145 4,264,620
2017 2,168,000 1,278,403 1,482,382 45,687 4,974,472
2018 2,527,418 1,492,299 1,723,242 53,261 5,796,220
2019 2,944,057 1,740,346 2,002,266 62,041 6,748,711
2020 3,146,666 1,865,693 2,125,759 66,311 7,204,429
2021 3,360,556 1,998,291 2,255,617 70,818 7,685,282
2022 3,586,624 2,138,708 2,392,379 75,582 8,193,293
2023 3,825,184 2,287,177 2,536,158 80,610 8,729,128
2024 4,077,163 2,444,290 2,687,503 85,920 9,294,875
2025 4,342,907 2,610,303 2,846,539 91,520 9,891,269
2026 4,623,681 2,786,011 3,014,042 97,437 10,521,170
2027 4,919,870 2,971,701 3,190,151 103,679 11,185,401
2028 5,232,175 3,167,848 3,375,225 110,260 11,885,508
2029 5,561,921 3,375,289 3,570,062 117,209 12,624,480
2030 5,909,556 3,594,362 3,774,821 124,535 13,403,274
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TableA.2 Energy and Power Forecast For Keberdehar town
RurDom RurComm RurLV RurStrL RurTotal Year KWh KWh KWh KWh KWh
2009 529,045 306,244 376,969 11,149 1,223,407
2010 625,856 363,539 442,482 13,189 1,445,066
2011 738,213 430,101 518,382 15,557 1,702,253
2012 868,339 507,261 606,138 18,299 2,000,037
2013 1,019,424 596,916 707,893 21,483 2,345,716
2014 1,194,740 701,022 825,825 25,177 2,746,765
2015 1,397,947 821,767 962,367 29,460 3,211,540
2016 1,633,405 961,756 1,120,421 34,421 3,750,003
2017 1,906,195 1,124,025 1,303,371 40,170 4,373,762
2018 2,222,137 1,312,049 1,515,093 46,828 5,096,106
2019 2,588,412 1,530,112 1,760,387 54,547 5,933,458
2020 2,766,393 1,640,228 1,868,852 58,297 6,333,770
2021 2,954,717 1,756,966 1,983,219 62,266 6,757,167
2022 3,153,348 1,880,347 2,103,367 66,452 7,203,514
2023 3,363,158 2,010,920 2,229,826 70,873 7,674,778
2024 3,584,738 2,149,077 2,362,917 75,543 8,172,273
2025 3,818,390 2,295,042 2,502,747 80,467 8,696,645
2026 4,065,335 2,449,576 2,650,078 85,671 9,250,660
2027 4,325,612 2,612,759 2,804,818 91,155 9,834,345
2028 4,600,171 2,785,199 2,967,521 96,941 10,449,833
2029 4,889,986 2,967,525 3,138,751 103,049 11,099,311
2030 5,195,753 3,160,207 3,318,865 109,492 11,784,317
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Appendix-B
TableB.1
Monthly Averaged Wind Direction At 50 m Above The Surface Of The Earth (degrees) for Kebridehar and Degehabur town
Lat 6.75 Lon 44.283 for Kebridehar
Lat 6.75 Lon 44.283 for Degehabur
Month 10-year Average
Month 10-year Average
Jan 64 Jan 57
Feb 67 Feb 62
Mar 74 Mar 68
Apr 79 Apr 70 May 100 May 75
Jun 175 Jun 126
Jul 204 Jul 205
Aug 211 Aug 218
Sep 214 Sep 224
Oct 212 Oct 225
Nov 208 Nov 225
Dec 202 Dec 222
Notes
measured clockwise from True North
direction the wind is coming from
The monthly average wind direction for a given month, averaged for that month over the 10-year period (July 1983 - June 1993).
Wind direction values are for 50 meters above the surface of the earth.
Source:NASA
Main Report Final Master Thesis
Table B.2 Probability density vs. wind speed at hub height in Kebridehar and Degehabur towns
Kebridehar town Degehabur town
NO.
Wind speed at 50meter Hub
Height In [m/s]
Wind Probability Density in
[%]
Wind speed at 50meter Hub
Height In [m/s] Wind Probability
Density [%] 1 0.0 0.000 0.000 0.000 2 0.5 2.246 0.500 2.665 3 1.5 6.413 1.500 7.509 4 2.5 9.751 2.500 11.205 5 3.5 11.917 3.500 13.349 6 4.5 12.795 4.500 13.870 7 5.5 12.492 5.500 13.009 8 6.5 11.281 6.500 11.203 9 7.5 9.513 7.500 8.943
10 8.5 7.537 8.500 6.658 11 9.5 5.633 9.500 4.642 12 10.5 3.982 10.500 3.039 13 11.5 2.669 11.500 1.872 14 12.5 1.698 12.500 1.087 15 13.5 1.026 13.500 0.595 16 14.5 0.590 14.500 0.308 17 15.5 0.323 15.500 0.151 18 16.5 0.169 16.500 0.070 19 17.5 0.084 17.500 0.030 20 18.5 0.040 18.500 0.013 21 19.5 0.018 19.500 0.005 22 20.5 0.008 20.500 0.002 23 21.5 0.003 21.500 0.001 24 22.5 0.001 22.500 0.000 25 23.5 0.000 23.500 0.000
26 24.5 0.000 24.500 0.000
Main Report Final Master Thesis
Table B.3 Wind speed daily profile for Degehabur
Time in Hours JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
m/s m/s m/s m/s m/s m/s m/s m/s m/s m/s m/s m/s
0.50 4.35 4.78 3.80 2.60 3.57 5.11 6.46 5.97 4.47 3.10 3.72 4.40 1.50 4.28 4.51 3.78 2.55 3.47 5.10 6.36 5.78 4.44 3.18 3.65 4.26 2.50 4.21 4.24 3.76 2.49 3.37 5.10 6.27 5.60 4.41 3.25 3.58 4.12 3.50 4.12 4.17 3.65 2.67 3.35 5.48 5.62 5.54 4.54 3.11 3.48 4.18 4.50 4.15 4.17 3.60 2.75 3.40 5.68 5.73 5.74 4.40 3.22 3.59 4.25 5.50 4.17 4.18 3.55 2.84 3.45 5.88 5.84 5.93 4.26 3.32 3.70 4.31 6.50 4.71 4.39 3.97 2.94 3.83 6.55 6.67 7.10 4.43 3.71 3.60 5.22 7.50 4.97 4.66 3.98 3.09 4.13 6.87 7.09 7.38 4.63 3.86 3.82 5.46 8.50 5.23 4.92 3.99 3.25 4.43 7.18 7.50 7.66 4.82 4.01 4.03 5.70 9.50 6.02 5.80 4.71 3.63 4.94 7.83 8.52 7.65 5.71 4.02 4.75 5.97
10.50 6.29 6.03 4.89 3.69 5.27 8.17 8.83 7.73 6.09 4.00 4.98 6.20 11.50 6.57 6.27 5.07 3.75 5.60 8.50 9.14 7.80 6.46 3.97 5.22 6.42 12.50 7.62 6.84 5.18 4.22 5.61 8.98 9.52 8.07 6.93 4.30 5.82 6.53 13.50 7.83 6.74 5.29 4.28 5.56 9.04 9.51 8.24 7.04 4.39 5.91 6.40 14.50 8.03 6.64 5.40 4.34 5.50 9.10 9.49 8.42 7.14 4.48 5.99 6.27 15.50 7.48 6.42 5.49 4.43 5.65 9.21 9.06 8.25 6.99 4.76 6.14 6.36 16.50 7.32 6.49 5.40 4.30 5.72 9.04 8.86 8.11 6.87 4.66 6.11 6.33 17.50 7.16 6.56 5.31 4.17 5.80 8.86 8.66 7.96 6.74 4.57 6.08 6.31 18.50 6.75 5.91 4.91 3.93 5.48 7.94 8.29 7.84 6.32 4.35 5.79 6.08 19.50 6.35 5.64 4.90 3.82 5.17 7.84 8.04 7.62 6.20 4.23 5.40 5.94 20.50 5.95 5.36 4.90 3.72 4.87 7.74 7.79 7.40 6.07 4.10 5.01 5.79 21.50 4.90 5.08 4.24 3.13 4.16 6.66 6.99 6.55 5.60 3.64 4.39 5.29 22.50 4.78 4.86 4.22 2.94 3.98 6.40 6.66 6.25 5.44 3.49 4.19 5.06
