Socio-economic assessment and energy system
analysis
Deliverable nº: D6.1
July 2016
EC-GA nº: 308912 Project full title: Innovative Configuration for a Fully
Renewable Hybrid CSP Plant WP: 6 Responsible partner: DTU-ME Authors: Cristian Cabrera and Lars Henrik Nielsen Dissemination level: Public
D6.1: Socio-economic assessment and energy system analysis
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Table of contents
ACKNOWLEDGEMENTS .......................................................................................................... 7
CONTACT .............................................................................................................................. 8
1 EXECUTIVE SUMMARY ................................................................................................... 9
2 INTRODUCTION............................................................................................................ 11
3 SOCIO-ECONOMIC FEASIBILITY ASSESSMENT ................................................................ 12
3.1 FRAMEWORK CONDITIONS FOR THE COUNTRIES ANALYSED ...................................................... 12
3.2 THE HYSOL ALTERNATIVE AND COMPETING TECHNOLOGY ...................................................... 12
3.3 APPROACH AND BASIC ASSUMPTIONS .................................................................................. 12
3.3.1 Economic indicator ................................................................................... 12
3.3.2 Base Case assumptions ............................................................................. 13
3.3.3 Base Case overview and issues addressed via sensitivity analyses .......... 13
3.4 KSA............................................................................................................................... 14
3.4.1 Base Case for KSA HYSOL plant................................................................. 14
3.4.2 Electricity costs as function of load factor and NG price .......................... 14
3.4.3 Design Point assumptions ......................................................................... 15
3.4.4 HYSOL relative to OCGT and CCGT ........................................................... 15
3.4.5 CO2 emission costs .................................................................................... 15
3.4.6 Results: HYSOL compared to OCGT........................................................... 16
3.4.7 Results: HYSOL compared to CCGT ........................................................... 17
3.5 MEXICO ......................................................................................................................... 19
3.5.1 Base Case for MEX HYSOL plant ............................................................... 19
3.5.2 Assumption on NG and biogas price relation ........................................... 20
3.5.3 Results: HYSOL compared to OCGT........................................................... 20
3.5.4 Results: HYSOL compared to CCGT ........................................................... 23
3.6 CHILE ............................................................................................................................. 24
3.6.1 Base Case for CHI HYSOL plant ................................................................. 24
3.6.2 Assumption on NG and Biogas price relation ........................................... 25
3.6.3 Results: HYSOL compared to OCGT........................................................... 25
3.6.4 Results: HYSOL compared to CCGT ........................................................... 27
3.7 RSA .............................................................................................................................. 29
3.7.1 Base Case for RSA HYSOL plant ................................................................ 29
3.7.2 Assumption on NG and Biogas price relation ........................................... 30
3.7.3 Results: HYSOL compared to OCGT........................................................... 31
3.7.4 Results: HYSOL compared to CCGT ........................................................... 33
3.8 SENSITIVITY ANALYSES ...................................................................................................... 34
3.8.1 KSA ............................................................................................................ 34
3.8.2 Mexico ...................................................................................................... 36
D6.1: Socio-economic assessment and energy system analysis
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3.8.3 Chile .......................................................................................................... 37
3.8.4 RSA ............................................................................................................ 39
3.9 KEY FINDINGS .................................................................................................................. 41
4 ENERGY SYSTEMS ANALYSIS ......................................................................................... 42
4.1 OBJECTIVE ...................................................................................................................... 42
4.2 METHOD ........................................................................................................................ 42
4.3 ETSAP-TIAM ................................................................................................................. 43
4.3.1 Times Architecture Background ................................................................ 43
4.3.2 Regions ..................................................................................................... 43
4.3.3 Time Frame ............................................................................................... 44
4.3.4 Model Structure ........................................................................................ 44
4.4 SCENARIOS ..................................................................................................................... 44
4.4.1 Carbon Price .............................................................................................. 45
4.5 ENERGY SYSTEM ASSESSMENT ............................................................................................ 46
4.5.1 Availability of resources ............................................................................ 46
4.6 MODELLING .................................................................................................................... 49
4.6.1 CSP technology overview .......................................................................... 49
4.6.2 HYSOL implemented in ETSAP-TIAM......................................................... 49
4.7 RESULTS ......................................................................................................................... 50
4.7.1 Annual electricity production.................................................................... 50
4.7.2 Total system cost ...................................................................................... 53
4.7.3 Direct CO2 emissions ................................................................................. 54
4.8 KEY FINDINGS .................................................................................................................. 55
5 CONCLUSION ............................................................................................................... 56
6 REFERENCES ................................................................................................................. 57
7 APPENDIX .................................................................................................................... 60
7.1 SECTION A: ENERGY SYSTEM ANALYSIS ................................................................................ 60
7.1.1 Calibration of TIAM model........................................................................ 60
7.1.2 Model Structure ........................................................................................ 60
7.1.3 CO2 tax in ETSAP-TIAM ............................................................................. 62
7.1.4 Flow diagram in ETSAP -TIAM .................................................................. 63
7.2 SECTION B: SOCIO-ECONOMIC FEASIBILITY ASSESSMENT ......................................................... 64
7.2.1 Power price composition Mexico .............................................................. 65
7.2.2 Power price composition for Chile ........................................................... 67
7.2.3 Power price composition for KSA .............................................................. 68
7.2.4 Power price composition for RSA .............................................................. 69
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List of tables
Table 3.1: General assumptions .................................................................................................. 13
Table 3.2: Parameters analysed for base and sensitivity cases .................................................. 13
Table 3.3: Assumptions for KSA .................................................................................................. 14
Table 3.4: General assumptions for Mexico................................................................................ 19
Table 3.5: Assumptions for Chile ................................................................................................. 24
Table 3.6: General assumptions for RSA ..................................................................................... 29