23.50 4.67 4.64 4.21 2.74 3.80 6.14 6.33 5.96 5.28 3.34 3.98 4.83
Main Report Final Master Thesis
Table B.4 Wind speed daily profile for Kebridehar
Time in Hours JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
m/s m/s m/s m/s m/s m/s m/s m/s m/s m/s m/s m/s
0.50 4.52 5.03 3.90 2.80 4.58 5.83 7.07 6.63 5.19 3.41 3.26 4.411.50 4.46 4.76 3.89 2.74 4.46 5.82 6.98 6.42 5.15 3.49 3.20 4.302.50 4.39 4.49 3.87 2.68 4.35 5.82 6.88 6.21 5.10 3.57 3.15 4.183.50 4.31 4.40 3.76 2.88 4.31 6.24 6.18 6.17 5.26 3.42 3.06 4.224.50 4.33 4.42 3.71 2.96 4.38 6.44 6.30 6.39 5.10 3.54 3.15 4.265.50 4.36 4.44 3.67 3.05 4.44 6.63 6.42 6.62 4.95 3.65 3.24 4.306.50 4.92 4.69 4.09 3.16 4.93 7.39 7.34 7.90 5.14 4.05 3.19 5.207.50 5.20 4.96 4.11 3.32 5.30 7.74 7.80 8.23 5.36 4.22 3.35 5.458.50 5.48 5.24 4.12 3.49 5.67 8.08 8.26 8.55 5.57 4.39 3.52 5.709.50 6.27 6.17 4.85 3.88 6.35 8.80 9.38 8.59 6.62 4.44 4.19 5.97
10.50 6.56 6.42 5.04 3.96 6.73 9.18 9.72 8.68 7.06 4.41 4.39 6.2011.50 6.84 6.67 5.24 4.04 7.10 9.56 10.07 8.78 7.50 4.39 4.58 6.4212.50 7.90 7.25 5.37 4.54 7.18 10.10 10.46 9.13 8.01 4.74 5.10 6.5213.50 8.11 7.15 5.49 4.59 7.12 10.17 10.45 9.31 8.11 4.84 5.17 6.4114.50 8.32 7.04 5.61 4.65 7.06 10.24 10.44 9.50 8.22 4.94 5.24 6.2915.50 7.76 6.84 5.68 4.75 7.22 10.35 10.01 9.33 8.06 5.23 5.37 6.3616.50 7.60 6.91 5.58 4.62 7.32 10.17 9.79 9.15 7.93 5.13 5.33 6.3417.50 7.43 6.97 5.48 4.49 7.41 9.98 9.58 8.97 7.80 5.03 5.30 6.3118.50 7.03 6.29 5.06 4.21 7.02 8.93 9.15 8.78 7.31 4.79 5.06 6.0819.50 6.62 6.00 5.04 4.09 6.62 8.83 8.86 8.54 7.14 4.65 4.71 5.9420.50 6.21 5.71 5.03 3.97 6.23 8.72 8.58 8.29 6.98 4.51 4.36 5.7921.50 5.10 5.38 4.38 3.37 5.36 7.50 7.69 7.30 6.42 3.97 3.83 5.3022.50 4.98 5.15 4.35 3.16 5.12 7.21 7.33 6.98 6.25 3.82 3.66 5.05
23.50 4.86 4.93 4.32 2.95 4.89 6.92 6.96 6.66 6.07 3.66 3.49 4.81
Main Report Final Master Thesis
Table B.5 Global Horizontal Solar Radiation Daily profile for Degehabur town
Timein
Hours JAN FEB MAR APR MAY JUNE JULY AUG SEP OCT NOV DEC kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
0.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.50 0.10 0.10 0.12 0.15 0.17 0.15 0.12 0.14 0.16 0.17 0.16 0.12 7.50 0.24 0.23 0.27 0.28 0.30 0.26 0.24 0.27 0.31 0.31 0.31 0.25 8.50 0.39 0.37 0.42 0.41 0.42 0.37 0.35 0.39 0.45 0.45 0.45 0.39 9.50 0.73 0.70 0.78 0.68 0.66 0.62 0.58 0.65 0.75 0.78 0.72 0.69
10.50 0.80 0.79 0.84 0.74 0.72 0.68 0.64 0.71 0.81 0.82 0.79 0.77 11.50 0.86 0.88 0.90 0.81 0.77 0.74 0.70 0.77 0.86 0.86 0.85 0.84 12.50 0.90 0.92 0.93 0.83 0.78 0.76 0.72 0.82 0.88 0.86 0.85 0.82 13.50 0.83 0.87 0.88 0.77 0.73 0.69 0.67 0.77 0.81 0.79 0.78 0.76 14.50 0.75 0.81 0.82 0.71 0.68 0.63 0.62 0.71 0.74 0.71 0.72 0.70 15.50 0.46 0.51 0.49 0.43 0.44 0.40 0.37 0.45 0.47 0.42 0.41 0.42 16.50 0.32 0.36 0.35 0.31 0.31 0.29 0.27 0.33 0.32 0.27 0.26 0.27 17.50 0.18 0.21 0.21 0.18 0.17 0.18 0.17 0.20 0.18 0.13 0.11 0.13 18.50 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.01 0.00 0.00 0.00 0.00 19.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 20.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 21.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 22.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
23.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Main Report Final Master Thesis
Table B.6 Global Horizontal Solar Radiation Daily profile for Kebridehar town
JAN FEB MAR APR MAY JUNE JULY AUG SEP OCT NOV DEC
Time in Hours
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
1.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.50 0.11 0.11 0.13 0.15 0.17 0.15 0.12 0.14 0.17 0.16 0.17 0.13 7.50 0.25 0.26 0.28 0.28 0.28 0.26 0.24 0.26 0.31 0.29 0.31 0.27 8.50 0.39 0.40 0.43 0.40 0.39 0.37 0.35 0.38 0.45 0.42 0.44 0.40 9.50 0.73 0.73 0.78 0.66 0.62 0.62 0.58 0.63 0.74 0.73 0.70 0.70
10.50 0.79 0.82 0.84 0.73 0.67 0.68 0.64 0.69 0.79 0.76 0.76 0.78 11.50 0.85 0.91 0.90 0.79 0.72 0.74 0.70 0.74 0.84 0.79 0.82 0.85 12.50 0.88 0.95 0.92 0.81 0.73 0.75 0.71 0.78 0.85 0.79 0.81 0.83 13.50 0.80 0.90 0.86 0.75 0.68 0.68 0.66 0.73 0.79 0.72 0.75 0.76 14.50 0.72 0.84 0.81 0.68 0.62 0.62 0.61 0.68 0.72 0.65 0.69 0.70 15.50 0.44 0.52 0.48 0.41 0.40 0.39 0.36 0.42 0.45 0.38 0.39 0.42 16.50 0.30 0.37 0.34 0.29 0.28 0.28 0.26 0.30 0.30 0.25 0.25 0.27 17.50 0.17 0.21 0.20 0.16 0.15 0.16 0.16 0.18 0.16 0.11 0.11 0.13 18.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 19.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 20.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 21.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 22.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 23.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Main Report Final Master Thesis
Table B.7 Global Solar radiation incident on PV Array Daily Profile with tracking system for
Degehabur town
Timein
Hours JAN FEB MAR APR MAY JUNE JULY AUG SEP OCT NOV DEC kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.50 0.45 0.44 0.54 0.58 0.63 0.54 0.43 0.57 0.70 0.69 0.71 0.54 7.50 0.65 0.59 0.66 0.61 0.63 0.55 0.48 0.60 0.73 0.71 0.75 0.65 8.50 0.85 0.74 0.77 0.64 0.64 0.56 0.54 0.62 0.75 0.74 0.78 0.76 9.50 1.06 0.94 0.99 0.79 0.77 0.73 0.68 0.77 0.89 0.95 0.93 0.95
10.50 1.04 0.96 0.97 0.81 0.79 0.75 0.70 0.78 0.89 0.93 0.94 0.97 11.50 1.01 0.98 0.95 0.82 0.80 0.78 0.73 0.79 0.88 0.91 0.95 0.99 12.50 1.04 1.00 0.96 0.84 0.80 0.79 0.73 0.83 0.90 0.92 0.96 0.97 13.50 1.00 0.99 0.96 0.82 0.79 0.75 0.71 0.82 0.88 0.91 0.98 0.97 14.50 0.97 0.99 0.96 0.81 0.79 0.72 0.69 0.81 0.87 0.90 0.99 0.97 15.50 0.82 0.83 0.75 0.63 0.68 0.58 0.50 0.66 0.75 0.77 0.85 0.84 16.50 0.79 0.78 0.72 0.60 0.62 0.55 0.47 0.64 0.73 0.66 0.68 0.71 17.50 0.76 0.74 0.68 0.56 0.56 0.51 0.44 0.62 0.71 0.56 0.52 0.58 18.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 19.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 20.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 21.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 22.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
23.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Main Report Final Master Thesis
Table B.8 Global Solar radiation incident on PV Array Daily Profile without tracking system for
Degehabur town
Timein
Hours JAN FEB MAR APR MAY JUNE JULY AUG SEP OCT NOV DEC kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
0.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.50 0.16 0.14 0.13 0.14 0.15 0.13 0.10 0.12 0.16 0.19 0.20 0.17 7.50 0.30 0.27 0.28 0.27 0.27 0.24 0.22 0.25 0.31 0.33 0.34 0.30 8.50 0.43 0.40 0.43 0.40 0.40 0.35 0.33 0.38 0.45 0.47 0.48 0.43 9.50 0.79 0.73 0.79 0.67 0.64 0.59 0.56 0.64 0.75 0.80 0.77 0.74
10.50 0.86 0.82 0.86 0.73 0.70 0.65 0.62 0.70 0.81 0.84 0.83 0.82 11.50 0.92 0.92 0.92 0.80 0.75 0.72 0.68 0.76 0.87 0.88 0.89 0.90 12.50 0.96 0.96 0.95 0.82 0.76 0.73 0.70 0.80 0.88 0.88 0.89 0.88 13.50 0.88 0.91 0.89 0.76 0.70 0.67 0.65 0.75 0.81 0.81 0.83 0.82 14.50 0.80 0.85 0.83 0.70 0.65 0.60 0.60 0.70 0.75 0.74 0.77 0.75 15.50 0.50 0.54 0.50 0.43 0.42 0.38 0.36 0.44 0.47 0.44 0.45 0.46 16.50 0.36 0.38 0.36 0.30 0.28 0.27 0.26 0.31 0.32 0.29 0.30 0.32 17.50 0.22 0.23 0.22 0.17 0.15 0.15 0.15 0.19 0.18 0.15 0.16 0.18 18.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 19.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 20.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 21.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 22.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
23.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Main Report Final Master Thesis
Table B.9 Global Solar radiation incident on PV Array Daily Profile without tracking system for
Kebridehar town
JAN FEB MAR APR MAY JUNE JULY AUG SEP OCT NOV DEC
Timein
Hours kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
0.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.50 0.15 0.14 0.13 0.14 0.15 0.13 0.11 0.13 0.17 0.17 0.20 0.17 7.50 0.29 0.28 0.28 0.27 0.26 0.24 0.22 0.25 0.31 0.30 0.33 0.31 8.50 0.43 0.42 0.43 0.40 0.38 0.35 0.33 0.37 0.45 0.43 0.46 0.44 9.50 0.77 0.76 0.79 0.65 0.60 0.59 0.56 0.62 0.74 0.74 0.73 0.74
10.50 0.83 0.85 0.85 0.72 0.65 0.65 0.62 0.67 0.79 0.78 0.79 0.82 11.50 0.89 0.94 0.91 0.78 0.70 0.72 0.68 0.73 0.85 0.81 0.85 0.90 12.50 0.92 0.99 0.93 0.80 0.71 0.73 0.69 0.77 0.85 0.81 0.85 0.87 13.50 0.84 0.93 0.87 0.74 0.66 0.66 0.64 0.72 0.79 0.74 0.79 0.81 14.50 0.76 0.87 0.82 0.68 0.61 0.59 0.59 0.67 0.72 0.67 0.73 0.74 15.50 0.47 0.55 0.48 0.41 0.39 0.37 0.35 0.41 0.45 0.39 0.42 0.45 16.50 0.34 0.39 0.34 0.28 0.26 0.26 0.25 0.29 0.30 0.26 0.28 0.31 17.50 0.20 0.23 0.20 0.16 0.13 0.14 0.15 0.17 0.16 0.12 0.14 0.17 18.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 19.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 20.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 21.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 22.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
23.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Main Report Final Master Thesis
Table B.10 Global Solar radiation incident on PV Array Daily Profile with tracking system for
Kebridehar town
JAN FEB MAR APRI
L MAY JUNE JULY AUG SEP OCT NOV DEC
Timein
Hours kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
kW/m2
0.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.50 0.48 0.52 0.56 0.56 0.56 0.54 0.43 0.54 0.68 0.56 0.70 0.59 7.50 0.64 0.66 0.66 0.58 0.57 0.55 0.49 0.57 0.71 0.60 0.71 0.68 8.50 0.80 0.80 0.76 0.61 0.58 0.56 0.54 0.59 0.73 0.64 0.72 0.76 9.50 1.02 0.98 0.97 0.76 0.71 0.73 0.68 0.74 0.87 0.86 0.87 0.95
10.50 1.00 0.99 0.95 0.78 0.73 0.75 0.70 0.75 0.86 0.84 0.89 0.96 11.50 0.98 1.01 0.94 0.80 0.74 0.78 0.73 0.76 0.86 0.82 0.90 0.98 12.50 1.00 1.02 0.94 0.82 0.75 0.78 0.73 0.80 0.87 0.83 0.91 0.96 13.50 0.96 1.02 0.94 0.80 0.74 0.75 0.71 0.79 0.86 0.82 0.92 0.96 14.50 0.93 1.02 0.94 0.78 0.73 0.72 0.69 0.77 0.85 0.80 0.93 0.96 15.50 0.77 0.87 0.73 0.60 0.62 0.58 0.49 0.61 0.71 0.66 0.80 0.83 16.50 0.73 0.83 0.70 0.57 0.56 0.54 0.46 0.59 0.69 0.56 0.64 0.70 17.50 0.70 0.79 0.66 0.54 0.51 0.51 0.44 0.57 0.66 0.45 0.48 0.57 18.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 19.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 20.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 21.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 22.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
23.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Ma
in R
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JAN
FE
B M
AR
APR
M
AY
JUN
E JU
LY
AU
G
SEP
OCT
N
OV
DEC
in
Hou
rs
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
0.50
41
.81
60.6
8 27
.61
8.58
22
.19
75.2
4 13
1.40
11
8.42
50
.73
18.4
3 28
.16
42.4
3 1.