Table 4.1: Current carbon prices in 2005 USD/tCO2eq ............................................................... 45
Table 4.2: IRENA's Renewable Energy Roadmap - REmap Countries Renewable Energy Targets,
2014 ............................................................................................................................................. 46
Table 4.3: Comparison of criteria between Biberacher (2010) and Trieb et al (2009) study ..... 48
Table 4.4: Comparison between Biberacher (2010) and Trieb et al (2009) study ...................... 48
Table 4.5: Inputs parameters for the HYSOL in ETSAP-TIAM ...................................................... 49
Table 4.6: Total system cost in billion USD2005 ............................................................................ 54
Table 4.7: Total direct CO2 emissions in Gt of CO2. .................................................................... 54
List of figures
Figure 3.1: Electricity production costs for OCGT and KSA HYSOL.............................................. 16
Figure 3.2: Electricity production costs for OCGT andKSA HYSOL .............................................. 17
Figure 3.3: Electricity production costs for CCGT and KSA HYSOL .............................................. 18
Figure 3.4: Electricity production costs for CCGT and KSA HYSOL .............................................. 19
Figure 3.5: Electricity production costs for OCGT, MEX HYSOL .................................................. 21
Figure 3.6: Electricity production costs for OCGT and MEX HYSOL ............................................ 22
Figure 3.7: Electricity production costs for CCGT and MEX HYSOL ............................................. 23
Figure 3.8: Electricity production costs for CCGT and MEX HYSOL ............................................. 24
Figure 3.9: Electricity production costs for OCGT and CHI HYSOL ............................................. 26
Figure 3.10: Electricity production costs for OCGT and CHI HYSOL ............................................ 27
Figure 3.11: Electricity production costs for CCGT andCHI HYSOL ............................................. 28
Figure 3.12: Electricity production costs for CCGT, CHI HYSOL ................................................... 29
Figure 3.13: Electricity production costs for OCGT and RSA HYSOL ........................................... 31
Figure 3.14: Electricity production costs for OCGT and RSA HYSOL ........................................... 32
Figure 3.15: Electricity production costs for CCGT and RSA HYSOL ............................................ 33
Figure 3.16: Electricity production costs for CCGT and RSA HYSOL ............................................ 34
Figure 3.17: Sensitivity relative to base case assumptions KSA HYSOL ...................................... 35
Figure 3.18: Sensitivity relative to base case assumptions KSA OCGT ........................................ 35
Figure 3.19: Sensitivity relative to base case assumptions KSA CCGT ........................................ 36
Figure 3.20:Sensitivity relative to base case assumptions MEX HYSOL ...................................... 36
Figure 3.21: Sensitivity relative to base case assumptions MEX OCGT ...................................... 37
Figure 3.22: Sensitivity relative to base case assumptions MEX CCGT ....................................... 37
Figure 3.23: Sensitivity relative to base case assumptions CHI HYSOL ....................................... 38
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Figure 3.24: Sensitivity relative to base case assumptions CHI OCGT ........................................ 38
Figure 3.25: Sensitivity relative to base case assumptions CHI CCGT ......................................... 39
Figure 3.26: Sensitivity relative to base case assumptions RSA HYSOL ...................................... 39
Figure 3.27: Sensitivity relative to base case assumptions RSA OCGT ........................................ 40
Figure 3.28: Sensitivity relative to base case assumptions RSA CCGT ........................................ 40
Figure 4.1: Diagram of framework for analysis and work flow ................................................... 43
Figure 4.2: Fifteen regions of the ETSAP-TIAM ........................................................................... 44
Figure 4.3: Annual average DNI (KWh/m2 year) .......................................................................... 46
Figure 4.4: Worldwide exclusion of sites for CSP plant construction ......................................... 47
Figure 4.5: Overall learning curve and the contributions of the main parts for CSP plant in Spain
..................................................................................................................................................... 50
Figure 4.6: Electricity production by fuel in Mexico, reference scenario ................................... 51
Figure 4.7: Electricity production by fuel in Mexico, HYSOL high penetration scenario ............ 51
Figure 4.8: Electricity production by fuel in Western Europe, reference scenario ..................... 52
Figure 4.9: Electricity production by fuel in Western Europe, HYSOL high penetration scenario
..................................................................................................................................................... 52
Figure 4.10: Electricity production by fuel in Africa, reference scenario .................................... 53
Figure 4.11: Electricity production by fuel in Africa, HYSOL high penetration scenario ............. 53
D6.1: Socio-economic assessment and energy system analysis
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Abbreviations
AEEI Autonomous Energy Efficiency Improvement
AFR Africa
CAPEX Capital Expenditure
CCGT Combined Cycle Gas Turbines
CSP Concentrate Solar Power
DNI Direct Normal Irradiance ETSAP-TIAM Energy Technology System Analysis Program TIMES Integrated Assessment Model
ETS Emission Trading Schemes
GT Gas Turbine
HFLH Annual Full Load Hours
HTS High Temperature Molten Salt
HYSOL HYbrid SOLar
IDIE Research Development Innovation and Energy
KSA The Kingdom of Saudi Arabia
LCOE Levelized Cost of Energy
LF Load Factor
MARKAL MARket Allocation mode
MEX Mexico
NG Natural Gas
O&M Operation and Maintenance
OCGT Open Cycle
OPEX Operational Expenditure
PH Assigned HYSOL capacity
p.a. Per annum (per year)
PV Photovoltaic
RE Renewable Energy
RES Renewable Energy Source
RSA Republic of South Africa
ST Steam Turbine
TIMES The Integrated MARKAL-EFOM System
WEU Western Europe
D6.1: Socio-economic assessment and energy system analysis
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Acknowledgements
Within the Seventh Framework Programme, the deliverable D6.1 "Socio-economic assessment
and energy system analysis" is a collaborative work among the System Analysis Group of the
Management Engineering Department of DTU, ACS Cobra, and PSA-CIEMAT and UPM.
Special thanks to go to Klaus Skytte, Olexandr Balyk, Kenneth Karlsson Mattia Baldini and Poul
Erik Grohnheit from DTU-ME and Helena Cabal (CIEMAT), who have been supporting forces
behind this work.
D6.1: Socio-economic assessment and energy system analysis
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Contact
Comments and questions are welcome and should be addressed to:
Cristian Cabrera
DTU-Management Engineering (ME)
Lars Henrik Nielsen
DTU- Management Engineering (ME)
D6.1: Socio-economic assessment and energy system analysis
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1 Executive summary
The aim of HYSOL Project is to become the European reference in competition to initiatives
ongoing in the CSP/biomass global market. The HYSOL Project focusses on overcoming the CSP
technology limitations to increase its contribution in the global electric market, hybridising
with biomass energy to achieve 100 % renewable and sustainable energy, and providing a
stable and reliable power independently of meteorogical circumstances.
Socio-economic assessment
The aim of this analysis is to investigate the economic viability of HYSOL relative to
conventional reference firm power generation technologies. In particular the HYSOL
performance relative to new power plants based on natural gas (NG) such as Open Cycle or
Combined Cycle Gas Turbines (OCGT or CCGT) are in focus. Levelized Cost of Energy (LCOE) are
used as a benchmark for comparison among the mentioned technologies Furthermore, a
sensitivity analysis is performed to identify the critical parameters that make HYSOL more
attractive from a socio-economic viewpoint. The regions examined are the Kingdom of Saudi
Arabia (KSA hereafter), Mexico, the Republic of South Africa (RSA hereafter) and Chile. These
regions not only have a prominent solar potential but also interesting market conditions, for
more information refer to D.6.4 "Analysis of regulation and economic incentives".
From the socio-economic assessment the following key findings are outlined in the box below:
Key findings from the socio-economic assessment
General findings:
CO2 emission cost increase significantly the LCOE cost in both OCGT and CCGT cases, in particular the OCGT plant solution is strongly exposed to potential rising CO2 emission while this cost may impact positively the future scenario for HYSOL.
HYSOL is sensitive to the interest rate. In Base Case a rate of calculation of 4% per annum (p.a.) has been assumed, which correspond to typical socio-economic conditions. Assuming a higher rate of interest of 10% p.a. equivalent to corporate economic interest rate, the sensitivity analysis shows that power production costs (LCOE) are increased substantially. Therewith, HYSOL is very sensitive to changes in the interest rate.