50
40.9
5 51
.31
29.9
8 8.
58
21.1
5 74
.58
126.
93
114.
62
48.6
5 17
.66
29.1
9 38
.70
2.50
40
.08
41.9
4 32
.35
8.58
20
.11
73.9
3 12
2.45
11
0.83
46
.58
16.9
0 30
.21
34.9
8 3.
50
44.6
2 46
.36
30.4
1 9.
67
21.6
6 92
.09
106.
82
97.4
8 48
.41
17.5
3 27
.28
37.4
4 4.
50
45.3
1 43
.05
28.4
8 10
.22
22.1
8 10
3.31
11
3.57
10
4.01
46
.10
18.7
6 28
.13
38.7
4 5.
50
46.0
1 39
.73
26.5
5 10
.77
22.7
0 11
4.52
12
0.32
11
0.55
43
.79
20.0
0 28
.98
40.0
3 6.
50
48.8
4 47
.24
32.7
4 12
.22
30.4
6 15
3.01
15
2.17
16
2.64
45
.90
29.5
7 24
.48
80.3
0 7.
50
56.1
4 55
.73
33.4
7 14
.56
38.2
3 16
9.02
17
0.84
17
3.71
51
.68
31.7
6 30
.77
88.3
5 8.
50
63.4
5 64
.22
34.2
1 16
.91
46.0
0 18
5.04
18
9.50
18
4.78
57
.46
33.9
5 37
.06
96.4
0 9.
50
113.
14
104.
24
53.2
7 24
.50
65.3
7 19
5.60
24
2.74
17
9.04
89
.41
31.8
1 51
.71
108.
08
10.5
0 12
3.78
11
3.74
58
.17
27.1
2 75
.09
206.
78
255.
38
181.
17
107.
04
31.0
2 57
.35
123.
05
11.5
0 13
4.43
12
3.24
63
.08
29.7
3 84
.82
217.
96
268.
02
183.
29
124.
67
30.2
3 62
.98
138.
02
12.5
0 18
4.99
13
1.75
67
.76
40.3
4 85
.86
256.
62
276.
18
206.
74
142.
95
41.1
7 93
.10
137.
04
13.5
0 19
4.39
13
1.75
72
.32
38.8
9 83
.69
254.
00
276.
75
214.
71
149.
95
44.7
0 94
.31
125.
98
14.5
0 20
3.80
13
1.75
76
.88
37.4
5 81
.53
251.
38
277.
31
222.
69
156.
95
48.2
3 95
.52
114.
92
15.5
0 17
4.11
11
3.86
80
.37
36.5
6 84
.10
250.
35
250.
82
202.
96
164.
51
50.6
1 10
3.56
11
3.71
16
.50
165.
38
121.
02
76.7
9 34
.14
85.2
7 24
5.17
23
8.84
19
9.57
15
2.92
47
.25
100.
34
117.
45
17.5
0 15
6.64
12
8.17
73
.22
31.7
3 86
.44
240.
00
226.
86
196.
17
141.
34
43.9
0 97
.11
121.
19
18.5
0 13
1.23
10
2.61
62
.06
26.0
9 76
.14
202.
32
215.
00
199.
13
120.
35
36.8
9 87
.29
111.
72
19.5
0 11
6.11
93
.65
62.3
3 24
.54
63.8
2 19
9.70
19
9.34
19
6.97
11
5.79
34
.49
74.5
9 10
5.16
20
.50
100.
99
84.6
9 62
.61
23.0
0 51
.51
197.
07
183.
68
194.
82
111.
23
32.1
0 61
.89
98.6
0 21
.50
65.1
0 72
.44
35.9
6 13
.99
32.3
3 14
5.17
15
8.84
14
9.39
98
.93
24.1
5 46
.35
80.9
7 22
.50
61.0
2 63
.30
35.8
3 12
.07
29.2
8 13
0.94
13
9.21
13
7.88
88
.34
22.3
1 40
.71
70.5
5
23.5
0 56
.95
54.1
6 35
.70
10.1
6 26
.24
116.
71
119.
57
126.
38
77.7
5 20
.47
35.0
7 60
.12
Ma
in R
ep
ort
Fin
al M
aste
r T
he
sis
T
ab
le C
.2 W
ind
tu
rbin
e p
ow
er o
utp
ut
da
ily p
rofi
le K
ebri
deh
ar
tow
n
Tim
e
JAN
FE
B M
AR
APR
M
AY
JUN
E JU
LY
AU
G
SEP
OCT
N
OV
D
EC
in H
ours
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
0.50
36
.73
54.9
6 23
.40
8.54
37
.53
85.2
3 12
5.77
11
2.01
61
.82
19.1
2 14
.02
32.9
9 1.
50
36.0
1 46
.91
25.3
5 8.
45
35.9
6 85
.15
122.
95
109.
88
59.1
0 18
.42
14.4
2 30
.53
2.50
35
.30
38.8
6 27
.30
8.37
34
.40
85.0
6 12
0.14
10
7.76
56
.38
17.7
2 14
.82
28.0
7 3.
50
39.2
3 42
.18
25.6
2 9.
51
37.1
4 98
.09
104.
97
103.
41
58.9
1 18
.21
13.5
2 29
.80
4.50
39
.52
39.7
0 24
.09
10.0
3 37
.79
105.
89
109.
81
110.
44
56.4
2 19
.57
13.9
4 30
.39
5.50
39
.81
37.2
2 22
.56
10.5
5 38
.45
113.
69
114.
66
117.
47
53.9
2 20
.93
14.3
6 30
.98
6.50
43
.06
43.6
4 27
.82
12.0
3 51
.47
157.
51
149.
06
162.
90
56.1
6 29
.85
12.6
7 61
.47
7.50
49
.87
51.7
4 28
.46
14.2
8 63
.71
168.
08
164.
62
172.
07
62.7
5 32
.39
15.6
5 68
.36
8.50
56
.69
59.8
5 29
.10
16.5
3 75
.96
178.
64
180.
18
181.