Country-specific findings:
For Chile, HYSOL is economically competitive when it is compared vs. OCGT and CCGT options, while it is not cost-effective in the KSA and Mexico. The lack of competitiveness in these countries is due to the significantly low NG prices in comparison to Chile (Chile NG is about three times as much as in Mexico or KSA). Furthermore, the current NG price conditions discourage the economic attractiveness of HYSOL in these countries.
For RSA, HYSOL competes favourable relative to the OCGT reference as can be seen from comparing results when base case data are assumed. This conclusion holds even without taking into account an assumed cost on CO2 emission. When compared to a CCGT reference plant the RSA HYSOL alternative is less favourable. However, introducing an assumed CO2 emission costs of 40 USD/tCO2eq emitted, narrows the LCOE price difference considerable (down to a LCOE difference of less than 5 USD/MWh).
D6.1: Socio-economic assessment and energy system analysis
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Energy system analysis
The objective of this analysis is to determine the impact of HYSOL roll-out on total system cost,
direct CO2 emissions and energy mix in regions with a high solar potential and attractive
market conditions, for example, Mexico, Africa and Western Europe. Chile and KSA were
excluded from this analysis due to modelling limitations.
From the energy system analysis the following key findings are summarized in the box below:
Key findings from the energy system analysis
General findings:
HYSOL will not be deployed under normal market conditions. This is due to the high investment cost of this technology. Therefore, HYSOL will need to be supported.
The deployment of HYSOL has neither negative nor positive effect in the total system cost, this is valid for all the regions analysed.
A high deployment of HYSOL has a negligible impact on direct C02 emissions at total energy system level. However, it may have an impact at local level because it can replace gas and oil fuelled power plants.
Country-specific findings:
In Africa, the roll-out of HYSOL can help to phase-out gas and oil power plants in the long-term.
In Mexico, the deployment of HYSOL could contribute to decrease gas and oil power plants in the mid-term.
In Western Europe, a high penetration of HYSOL has negligible impact on the power system. This is due to the limited solar potential and land availability of the region.
D6.1: Socio-economic assessment and energy system analysis
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2 Introduction
Concentrating Solar Power (CSP) is in its infancy in terms of deployment compared to the other
renewable power generation technologies, with only 5 GW of CSP installed worldwide at the
end of 2014; of this capacity, the CSP market is dominated by parabolic trough technologies
(around 85% of cumulative installed capacity) (IRENA, 2014b). Nevertheless, an increasing
numbers of solar towers are being built and offer the promise of lower electricity costs. CSP
can integrate low-cost thermal energy storage in order to provide dispatchable electricity to
the grid and capture peak market
CSP plants utilize thermal conversion of direct solar irradiation. A trough or tower
configuration focus solar radiation and heat up oil or molten salt that subsequently in high
temperature heat exchangers generate steam for power generation. High Temperature
Molten Salt can be stored (HTS) and the stored heat can thus increase the load factor and the
usability for a CSP plant, e.g. to cover night (peak) demand. In the HYSOL concept (HYbrid
SOLar) such configuration is extended further to include a gas turbine fuelled by upgraded
biogas or natural gas. The optimised integrated HYSOL concept, therefore, becomes a fully
dispatchable (offering firm power) and a fully Renewable Energy (RE) based power supply
alternative, offering CO2-free electricity in regions with sufficient solar resources and attractive
market conditions.
Under this framework the objectives of the study are:
1. To study the economic potential of HYSOL in comparison to competing technologies from
a socio-economic perspective, e.g. to compare HYSOL vs. Open/Combined Cycle Gas
Turbine (OCGT and CCGT) for KSA, Mexico, RSA and Chile.
2. To examine effect on the energy system, when HYSOL is deployed, in terms of total system
cost, direct CO2 emissions and energy mix under different scenarios in Africa, Western
Europe and Mexico.
This study contents mainly two analyses, a socio-economic and an energy system analysis. The
socio-economic study examines the future economic viability of HYSOL in KSA, Mexico, RSA
and Chile, from a socio-economic viewpoint. For each country, different scenarios are
investigated where HYSOL competes vs. OCGT and CCGT under different conditions, e.g.
Variable Natural Gas (NG) price and CO2 emission cost among others parameters are exposed
to sensitivity analysis to determine the key parameters that have a significant impact on the
economic feasibility of this technology, based on Levelized Cost of Energy (LCOE) differences.
In addition, an energy system analysis is carried out to foreseeing the future economic
potential of HYSOL under three different deployment scenarios: a low, a moderate and a high
HYSOL roll-out, for Western Europe, Africa, and Mexico. This analysis shows the overall impact
of HYSOL in terms of CO2 emissions reduction, energy mix and total system cost. Finally,
conclusions based on the key findings found in both socio-economic and energy system
analysis are drawing in the conclusion section.
D6.1: Socio-economic assessment and energy system analysis
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3 Socio-economic feasibility assessment
The economic feasibility of HYSOL configurations is addressed. The HYSOL alternative is
discussed relative to conventional reference firm power generation technologies. In particular
the HYSOL performance relative to new power plants based on Natural Gas (NG) such as Open
Cycle or Combined Cycle Gas Turbines (OCGT or CCGT) are in focus. The feasibility of
renewable based HYSOL power plant configurations attuned to specific electricity consumption
patterns in KSA, Mexico, RSA and Chile, where promising solar energy potentials are discussed.
3.1 Framework conditions for the countries analysed
The analytical approach used is illustrated from an example where a HYSOL configuration is
optimised to conditions seen in the countries studied. Thus, the HYSOL power plant studied
has been attuned to solar potentials and power system characteristics resembling conditions
in the countries analysed.
HYSOL plant configuration particularizes the basic outline by the choices:
For all the countries analysed, a CSP Tower configuration has been assumed. HYSOL
configurations can also be applied with CSP trough design;
The HYSOL plant investments do not include investments in biogas plants. The HYSOL plant
is assumed to purchase biogas at a price that equals the price of natural gas (NG) plus the
value of the reduced CO2 emission when biogas is used. HYSOL’s 100% renewable
configuration use biogas upgraded to NG quality.
As the HYSOL configuration analysed uses natural gas (NG) and not biogas based methane, the
plant may not be termed fully renewable, though being a firm, fully dispatchable and mainly
renewables based power plant.
Note: The data used for this analysis was provided by IDIE (Research Development Innovation
and Energy) unless otherwise indicated.
3.2 The HYSOL alternative and competing technology
This analysis compares electricity production costs for a HYSOL plant alternative to production
cost for conventional power plant solutions or reference plants.
For the KSA, Chile, Mexico and RSA cases it has been assumed that the main competing
reference technologies are an OCGT and a CCGT using NG.
3.3 Approach and basic assumptions
3.3.1 Economic indicator
A socio-economic approach is applied focusing on the economic indicator Levelized Cost of
Energy (LCOE), and on the sensitivity of the LCOE in particular to variations in the two
parameters:
• Load factor or the number of full load hours per year, and the
D6.1: Socio-economic assessment and energy system analysis
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• price of natural gas (given as the levelized NG price covering the period analysed).