24
69.3
3 34
.92
18.6
4 75
.24
9.50
98
.15
94.6
0 45
.23
23.2
5 99
.96
186.
34
217.
98
175.
73
103.
87
33.3
5 26
.75
84.0
5 10
.50
107.
53
103.
54
49.5
7 25
.94
113.
26
201.
74
225.
45
182.
17
122.
25
32.6
8 29
.68
95.5
0 11
.50
116.
92
112.
48
53.9
2 28
.62
126.
57
217.
13
232.
92
188.
61
140.
63
32.0
1 32
.60
106.
96
12.5
0 15
8.60
12
0.21
58
.98
38.3
9 12
7.15
24
7.36
24
0.53
20
5.36
15
3.68
42
.89
48.3
4 10
6.27
13
.50
166.
21
120.
80
62.6
2 37
.15
126.
07
242.
47
247.
36
212.
01
160.
32
46.3
6 48
.95
98.6
1 14
.50
173.
82
121.
38
66.2
6 35
.92
124.
99
237.
58
254.
19
218.
66
166.
96
49.8
3 49
.56
90.9
6 15
.50
150.
63
105.
58
69.0
9 35
.46
125.
64
239.
14
234.
66
201.
99
178.
10
52.7
9 55
.23
89.5
0 16
.50
143.
15
112.
69
65.9
8 33
.14
130.
02
232.
66
226.
53
198.
68
166.
88
49.5
3 52
.30
91.9
0 17
.50
135.
66
119.
80
62.8
7 30
.82
134.
40
226.
18
218.
40
195.
36
155.
66
46.2
8 49
.38
94.2
9 18
.50
115.
98
94.7
4 52
.36
25.2
4 12
4.32
19
7.34
19
7.57
19
2.46
13
5.00
38
.40
44.8
3 87
.60
19.5
0 10
2.28
86
.46
52.2
8 23
.60
104.
88
195.
94
189.
52
187.
43
129.
55
35.9
1 37
.97
82.3
8 20
.50
88.5
8 78
.17
52.2
0 21
.97
85.4
5 19
4.55
18
1.46
18
2.41
12
4.09
33
.41
31.1
1 77
.15
21.5
0 56
.36
65.0
3 31
.04
13.7
7 55
.12
155.
26
153.
25
143.
14
115.
40
24.5
6 23
.61
62.5
4 22
.50
52.8
2 57
.83
30.5
8 11
.87
49.9
5 13
9.38
13
7.20
13
4.47
10
4.16
22
.82
20.5
8 54
.22
23.5
0 49
.29
50.6
2 30
.12
9.97
44
.77
123.
50
121.
16
125.
80
92.9
3 21
.09
17.5
6 45
.90
Ma
in R
ep
ort
Fin
al M
aste
r T
he
sis
T
ab
le C
.3 P
V A
rra
y p
ow
er
ou
tpu
t d
ail
y p
rofi
le f
or
Ke
bri
de
ha
r to
wn
Tim
e
JAN
FE
B M
AR
APR
M
AY
JUN
E JU
LY
AU
G
SEP
OCT
N
OV
D
EC
in H
ours
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
0.50
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
1.
50
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
2.50
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
3.
50
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
4.50
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
5.
50
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
6.50
20
7.44
22
0.82
23
3.95
23
3.51
23
4.93
22
8.27
18
6.88
23
1.59
28
4.02
23
7.61
29
1.01
25
0.21
7.
50
268.
40
273.
77
271.
42
244.
82
239.
16
232.
63
208.
60
240.
82
293.
65
253.
84
295.
38
281.
43
8.50
32
9.36
32
6.72
30
8.88
25
6.12
24
3.39
23
7.00
23
0.32
25
0.05
30
3.28
27
0.07
29
9.75
31
2.65
9.
50
407.
78
392.
05
388.
99
314.
86
296.
66
306.
49
286.
79
309.
19
355.
27
354.
51
354.
73
381.
65
10.5
0 40
0.50
39
7.15
38
2.70
32
2.81
30
2.46
31
5.58
29
6.64
31
3.57
35
4.05
34
8.70
36
1.14
38
9.25
11
.50
393.
23
402.
25
376.
40
330.
77
308.
26
324.
68
306.
48
317.
95
352.
82
342.
88
367.
55
396.
85
12.5
0 40
0.38
40
9.29
37
8.12
33
5.68
31
1.22
32
9.36
30
9.49
33
3.00
35
7.07
34
6.67
37
1.49
38
7.49
13
.50
386.
58
408.
53
377.
48
328.
89
306.
85
316.
19
301.
03
328.
20
352.
15
339.
85
375.
02
386.
84
14.5
0 37
2.78
40
7.76
37
6.83
32
2.11
30
2.47
30
3.02
29
2.57
32
3.40
34
7.23
33
3.03
37
8.54
38
6.18
15
.50
313.
90
352.
53
297.
60
251.
33
261.
40
245.
89
211.
41
260.
63
295.
74
278.
33
328.
43
341.
06
16.5
0 30
1.17
33
6.87
28
4.41
23
8.49
23
7.18
23
2.47
19
9.18
25
2.43
28
6.04
23
7.11
26
6.79
29
1.42
17
.50
288.
44
321.
20
271.
22
225.
65
212.
97
219.
04
186.
94
244.
24
276.
34
195.
89
205.
14
241.
77
18.5
0 0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
19
.50
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
20.5
0 0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
21
.50
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
22.5
0 0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
23.5
0 0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
Ma
in R
ep
ort
Fin
al M
aste
r T
he
sis
Ta
ble
C.4
PV
Arr
ay
po
wer
ou
tpu
t d
ail
y p
rofi
le f
or
D t
ow
n
Tim
e
JAN
FE
B M
AR
APR
M
AY
JUN
E JU
LY
AU
G
SEP
OCT
N
OV
D
EC
in
Hou
rs
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
0.50
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
1.
50
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
2.50
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
3.
50
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
4.50
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
5.
50
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
6.50
23
1.58
22
7.05
26
9.83
28
5.58
31
3.52
27
1.45
22
0.45
28
5.21
34
3.83
33
7.03
35
1.28
27
1.45
7.
50
323.
55
295.
08
322.
21
300.
46
315.
30
276.
11
247.
11
298.
16
356.
50
349.
72
367.
32
322.
53
8.50
41
5.51
36
3.10
37
4.59
31
5.33
31
7.07
28
0.78
27
3.77
31
1.12
36
9.16
36
2.42
38
3.37
37
3.60
9.
50
504.
00
450.
65
470.
09
384.
27
381.
57
363.
00
341.
18
380.
64
431.
23
455.
79
445.
59
458.
21
10.5
0 49
4.13
45
8.54
46
2.24
39
2.95
38
7.16
37
3.74
35
2.98
38
4.89
42
9.57
44
7.06
45
1.69
46
7.21
11
.50
484.
26
466.
43
454.
39
401.
64
392.
75
384.
49
364.
78
389.
14
427.
92
438.
33
457.
79
476.
21
12.5
0 49
4.66
47
5.85
45
6.44
40
7.52
39
4.22
39
0.56
36
9.13
40
6.09
43
3.29
44
3.61
46
4.99
46
5.12
13
.50
479.
61
473.
66
455.
90
400.
69
390.
34
375.
19
359.
21
401.
65
428.
20
439.
96
469.
23
464.