The solar potential and the annual power production heavily impact the HYSOL power plant
economy. And for fossil based competing reference technologies fuel cost and CO2 emission
cost developments constitute important framework conditions. LCOE dependency on in
particular these major parameters will be in focus in this study of HYSOL solutions (based
predominantly on a Renewable Energy Source (RES)) relative to fossil based conventional
reference power plant solutions.
3.3.2 Base Case assumptions
For the present socio-economic analysis1 the following general assumptions have been
adopted as 'Base Case' as outlined in Table 3.1.
Table 3.1: General assumptions
General assumptions
Price level Year 2015
Socio economic rate of calculation (rate of interest)
4 % p.a.
Project base year 2020
Period analysed 2021-2045
Period in years 25 years
Note: Assumptions are valid for all the countries studied.
3.3.3 Base Case overview and issues addressed via sensitivity analyses
Electricity production costs (LCOE) are furthermore analysed for its dependence on or
sensitivity to variations in the parameters outlined in Table 3.2.
Table 3.2: Parameters analysed for base and sensitivity cases
General assumptions & sensitivities
Natural Gas price Sensitivity Base Case -/+40%
CO2 emission quota market price
Base case-Sensitivity 0-40 USD/tCO2eq2
Capacity assignment Base case-Sensitivity 1303-
1504 MW
5-100MW <--> 180MW
1 Socio-economic analyses are used to assess how the objectives of energy policy are achieved in the
most appropriate way. The objective of socio-economic analysis of projects is to improve the basis for a qualified social prioritization of scarce resources. A sensible social prioritization of resources across sectors with varying time horizons require that assessments are made based on consistent and transparent methods, while special issues and consequences are described as best as possible. The result will always be a balance of both economic and non-economic considerations, including social, ethical and others. http://www.ens.dk/en/info/facts-figures/scenarios-analyses-models/socio-economic-method-analyses 2 Tonnes of carbon dioxide equivalents.
D6.1: Socio-economic assessment and energy system analysis
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Lifetime of initial investment
Base case-Sensitivity 25-20 years
Interest rate Base case-Sensitivity 4.0-10% p.a.
Initial investment (CAPEX)
Sensitivity Base Case +/- 20%
3.4 KSA
3.4.1 Base Case for KSA HYSOL plant
Chosen Base Case for KSA HYSOL plant annual production, assigned capacity, load factor and
NG price (including sensitivity) are outlined in Table 3.3.
Table 3.3: Assumptions for KSA
KSA assumptions
Annual electricity production 812.7 GWh6/year
Assigned HYSOL capacity (PH) 130 MW
Annual full load hours7 (HFLH) 6 251 hours/year
Load factor8 (LF) 0.714
NG price 13.65 USD/MWh9 (4USD/MMBtu
10)
Sensitivity +/- 20%, +/-40% (Base Case)
Note: Data on investments, operation and maintenance costs for the KSA HYSOL configuration
are found in the Appendix.
3.4.2 Electricity costs as function of load factor and NG price
In Figure 3.1-Figure 3.4, results on the LCOE (given along the y-axis) are shown as a function of
the annual load. The annual load or electricity production, here expressed through its
equivalent, the number of full load hours per year, is shown along the x-axis.
HYSOL plant operation at different load factors is assumed to maintain the relative ST and GT
contribution to the electricity production. Thus, even the annual power production may differ
from the Base Case assumption the %-split of production contributions from the ST and GT
HYSOL plant components is assumed constant. And the share of the annual production based
on gas (via the GT directly and indirectly via GT flue gas heat recovered and utilized by the ST)
is kept constant.
3 130 MW is assigned to KSA.
4 150 MW is assigned to Mexico, RSA and Chile.
5 Megawatt.
6 Gigawatt-hours.
7 HFLH=812.7 GWh/year/130 MW=6 251 hours/year.
8 LF= 6 251/8 760 = 0.714
9 Megawatt-hours.
10 Million British Thermal Units.
D6.1: Socio-economic assessment and energy system analysis
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Furthermore, for this feasibility analysis the HYSOL plant operation efficiency is assumed
constant, - even at e.g. lower annual production levels. And gas consumption per MWh
electricity generated, accordingly, is assumed constant and independent of the production.
This may be a somewhat rough assumption.
3.4.3 Design Point assumptions
Assumptions used as basis for optimizing and configuring the HYSOL plant, will in the following
be termed the 'Design Point' data assumptions. Yellow points, 'Design Points', shown in Figure
3.1-Figure 3.4 represent results for the KSA HYSOL plant based on Base Case assumptions.
Black points, correspondingly, represent (OCGT or CCGT) reference technology results based
on equivalent assumptions. Other results presented may thus be considered as sensitivity and
parameter analyses.
3.4.4 HYSOL relative to OCGT and CCGT
In what follows the KSA HYSOL plant alternative is compared to competing 'conventional' or
reference plant solutions based on equivalent system framework condition. Benchmarked via
the LCOE the competing technologies are evaluated using equivalent general assumptions. The
so-called Base Case data assumptions form the core for this feasibility comparison. For
selected key parameters LCOE consequences of data deviating from Base Case are covered via
sensitivity analysis.
For consistency of the comparison it is assumed, that the average annual electricity production
is the same for the HYSOL alternative and for the reference plants. Furthermore, plants being
compared are assumed to have the same capacity value in the KSA power system, and the
plants are assumed to be fully dispatchable (firm power). Thus, all plants are assumed to be
able to occupy the same position in the overall power system dispatch.
Data for the KSA HYSOL alternative and for the assumed KSA OCGT and KSA CCGT reference
power plants are found in the Appendix.
It can be observed from Figure 3.1-Figure 3.4 that the annual number of full load operation
hours for the HYSOL plant, shown along the x-axis, is extremely important for the electricity
production cost achieved, - and the plant economy. Low annual power production results in
high production costs. For the overall economy of a HYSOL plant, therefore, it is very important
to achieve high annual power production, as the total production costs are much dominated
by high initial investments. NG prices, however, have minor impact on the HYSOL power
production cost due to the relatively low electricity production contribution via the GT part of
the KSA HYSOL configuration.
3.4.5 CO2 emission costs
Comparison of HYSOL solutions relative to conventional OCGT and CCGT power plant solutions
are carried out for cases with and without inclusion of an assumed CO2 emission cost. For this
sensitivity analysis it has been assumed, as an example, that CO2 emission costs amounts to 40
USD/tCO2eq emitted. For natural gas (NG) this CO2 emission cost is equivalent to 8.17
D6.1: Socio-economic assessment and energy system analysis
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USD/MWh NG. The CO2 emission cost assumed thus rises the NG price with an extra 8.17
USD/MWh NG.USD
3.4.6 Results: HYSOL compared to OCGT
Figure 3.1 shows the electricity production costs for OCGT and KSA HYSOL configuration, as
function of load factor and NG price.
Figure 3.1: Electricity production costs for OCGT and KSA HYSOL
Note: Assumed CO2 costs = 0 USD/tCO2eq, R=4%p.a., Lifetime=25years. Unit: USD/MWh el.
Figure 3.2 shows the electricity production costs for OCGT and KSA HYSOL configuration, as
function of load factor and NG price.