21
14.5
0 46
4.55
47
1.47
45
5.37
39
3.87
38
6.47
35
9.81
34
9.30
39
7.21
42
3.11
43
6.30
47
3.48
46
3.30
15
.50
397.
96
401.
81
363.
91
312.
54
338.
28
293.
99
254.
42
326.
73
366.
32
375.
45
411.
31
410.
05
16.5
0 38
3.99
38
0.58
34
8.02
29
5.85
30
7.98
27
6.22
23
8.57
31
7.81
35
7.24
32
7.36
33
6.85
35
0.77
17
.50
370.
03
359.
34
332.
14
279.
16
277.
68
258.
45
222.
73
308.
90
348.
16
279.
28
262.
39
291.
49
18.5
0 0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
19
.50
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
20.5
0 0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
21
.50
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
22.5
0 0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
23.5
0 0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
0.
00
0.00
Ma
in R
ep
ort
Fin
al M
aste
r T
he
sis
Tab
le C
.5 I
nver
ter
ou
tpu
t p
ow
er d
ail
y p
rofi
les
for
Deg
ehab
ur
tow
n
Tim
e
JAN
FE
B M
AR
APR
M
AY
JUN
E JU
LY
AU
G
SEP
OCT
N
OV
DEC
in
H
ours
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
0.5
104.
27
96.3
7 10
9.47
51
.2
64.1
4 85
.62
61.2
8 79
.92
98.3
9 80
.46
111.
82
106.
41
1.5
105.
33
101.
17
107.
11
43.7
1 62
.67
87.7
9 63
.54
79.2
2 99
.91
74.7
7 11
2.23
10
7.99
2.
5 10
6.39
10
5.97
10
4.74
36
.22
61.1
9 89
.97
65.7
9 78
.51
101.
43
69.0
8 11
2.64
10
9.57
3.
5 10
7.84
10
1.74
10
6.91
10
.75
58.2
4 85
.79
77.6
1 76
.07
102.
37
54.3
6 10
5.81
10
3.73
4.
5 10
9.91
10
4.14
10
6.38
8.
31
56.5
9 81
.37
77.6
8 73
.21
103.
28
48.3
8 94
.99
102.
33
5.5
111.
98
106.
55
105.
86
5.86
54
.93
76.9
5 77
.76
70.3
5 10
4.19
42
.4
84.1
6 10
0.94
6.
5 18
7.68
18
3.92
20
7.3
206.
85
208.
58
107.
4 95
.47
97.5
6 19
9.6
210.
69
217.
66
169.
87
7.5
166.
49
166.
13
184.
8 19
2.29
18
2.06
92
.71
87.7
9 83
.52
168.
46
186.
09
185.
72
144.
35
8.5
145.
30
148.
35
162.
29
177.
73
155.
54
78.0
1 80
.1
69.4
8 13
7.32
16
1.5
153.
78
118.
83
9.5
106.
07
127.
07
160.
12
181.
33
149.
62
88.8
6 69
.61
87.2
7 12
5.03
17
2.57
15
1.59
11
2.60
10
.5
99.5
0 11
4.06
14
9.37
17
1.14
13
5.49
70
.18
65.2
4 75
.89
113.
15
168.
24
144.
25
102.
34
11.5
92
.94
101.
06
138.
61
160.
94
121.
36
51.5
1 60
.87
64.5
1 10
1.27
16
3.92
13
6.91
92
.08
12.5
72
.12
101.
62
149.
23
166.
21
133.
94
50.5
7 51
.08
74.2
8 10
2.14
17
1.33
13
2.53
10
5.47
13
.5
69.5
5 10
2.78
14
6.94
17
1.14
13
4.13
50
.77
47.5
9 71
.18
97.7
7 16
9.05
13
1.23
11
3.00
14
.5
66.9
8 10
3.94
14
4.65
17
6.06
13
4.32
50
.98
44.1
68
.09
93.4
1 16
6.76
12
9.92
12
0.53
15
.5
94.5
3 13
8.33
16
0.98
19
2.95
15
2.41
66
.47
65.7
4 87
.75
109.
86
188.
9 14
6.3
137.
50
16.5
12
1.54
15
3.68
18
7.05
21
6.36
17
1.08
86
.74
84.8
8 10
8.62
13
6.78
21
5.98
16
9.59
15
6.73
17
.5
148.
55
169.
04
213.
12
239.
77
189.
76
107.
01
104.
02
129.
49
163.
71
243.
06
192.
87
175.
95
18.5
20
6.91
23
7.29
25
7.64
26
7.96
23
1.04
16
3.32
15
8.1
164.
23
221.
26
273.
11
250.
88
228.
91
19.5
21
3.31
23
4.53
25
0.5
234.
97
219.
31
155.
06
153.
27
159.
78
215.
39
266.
14
250.
63
225.
26
20.5
21
9.71
23
1.77
24
3.35
20
1.98
20
7.59
14
6.8
148.
44
155.
33
209.
53
259.
17
250.
39
221.
61
21.5
22
1.99
21
7.47
23
1.45
13
7.6
185.
93
153.
27
149.
07
163.
54
186.
61
223.
33
236.
99
208.
17
22.5
19
2.16
19
0.78
19
9.79
11
1.46
15
0.75
13
6.91
13
1.82
14
3.74
16
4.4
190.
35
208.
48
186.
77
23.5
16
2.33
16
4.09
16
8.13
85
.33
115.
57
120.
55
114.
56
123.
94
142.
19
157.
37
179.
97
165.
36
Ma
in R
ep
ort
Fin
al M
aste
r T
he
sis
T
ab
le C
.6 I
nv
erte
r ou
tpu
t p
ow
er d
ail
y p
rofi
les
for
Keb
rid
ehar
tow
n
Tim
e
JAN
FE
B M
AR
APR
M
AY
JUN
E JU
LY
AU
G
SEP
OCT
N
OV
D
EC
in
Hou
rs
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
kW
0.5
103.
34
93.9
7 11
3.97
51
.38
94.6
3 76
.83
55.9
1 72
.36
86.5
0 77
.43
85.7
8 10
3.04
1.
5 10
4.38
98
.30
112.
29
49.3
4 94
.03
78.1
5 57
.68
72.4
3 88
.31
69.7
7 82
.57
104.
00
2.5
105.
43
102.
63
110.
61
47.2
9 93
.44
79.4
7 59
.46
72.5
1 90
.11
62.1
0 79
.37
104.
96
3.5
106.
38
99.1
5 10
9.66
28
.85
87.4
3 75
.53
71.1
5 68
.99
89.8
2 53
.27
69.5
5 10
4.25
4.
5 10
7.91
10
1.37
10
9.85
18
.46
83.9
8 71
.53
71.5
1 65
.73
91.1
5 48
.89
61.8
2 10
2.27
5.
5 10
9.45
10
3.59
11
0.04
8.
08
80.5
4 67
.54
71.8
8 62
.46
92.4
8 44
.52
54.0
9 10
0.28
6.
5 13
2.33
10
8.31
11
7.20
11
2.58
98
.47
87.3
5 80
.75
75.7
3 13
5.66
10
5.22
11
9.73
95
.16
7.5
115.
89
103.
02
118.
59
117.
84
92.6
4 74
.44
71.8
7 65
.37
117.
87
108.
30
123.
04
92.9
2 8.
5 99
.44
97.7
2 11
9.98
12
3.10
86
.81
61.5
4 62
.99
55.0
2 10
0.09
11
1.38
12
6.35
90
.68
9.5
92.0
2 96
.65
123.
73
139.
14
86.8
4 71
.43
58.9
0 67
.22
94.3
5 13
3.34
13
6.96
90
.90
10.5
97
.17
100.
08
134.
10
150.
76
92.6
4 62
.00
60.3
7 66
.75
93.9
5 14
7.94
14
8.64
95
.73
11.5
10
2.33
10
3.52
14
4.47
16
2.39
98
.43
52.5
7 61
.85
66.2
9 93
.56
162.
53
160.
33
100.
56
12.5
72
.62
94.2
6 14
4.39
15
4.68
97
.08
43.7
4 53
.22
64.4
5 80
.65
155.
88
151.
97
109.
96
13.5
76
.86
103.
31
151.
51
167.
86
104.
14
47.0
0 50
.29
67.3
9 85
.36
162.
30
159.
89
125.
94
14.5
81
.09
112.
36
158.
63
181.
03
111.
20
50.2
6 47
.36
70.3
3 90
.07
168.
72
167.
82
141.
92
15.5
90
.25
121.
78
149.
01
174.
92
108.
77
50.9
8 54
.35
69.7
8 86
.48
160.
26
157.
88
134.
91
16.5
98
.16
118.
45
154.
01
177.
18
107.
52
56.5
5 58
.96
74.4
7 93
.83
165.
79
160.
86
134.
53
17.5
10
6.07
11
5.12
15
9.02
17
9.44
10
6.27
62
.11
63.5
7 79
.17
101.
18
171.
32
163.
84
134.
15
18.5
17
4.02
20
0.93
22
9.97
23
5.81
16
1.35
11
5.75
11
9.59
12
1.68
16
5.11
23
6.32
22
7.76
20
5.47
19
.5
174.
47
191.
69
214.
72
202.
54
161.
03
106.
58
109.
61
116.
68
155.
85
216.
46
212.
08
194.
94
20.5
17
4.93
18
2.45
19
9.47
16
9.28
16
0.72
97
.41
99.6
3 11
1.68
14
6.59
19
6.60
19
6.40
18
4.42
21
.5
173.
56
167.
54
188.
80
114.
53
158.
12
99.2
1 10
2.10
11
2.71
12
7.53
16
9.90
17
4.79
16
7.19
22
.5
159.
36
155.
84
173.
37
100.
37
147.
17
96.6
8 96
.40
107.
97
118.
77
150.
07
155.
34
159.
50
23.5
14
5.17
14
4.13
15
7.93
86
.22
136.
21
94.1
5 90
.70
103.
23
110.
01
130.
25
135.
88
151.
81
Main Report Final Master Thesis
Appendix D: Kyocera Photovoltaic modules technical specification
Main Report Final Master Thesis
Main Report Final Master Thesis
Appendix E: HOMER Input Summary
HOMER Input Summary for Degehabur town
File name: Degehabur town final runFile version: 2.68 beta Author: Bizuayehu Tesfaye
AC Load: Primary Load 1
Data source: Synthetic Daily noise: 0% Hourly noise: 0% Scaled annual average: 5,001 kWh/dScaled peak load: 343 kW Load factor: 0.608
AC Deferrable Load
Month Average Load
(kWh/d)Jan 500 Feb 500 Mar 500 Apr 500 May 500 Jun 500 Jul 500 Aug 500 Sep 500 Oct 500 Nov 500 Dec 500
Main Report Final Master Thesis
Scaled annual average: 300 kWh/dStorage capacity: 500 kWh Peak load: 150 kW Min. load ratio: 0.9%
PV
Size (kW) Capital ($) Replacement ($) O&M ($/yr)
1.000 6,000 5,000 52.000 12,000 10,000 103.000 18,000 15,000 15
Sizes to consider: 0, 600, 650, 700, 750, 800, 900, 1,200 kWLifetime: 25 yr Derating factor: 80% Tracking system: Two Axis Slope: 8.22 deg Azimuth: 0 deg Ground reflectance: 20%
Solar Resource
Latitude: 8 degrees 13 minutes NorthLongitude: 43 degrees 34 minutes EastTime zone: GMT +3:00
Data source: Synthetic
Month Clearness Index Average Radiation
(kWh/m2/day) Jan 0.719 6.557Feb 0.693 6.748Mar 0.682 7.024Apr 0.600 6.290May 0.597 6.154Jun 0.571 5.778Jul 0.538 5.467Aug 0.602 6.223Sep 0.655 6.748Oct 0.667 6.574Nov 0.694 6.399Dec 0.694 6.159
Main Report Final Master Thesis
Scaled annual average: 6.34 kWh/m²/d
AC Wind Turbine: Elotec
Quantity Capital ($) Replacement ($) O&M ($/yr)
1 97,500 83,850 1,9502 195,000 167,700 3,900
Quantities to consider: 0, 2, 3, 4, 5, 7, 8, 9, 10, 15, 20, 25, 30, 32, 35, 38, 40 Lifetime: 25 yr Hub height: 40 m
Wind Resource
Data source: Synthetic
Month Wind Speed
(m/s) Jan 5.75 Feb 5.39 Mar 4.51 Apr 3.43 May 4.59 Jun 7.27 Jul 7.64 Aug 7.11 Sep 5.64 Oct 3.88
Main Report Final Master Thesis
Nov 4.71 Dec 5.49
Weibull k: 2.00 Autocorrelation factor: 0.850 Diurnal pattern strength: 0.250 Hour of peak wind speed: 15 Scaled annual average: 5.45 m/s Anemometer height: 50 m Altitude: 1,095 m Wind shear profile: LogarithmicSurface roughness length: 0.01 m
AC Generator: Diesel Generator
Size (kW) Capital ($) Replacement ($) O&M ($/hr)
30.000 0 15,000 1.500100.000 0 50,000 5.000400.000 0 200,000 20.000
Sizes to consider: 0, 400 kW Lifetime: 15,000 hrs Min. load ratio: 40% Heat recovery ratio: 0% Fuel used: Diesel Fuel curve intercept: 0.08 L/hr/kWFuel curve slope: 0.25 L/hr/kW
Main Report Final Master Thesis
Fuel: Diesel
Price: $ 1/L Lower heating value: 43.2 MJ/kg Density: 820 kg/m3 Carbon content: 88.0% Sulfur content: 0.330%
Battery: Surrette 4KS25P
Quantity Capital ($) Replacement ($) O&M ($/yr)
1 1,700 1,500 10.002 3,500 3,100 20.00
700 1,260,000 1,120,000 7,000.00Quantities to consider: 0, 2,300, 2,500, 3,000, 3,500Voltage: 4 V Nominal capacity: 1,900 Ah Lifetime throughput: 10,569 kWh
Converter
Size (kW) Capital ($) Replacement ($) O&M ($/yr)
10.000 9,000 9,000 90100.000 90,000 90,000 900300.000 270,000 270,000 2,700400.000 360,000 360,000 3,600
Sizes to consider: 0, 10, 100, 300, 400, 500, 600, 700 kW Lifetime: 15 yr Inverter efficiency: 90% Inverter can parallel with AC generator: Yes Rectifier relative capacity: 100% Rectifier efficiency: 85%
Grid Extension
Capital cost: $ 125,000/km O&M cost: $ 2,500/yr/km Power price: $ 0/kWh
Economics
Main Report Final Master Thesis
Annual real interest rate: 4% Project lifetime: 25 yr Capacity shortage penalty: $ 0/kWhSystem fixed capital cost: $ 0 System fixed O&M cost: $ 0/yr
Generator control
Check load following: Yes Check cycle charging: Yes Setpoint state of charge: 80% Allow systems with multiple generators: YesAllow multiple generators to operate simultaneously: YesAllow systems with generator capacity less than peak load: Yes
Emissions