D6.1: Socio-economic assessment and energy system analysis
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Figure 3.2: Electricity production costs for OCGT and KSA HYSOL
Note: Assumed CO2 costs = 40USD/tCO2eq, R=4%p.a., Lifetime=25years. Unit: USD/MWh el.
3.4.7 Results: HYSOL compared to CCGT
Figure 3.3 shows the electricity production costs for CCGT and KSA HYSOL configuration, as
function of load factor and NG price.
D6.1: Socio-economic assessment and energy system analysis
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Figure 3.3: Electricity production costs for CCGT and KSA HYSOL
Note: Assumed CO2 costs = 0USD/tCO2eq, R=4%p.a., Lifetime=25years. Unit: USD/MWh el.
Figure 3.4 shows the electricity production costs for CCGT and KSA HYSOL configuration, as
function of load factor and NG price.
D6.1: Socio-economic assessment and energy system analysis
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Figure 3.4: Electricity production costs for CCGT and KSA HYSOL
Note: Assumed CO2 costs = 40USD/tCO2eq, R=4%p.a., Lifetime=25years. Unit: USD/MWh el.
For details about LCOE price composition see the Appendix section.
3.5 Mexico
3.5.1 Base Case for MEX HYSOL plant
Chosen Base Case for the MEX HYSOL plant annual production, assigned capacity and load
factor are outlined in Table 3.4.
Table 3.4: General assumptions for Mexico
Mexico assumptions
Annual electricity production 929.2 GWh/year
Assigned HYSOL capacity (PH) 150 MW
Annual full load hours11
(HFLH) 6 195 hours/year
Load factor12
(LF) 0.707
NG price 13.31 USD/MWh (3.9 USD/MMBtu)
Sensitivity +/- 20%, +/-40% (Base Case)
11
HFLH = 929.2 GWh / 150MW = 6 195 hours/year. 12
LF= 6 251/8 760= 0.707.
D6.1: Socio-economic assessment and energy system analysis
20
Note: Data on investments, operation and maintenance costs for the MEX HYSOL configuration
are found in the Appendix.
3.5.2 Assumption on NG and biogas price relation
It has been assumed that the price of biogas can be estimated to equal the price of natural gas
(NG) plus the cost for the CO2 emission using the NG.
A CO2 emission cost, as assumed in our case study, of 40USD/tCO2eq emitted corresponds to a
rise of the NG price with an extra 8.17 USD/MWh NG. Thus, for the case of 40 USD/tCO2eq
emitted this means that the Biogas price will equal the NG price plus 8.17 USD/MWh NG.
With a NG price of 13.65 USD/MWh NG the assumption thus implies:
Biogas price = NG price + 8.17USD/MWh = 13.31 USD/MWh + 8.17 USD/MWh = 21.48
USD/MWh NG
If it is furthermore assumed that biogas has zero CO2 emission the economic consequence of
the use of biogas as fuel in HYSOL plant solutions will correspond to fuel costs as for NG plus its
CO2 cost. The fuel price relations for HYSOL, OCGT and CCGT solutions thus correspond to the
NG price including CO2 costs. However in this case the HYSOL solution using biogas has no CO2
emission.
The economic calculations shown in Figure 3.5 and Figure 3.6 showing power production costs
(LCOE) for the HYSOL solution relative to the OCGT and CCGT solutions, therefore, will hold
also for the case where HYSOL use biogas (and thus has no CO2 emission) and the OCGT and
CCGT use NG and emit CO2 at a cost of 40USD/tCO2eq emitted.
3.5.3 Results: HYSOL compared to OCGT
In Figure 3.5 it has been assumed that the CO2 emission costs are 0 USD/tCO2eq emitted. In
such scenario the CO2 reduction achieved by using (CO2 emission free biogas) thus has no
value. Therefore, in the 0 USD/tCO2eq emitted scenario, it has been assumed that both the
HYSOL plant and the OCGT plant use NG.
D6.1: Socio-economic assessment and energy system analysis
21
Figure 3.5: Electricity production costs for OCGT and MEX HYSOL
Note: Assumed CO2 costs = 0USD/tCO2eq, R=4%p.a., Lifetime=25years. Unit: USD/MWh el.
In Figure 3.5 it has been assumed that the CO2 emission costs are 40 USD/tCO2eq emitted. In
this case it has been assumed that the HYSOL plant use (CO2 emission free) biogas. The price of
biogas has been assumed to equal the price of NG plus the value of CO2 emission reduction
achieved by using biogas substituting NG.
However, the reference OCGT plant that solely relies on gas as fuel has been assumed use NG
priced as the NG price plus the cost of the CO2 emitted. (A cost of 40 USD/tCO2eq emitted
equals a price increase for the NG with an extra 8.17 USD/MWh NG.)
D6.1: Socio-economic assessment and energy system analysis
22
Figure 3.6: Electricity production costs for OCGT and MEX HYSOL
Note: Assumed CO2 costs = 40 USD/tCO2eq, R=4%p.a., Lifetime=25years. Unit: USD/MWh el.
D6.1: Socio-economic assessment and energy system analysis
23
3.5.4 Results: HYSOL compared to CCGT
Figure 3.7 compares MEX HYSOL vs. CCGT in terms of their electricity production costs under
different NG prices and a carbon cost of 0 USD/tCO2eq.
Figure 3.7: Electricity production costs for CCGT and MEX HYSOL
Note: Assumed CO2 costs = 0 USD/tCO2eq, R=4%p.a., Lifetime=25years. Unit: USD/MWh el.
Figure 3.8 shows MEX HYSOL vs. CCGT in terms of their electricity production costs under
different NG prices and a carbon cost of 40 USD/tCO2eq.
D6.1: Socio-economic assessment and energy system analysis
24
Figure 3.8: Electricity production costs for CCGT and MEX HYSOL
Note: Assumed CO2 costs = 40 USD/tCO2eq, R=4%p.a., Lifetime=25years. Unit: USD/MWh el.
For details about LCOE price composition see the Appendix section.
3.6 Chile
3.6.1 Base Case for CHI HYSOL plant
Chosen Base Case for the CHI HYSOL plant annual production, assigned capacity and load
factor are outlined in Table 3.5.
Table 3.5: Assumptions for Chile
Chile assumptions
Annual electricity production 868.5 GWh/year
Assigned HYSOL capacity (PH) 150 MW
Annual full load hours13
(HFLH) 5 790 hours/year
Load factor14
(LF) 0.661
NG price 44.36 USD/MWh (4 USD/MMBtu)
13
HFLH = 868.48GWh / 150MW = 5 790 h/year. 14
LF= 5790/8760= 0.661.
D6.1: Socio-economic assessment and energy system analysis
25
Sensitivity +/- 20%, +/-40% (Base Case)
Note: Data on investments, operation and maintenance costs for the CHI HYSOL configuration
are found in the Appendix.
3.6.2 Assumption on NG and Biogas price relation
It has been assumed that the price of Biogas can be estimated to equal the price of natural gas
(NG) plus the cost for the CO2 emission using the NG.
A CO2 emission cost, as assumed in our case study, of 40USD/tCO2eq emitted corresponds to a
rise of the NG price with an extra 8.17 USD/MWh NG. Thus, for the case of 40 USD/tCO2eq
emitted this means that the Biogas price will equal the NG price plus 8.17 USD/MWh NG.
With a NG price of 13.65 USD/MWh NG the assumption thus implies:
Biogas price = NG price + 8.17 USD/MWh = 44.36 USD/MWh + 8.17 USD/MWh= 52.53
USD/MWh NG.
If it is furthermore assumed that biogas has zero CO2 emission the economic consequence of
the use of biogas as fuel in HYSOL plant solutions will correspond to fuel costs as for NG plus its
CO2 cost. The fuel price relations for HYSOL, OCGT and CCGT solutions thus correspond to the
NG price including CO2 costs. However in this case the HYSOL solution using biogas has no CO2
emission.
The economic calculations shown in Figure 3.10 and ¡Error! No se encuentra el origen de la
referencia. showing power production costs (LCOE) for the HYSOL solution relative to the
OCGT and CCGT solutions, therefore, will hold also for the case where HYSOL use biogas (and
thus has no CO2 emission) and the OCGT and CCGT use NG and emit CO2 at a cost of 40
USD/tCO2eq emitted.
3.6.3 Results: HYSOL compared to OCGT
In Figure 3.9 it has been assumed that the CO2 emission costs are 0 USD/tCO2eq emitted. In
such scenario the CO2 reduction achieved by using (CO2 emission free biogas) thus has no
value. Therefore, in the 0 USD/tCO2eq emitted scenario, it has been assumed that both the
HYSOL plant and the OCGT plant use NG.
D6.1: Socio-economic assessment and energy system analysis
26
Figure 3.9: Electricity production costs for OCGT and CHI HYSOL
Note: Assumed: CO2 costs = 0 USD/tCO2eq, R=4%p.a., Lifetime=25years. Unit: USD/MWh el.
In Figure 3.11 it has been assumed that the CO2 emission costs are 40 USD/tCO2eq emitted. In
this case it has been assumed that the HYSOL plant use (CO2 emission free) biogas. The price of
biogas has been assumed to equal the price of NG plus the value of CO2 emission reduction
achieved by using biogas substituting NG.
However, the reference OCGT plant that solely relies on gas as fuel has been assumed use NG
priced as the NG price plus the cost of the CO2 emitted. (A cost of 40 USD/tCO2eq emitted
equals a price increase for the NG with an extra 8.17 USD/MWh NG.)
D6.1: Socio-economic assessment and energy system analysis
27
Figure 3.10: Electricity production costs for OCGT and CHI HYSOL
Note: Assumed CO2 costs = 40 USD/tCO2eq, R=4%p.a., Lifetime=25years. Unit: USD/MWh el.
3.6.4 Results: HYSOL compared to CCGT
Figure 3.11 compares CHI HYSOL vs. CCGT in terms of their electricity production costs under
different NG prices and a carbon cost of 0 USD/tCO2eq.
D6.1: Socio-economic assessment and energy system analysis
28
Figure 3.11: Electricity production costs for CCGT and CHI HYSOL
Note: Assumed CO2 costs = 0USD/tCO2eq, R=4%p.a., Lifetime=25years. Unit: USD/MWh el.
Figure 3.12 shows CHI HYSOL vs. CCGT in terms of their electricity production costs under
different NG prices and a carbon cost of 40USD/tCO2eq.
D6.1: Socio-economic assessment and energy system analysis
29
Figure 3.12: Electricity production costs for CCGT, CHI HYSOL
Note: Assumed CO2 costs = 40USD/tCO2eq, R=4%p.a., Lifetime=25years. Unit: USD/MWh el.
3.7 RSA
3.7.1 Base Case for RSA HYSOL plant
Chosen Base Case for the RSA HYSOL plant annual production, assigned capacity and load
factor are outlined in Table 3.6.
Table 3.6: General assumptions for RSA
RSA assumptions
Annual electricity production 1 014 GWh/year
Assigned HYSOL capacity (PH) 150 MW
Annual full load hours15
(HFLH) 6 760 hours/year
Load factor16
(LF) 0.772
NG price 23.88 USD/MWh (7 USD/MMBtu)
Sensitivity +/- 20%, +/-40% (Base Case)
Note: Data on investments, operation and maintenance costs for the RSA HYSOL configuration
are found in the Appendix.
15
HFLH = 1 014 GWh / 150 MW = 6 760 hours/year. 16
LF= 6 760/8 760= 0.772.
D6.1: Socio-economic assessment and energy system analysis
30
3.7.2 Assumption on NG and Biogas price relation
It has been assumed that the price of biogas can be estimated to equal the price of natural gas
(NG) plus the cost for the CO2 emission using the NG.
A CO2 emission cost, as assumed in our case study, of 40 USD/tCO2eq emitted corresponds to a
rise of the NG price with an extra 8.17 USD/MWh NG. Thus, for the case of 40 USD/tCO2eq
emitted this means that the biogas price will equal the NG price plus 8.17 USD/MWh NG.
With a NG price of 23.88 USD/MWh NG the assumption thus implies:
Biogas price = NG price + 8.17 USD/MWh = 23.88 USD/MWh + 8.17 USD/MWh = 32.05
USD/MWh NG.
If it is furthermore assumed that biogas has zero CO2 emission the economic consequence of
the use of biogas as fuel in HYSOL plant solutions will correspond to fuel costs as for NG plus its
CO2 cost. The fuel price relations for HYSOL, OCGT and CCGT solutions thus correspond to the
NG price including CO2 costs. However in this case the HYSOL solution using biogas has no CO2
emission.
The economic calculations shown in Figure 3.14 and Figure 3.16 showing power production
costs (LCOE) for the HYSOL solution relative to the OCGT and CCGT solutions, therefore, will
hold also for the case where HYSOL use biogas (and thus has no CO2 emission) and the OCGT
and CCGT use NG and emit CO2 at a cost of 40 USD/tCO2 eq emitted.
D6.1: Socio-economic assessment and energy system analysis
31
3.7.3 Results: HYSOL compared to OCGT
Figure 3.13 shows the LCOE of RSA HYSOL vs. OCGT as a function of the annual full load hours
and NG prices. HYSOL is competitive at about 24 USD/MWh NG price, because at design point,
HYSOL LCOE is 67 USD/MWh vs. 84 USD/MWh of OCGT.
Figure 3.13: Electricity production costs for OCGT and RSA HYSOL
Note: Assumed CO2 costs = 0 USD/tCO2eq, R=4%p.a., Lifetime=25years. Unit: USD/MWh el.
Figure 3.14 illustrates the LCOE of RSA HYSOL vs. OCGT as a function of the annual full load
hours and NG prices. HYSOL is competitive at about 24 USD/MWh NG, because at design point,
HYSOL LCOE is 72 USD/MWh vs. 110 USD/MWh of OCGT.
D6.1: Socio-economic assessment and energy system analysis
32
Figure 3.14: Electricity production costs for OCGT and RSA HYSOL
Note: Assumed CO2 costs = 40 USD/tCO2eq, R=4%p.a., Lifetime=25years. Unit: USD/MWh el.