Carbon dioxide penalty: $ 0/tCarbon monoxide penalty: $ 0/tUnburned hydrocarbons penalty: $ 0/tParticulate matter penalty: $ 0/tSulfur dioxide penalty: $ 0/tNitrogen oxides penalty: $ 0/t
Constraints
Maximum annual capacity shortage: 5%Minimum renewable fraction: 0%Operating reserve as percentage of hourly load: 0%Operating reserve as percentage of peak load: 0%Operating reserve as percentage of solar power output: 5%Operating reserve as percentage of wind power output: 5%
HOMER Input Summary for Kebridehar town
File name: Keberdehar final run.hmrFile version: 2.68 beta Author:
AC Load: Primary Load 1
Main Report Final Master Thesis
Data source: Synthetic Daily noise: 0% Hourly noise: 0% Scaled annual average: 4,565 kWh/dScaled peak load: 290 kW Load factor: 0.656
AC Deferrable Load
Month Average Load
(kWh/d)Jan 120 Feb 0 Mar 0 Apr 0 May 0 Jun 400 Jul 400 Aug 400 Sep 200 Oct 0 Nov 0 Dec 0 Scaled annual average: 100 kWh/dStorage capacity: 300 kWh Peak load: 100 kW Min. load ratio: 0.9%
PV
Size (kW) Capital ($) Replacement ($) O&M ($/yr)
1.000 6,000 5,000 52.000 12,000 10,000 10
Main Report Final Master Thesis
3.000 18,000 15,000 15Sizes to consider: 0, 530, 550, 600, 650, 750, 800, 900, 1,000 kWLifetime: 25 yr Derating factor: 80% Tracking system: Two Axis Slope: 6.75 deg Azimuth: 0 deg Ground reflectance: 20%
Solar Resource
Latitude: 6 degrees 45 minutes NorthLongitude: 44 degrees 17 minutes EastTime zone: GMT +3:00
Data source: Synthetic
Month Clearness Index Average Radiation
(kWh/m2/day) Jan 0.693 6.440Feb 0.712 7.027Mar 0.671 6.951Apr 0.585 6.108May 0.559 5.699Jun 0.571 5.697Jul 0.538 5.403Aug 0.577 5.938Sep 0.636 6.571Oct 0.608 6.049Nov 0.660 6.197Dec 0.687 6.232Scaled annual average: 6.19 kWh/m²/d
Main Report Final Master Thesis
AC Wind Turbine: Elotec
Quantity Capital ($) Replacement ($) O&M ($/yr)
1 97,500 83,850 1,9502 195,000 167,700 3,900
Quantities to consider: 0, 3, 5, 6, 10, 15, 20, 25, 30, 32, 33Lifetime: 25 yr Hub height: 40 m
Wind Resource
Data source: Synthetic
Month Wind Speed
(m/s) Jan 5.98 Feb 5.72 Mar 4.65 Apr 3.68 May 5.88 Jun 8.19 Jul 8.40 Aug 7.96 Sep 6.51 Oct 4.26 Nov 4.12 Dec 5.49
Main Report Final Master Thesis
Weibull k: 2.00 Autocorrelation factor: 0.850 Diurnal pattern strength: 0.250 Hour of peak wind speed: 15 Scaled annual average: 5.91 m/s Anemometer height: 50 m Altitude: 493 m Wind shear profile: LogarithmicSurface roughness length: 0.01 m
AC Generator: Generator 1
Size (kW) Capital ($) Replacement ($) O&M ($/hr)
30.000 0 15,000 1.500100.000 0 50,000 5.000375.000 0 187,500 18.750
Sizes to consider: 0, 375 kW Lifetime: 15,000 hrs Min. load ratio: 40% Heat recovery ratio: 0% Fuel used: Diesel Fuel curve intercept: 0.08 L/hr/kWFuel curve slope: 0.25 L/hr/kW
Fuel: Diesel
Main Report Final Master Thesis
Price: $ 1/L Lower heating value: 43.2 MJ/kg Density: 820 kg/m3 Carbon content: 88.0% Sulfur content: 0.330%
Battery: Surrette 4KS25P
Quantity Capital ($) Replacement ($) O&M ($/yr)
1 1,700 1,500 10.002 3,400 3,000 20.00
Quantities to consider: 0, 2,050, 2,500, 3,000, 3,500, 4,000Voltage: 4 V Nominal capacity: 1,900 Ah Lifetime throughput: 10,569 kWh Min battery life: 10 yr
Converter
Size (kW) Capital ($) Replacement ($) O&M ($/yr)
4.000 3,600 3,600 40Sizes to consider: 0, 4, 300, 400 kWLifetime: 15 yr Inverter efficiency: 95% Inverter can parallel with AC generator: Yes Rectifier relative capacity: 100% Rectifier efficiency: 90%
Grid Extension
Capital cost: $ 125,000/km O&M cost: $ 2,500/yr/km Power price: $ 0/kWh
Economics
Annual real interest rate: 4% Project lifetime: 25 yr Capacity shortage penalty: $ 0/kWhSystem fixed capital cost: $ 0 System fixed O&M cost: $ 0/yr
Main Report Final Master Thesis
Generator control
Check load following: Yes Check cycle charging: Yes Setpoint state of charge: 80% Allow systems with multiple generators: YesAllow multiple generators to operate simultaneously: YesAllow systems with generator capacity less than peak load: Yes
Emissions
Carbon dioxide penalty: $ 0/tCarbon monoxide penalty: $ 0/tUnburned hydrocarbons penalty: $ 0/tParticulate matter penalty: $ 0/tSulfur dioxide penalty: $ 0/tNitrogen oxides penalty: $ 0/t
Constraints
Maximum annual capacity shortage: 5%Minimum renewable fraction: 0%Operating reserve as percentage of hourly load: 0%Operating reserve as percentage of peak load: 0%Operating reserve as percentage of solar power output: 5%Operating reserve as percentage of wind power output: 5%
Bizuayehu Tesfaye
REYST report 05-2011
Bizuayehu Tesfaye Im
proved Sustainable Power Supply
RE
YS
T rep
ort 05-2011
Improved Sustainable Power Supplyfor Dagahabur and Kebridahar Town
of Somalia Region in Ethiopia
REYKJAVIK ENERGY GRADUATE SCHOOL OF SUSTAINABLE SYSTEMS
Reykjavík Energy Graduate School of Sustainable Systems (REYST) combines the expertise of its partners: Reykjavík Energy, Reykjavík University and the University of Iceland.
Objectives of REYST:Promote education and research in sustainable energy
earth sciences
REYST is an international graduate programme open for students holding BSc degrees in engineering, earth sciences or business.
REYST offers graduate level education with emphasis on practicality, innovation and interdisciplinary thinking.
REYST reports contain the master’s theses of REYST graduates who earn their degrees from the University of Iceland and Reykjavík University.