D6.1: Socio-economic assessment and energy system analysis
33
3.7.4 Results: HYSOL compared to CCGT
Figure 3.15 illustrates the LCOE of RSA HYSOL vs. CCGT as a function of the annual full load
hours and NG prices. HYSOL is not competitive at design point (approximately 24 USD/MWh),
because HYSOL LCOE corresponds to 67 USD/MWh vs. 54 USD/MWh of CCGT.
Figure 3.15: Electricity production costs for CCGT and RSA HYSOL
Note: Assumed CO2 costs = 0 USD/tCO2eq, R=4%p.a., Lifetime=25years. Unit: USD/MWh el.
Figure 3.16 shows the LCOE of RSA HYSOL vs. CCGT as a function of the annual full load hours
and NG prices. HYSOL is not competitive at design point (approximately 24 USD/MWh),
because HYSOL LCOE corresponds to 72 USD/MWh vs. 68 USD/MWh of CCGT.
D6.1: Socio-economic assessment and energy system analysis
34
Figure 3.16: Electricity production costs for CCGT and RSA HYSOL
Note: Assumed CO2 costs = 40 USD/tCO2eq, R=4%p.a., Lifetime=25years. Unit: USD/MWh el.
3.8 Sensitivity analyses
3.8.1 KSA
Figure 3.17 illustrates KSA HYSOL results in overview: Electricity production costs (LCOE) -
Sensitivity relative to Base Case Assumptions. Units: USD/MWh el.
D6.1: Socio-economic assessment and energy system analysis
35
Figure 3.17: Sensitivity relative to base case assumptions KSA HYSOL
Figure 3.18 shows KSA OCGT results in overview: Electricity production costs (LCOE) -
Sensitivity relative to Base Case Assumptions. Units: USD/MWh el.
Figure 3.18: Sensitivity relative to base case assumptions KSA OCGT
Figure 3.19 shows KSA CCGT results in overview: Electricity production costs (LCOE) -
Sensitivity relative to Base Case Assumptions. Units: USD/MWh el.
D6.1: Socio-economic assessment and energy system analysis
36
Figure 3.19: Sensitivity relative to base case assumptions KSA CCGT
3.8.2 Mexico
Figure 3.20 shows MEX HYSOL results in overview: Electricity production costs (LCOE) -
Sensitivity relative to Base Case Assumptions. Units: USD/MWh el.
Figure 3.20:Sensitivity relative to base case assumptions MEX HYSOL
Figure 3.21 illustrates MEX OCGT results in overview: Electricity production costs (LCOE) -
Sensitivity relative to Base Case Assumptions. Units: USD/MWh el.
D6.1: Socio-economic assessment and energy system analysis
37
Figure 3.21: Sensitivity relative to base case assumptions MEX OCGT
Figure 3.22 shows MEX CCGT results in overview: Electricity production costs (LCOE) -
Sensitivity relative to Base Case Assumptions. Units: USD/MWh el.
Figure 3.22: Sensitivity relative to base case assumptions MEX CCGT
3.8.3 Chile
Figure 3.23 illustrates CHI HYSOL results in overview: Electricity production costs (LCOE) -
Sensitivity relative to Base Case Assumptions. Units: USD/MWh el.
D6.1: Socio-economic assessment and energy system analysis
38
Figure 3.23: Sensitivity relative to base case assumptions CHI HYSOL
Figure 3.24 shows CHI OCGT results in overview: Electricity production costs (LCOE) -
Sensitivity relative to Base Case Assumptions. Units: USD/MWh el.
Figure 3.24: Sensitivity relative to base case assumptions CHI OCGT
Figure 3.25 shows CHI CCGT results in overview: Electricity production costs (LCOE) - Sensitivity
relative to Base Case Assumptions. Units: USD/MWh el.
D6.1: Socio-economic assessment and energy system analysis
39
Figure 3.25: Sensitivity relative to base case assumptions CHI CCGT
3.8.4 RSA
Figure 3.26 illustrates RSA HYSOL results in overview: Electricity production costs (LCOE) -
Sensitivity relative to Base Case Assumptions. Units: $/MWh el.
Figure 3.26: Sensitivity relative to base case assumptions RSA HYSOL
D6.1: Socio-economic assessment and energy system analysis
40
Figure 3.27 shows RSA OCGT results in overview: Electricity production costs (LCOE) -
Sensitivity relative to Base Case Assumptions. Units: $/MWh el.
Figure 3.27: Sensitivity relative to base case assumptions RSA OCGT
Figure 3.28 depicts RSA CCGT results in overview: Electricity production costs (LCOE) -
Sensitivity relative to Base Case Assumptions. Units: $/MWh el.
Figure 3.28: Sensitivity relative to base case assumptions RSA CCGT
D6.1: Socio-economic assessment and energy system analysis
41
3.9 Key findings
General findings:
The price of natural gas (NG) and its expected development strongly impacts the economic
attractiveness of HYSOL solutions relative to NG based competing technologies, such as
OCGT and CCGT power plants.
CO2 emission costs acts significantly in favour of HYSOL solutions. As seen from the
sensitivity analysis, in particular an OCGT plant solution is strongly exposed to potential
rising CO2 emission costs.
The capacity of a HYSOL plant is defined by the size of firm capacity it may substitute being
part of the power system in question. This impacts the required capacity investments for
competing solutions (OCGT or CCGT) matching the HYSOL plant in the system. The
economic implication of different capacity assignments, however, as seen from the
sensitivity analysis, is relatively minor. This due to the relative low initial investment
component for OCGT and CCGT plants, which may be seen comparing power price
composition results shown in the Appendix.
The period analysed and the lifetime of the initial investments has minor impact on the
electricity production cost for the OCGT and CCGT plant solutions. Being an initial
investment intensive RES based technology the HYSOL solution is seen to be impacted,
though moderately, from changes in lifetime of the investment.
The interest rate or the rate of calculation is important for investment intensive plants,
such as the HYSOL solution. In Base Case a rate of calculation of 4% p.a. has been assumed,
which may correspond to typical socio-economic conditions. Assuming a higher rate of
interest of 10% p.a., that may resemble a corporate economic situation, it is seen from the
sensitivity analysis that power production costs (LCOE) are increased substantially. In
particular the HYSOL solution is very sensitive to changes in the interest rate.
HYSOL solutions, being investment intensive are very sensitive to changes in the overall
investment costs, and the rate of interest, whereas the OCGT and CCGT solutions are
considerable less exposed to changes in the overall investment.
Country-specific findings:
For Chile, HYSOL is economically competitive when compared to OCGT and CCGT options,
while this HYSOL solution is not competitive in the KSA and Mexico cases. The lack of
competitiveness in these countries could be attributing to the significantly low NG prices.
(NG price in Chile is about three times as much as in Mexico or KSA).
The HYSOL solution in RSA competes favourable relative to the OCGT reference as can be
seen from comparing results when base case data are assumed. This conclusion holds
without taking into account an assumed cost on emission of CO2. When compared to a
CCGT reference plant the RSA HYSOL alternative is less favourable. However, introducing
an assumed CO2 emission costs of 40 USD/tCO2eq emitted, narrows the LCOE price
difference considerable (down to a LCOE difference of less than 5 USD/MWh).
D6.1: Socio-economic assessment and energy system analysis
42
4 Energy Systems Analysis
4.1 Objective
The general objective of the energy systems analysis is to assess the effects of introducing the
HYSOL technology into the target markets. I.e. how a hybrid CSP technology will affect the
surrounding energy system while taking into account the availability of resources for each
region/country selected.
More specific, this exercise will help to understand the possible contribution in terms of CO2
abatement, system cost reduction and energy mix diversification.
4.2 Method
Energy-economic modelling (bottom-up) is the main method for this study, using the Energy
Technology System Analysis Program TIMES Integrated Assessment Model (ETSAP-TIAM). The
framework for the analysis is presented in Figure 4.1.
First, a reference scenario is created based on a default reference energy system
(described below);
Then an evaluation criteria is created for analysis, and based on these criteria, a HYSOL
scenario is created that represents different technological and policy constraints and
country/region specific CSP targets;
Furthermore, a high penetration HYSOL scenario will emphasize the effects on the
surrounding energy system.
These scenarios will be modelled in ETSAP-TIAM and compared to a reference scenario to see
the effect that the alternative technological and political factors have on the resulting
implementation of the HYSOL. The methodology used for analysing the energy systems is
based on linear programming.
D6.1: Socio-economic assessment and energy system analysis
43
Figure 4.1: Diagram of framework for analysis and work flow
4.3 ETSAP-TIAM
4.3.1 Times Architecture Background
The TIMES (The Integrated MARKAL-EFOM System) model generator, is an evolved version of
MARKAL (MARket Allocation model), developed under the IEA implementing agreement,
ETSAP. TIMES is a model generating set of optimization equations17 that computes an inter-
temporal dynamic partial equilibrium on energy and emission markets based on the
maximization of total surplus (defined as the sum of supplier and consumer surpluses). In
essence, a model generated by TIMES finds the least-cost solution for the entire energy system
with flexibility in terms of time resolution and sectorial focus.
4.3.2 Regions
ETSAP-TIAM is a global technology-rich model of the entire energy/emission system of the
world based on the TIMES model architecture. The model is set up to explore the development
of the world energy system for the 21st century, representing the energy system of the world,
divided into 15 regions (Figure 4.2). ETSAP-TIAM models the procurement, transformation,
trade, and consumption of a large number of energy forms. Results from applicable processes
are also aggregated to the global level.
17 A complete description of the TIMES equations appears in: http://www.iea-
etsap.org/web/Documentation.asp.
No
Reference scenario HYSOL scenarios
ETSAP-TIAM
Evaluation criteria: E.g.
does HYSOL deploy
under normal market
conditions?
Energy system
assessment
Input data
Output data
Yes
New input data
D6.1: Socio-economic assessment and energy system analysis
44
Figure 4.2: Fifteen regions of the ETSAP-TIAM18
4.3.3 Time Frame
Our analysis considers from 2010 to 2050. We conduct the analysis using 2010 as a base year,
and use 10-year time steps. In which 2030 is considered as midterm and 2050 is considered as
long term.
4.3.4 Model Structure
As ETSAP-TIAM is based on the TIMES equations, it is a perfect foresight, linear optimization
model (ETSAP-TIAM optimizes all time periods simultaneously). The objective function that is
maximized is the discounted net present value of the total surplus for the entire world. The
surplus maximization can be subject to many exogenously-defined constraints on a regional,
sectoral or global basis, such as supply bounds (in the form of detailed supply curves) for the
primary resources, technical constraints governing the creation, operation, and abandonment
of each technology, balance constraints for all energy forms and emissions, timing of
investment payments and other cash flows, and the satisfaction of a set of demands for energy
services in all sectors of the economy. For more information see the Appendix section.
4.4 Scenarios
First a reference scenario is run in ETSAP-TIAM that assumes no additional energy efficiency
improvements beyond currently adopted policies. It also contains no additional climate
polices, and no renewable energy targets. HYSOL scenario is then run in ETSAP-TIAM. In both
scenarios, ETSAP-TIAM will then optimize the energy systems based on resource availability,
existing infrastructure stock, and prices given the exogenous constraints.
18
Energy Technology System Analysis Program TIMES Integrated Assessment Model (ETSAP-TIAM).
ETSAP-TIAM Regions
AFR Africa
AUS Australia & NZ
CAN Canada
CHI China
CSA Central and South America
EEU Eastern Europe
FSU Former Soviet Union
IND India
JPN Japan
MEA Middle East
MEX Mexico
ODA Other Developing Asia
SKO South Korea
USA United States
WEU Western Europe
D6.1: Socio-economic assessment and energy system analysis
45
The following scenarios are constructed:
Reference: This scenario reflects the development of the global, regional and sectoral
energy demand if current technological trends and policies are continued. This pathway
will take into account current technological mixes, performance and cost data for
conventional technologies, and default assumptions for Autonomous Energy Efficiency
Improvement (AEEI). It also takes into account the current carbon price, holding it constant
until 2050. It does not take into consideration any major energy efficiency improvements
and policy interventions beyond what have already been planned.
HYSOL: This scenario considers the elements mentioned in the reference scenario,
additionally, it will explicitly take into account the CSP installed capacity targets for Mexico
(MEX), Africa (AFR) and Western Europe (WEU), in this way we will study how the energy
system react under a forced implementation of the HYSOL.
HYSOL high penetration: This scenario multiplies the CSP installed capacity targets of each
region/country studied by factor ten, except for WEU which its CSP target is multiplied by
factor 6, this is due to the lack of resources available in this region, see section 4.5.1. This
scenario is interesting because it will show, for instance, which power plants will be
replaced when a high penetration of HYSOL comes into place.
4.4.1 Carbon Price
The (World Bank, 2014) released a report that documented the current state of carbon taxes
and carbon Emission Trading Schemes (ETS) and their price levels. Further information on ETS
was taken from the International Carbon Action Partnership (ICAP, 2015).
Carbon taxes are summarized in Table 4.1, and are applied in ETSAP-TIAM for the periods
2015-2050 in all the scenarios. See more about the assumptions behind carbon pricing in the
Appendix.
Table 4.1: Current carbon prices in 2005 USD/tCO2eq
Region Industry Power Heat Buildings Transport (excluding Aviation)
Oil Coal
MEX - - - - - 0.62 1.00
WEU 7.02 11.35 7.02 - 5.43 - -
AFR - - - - - - -
Sources: (ICAP, 2015) and (World Bank, 2014).
For the HYSOL scenario, the following approach was considered: Identical carbon prices as in
the Reference scenario were considered. Additionally, specific renewable energy targets were
taken into account for the studied regions/countries. These targets focus on the installed
capacity for concentrated solar thermal technologies as outlined in
Table 4.2.
D6.1: Socio-economic assessment and energy system analysis
46
Table 4.2: IRENA's Renewable Energy Roadmap - REmap Countries Renewable Energy Targets, 2014
Country Installed capacity of CSP (GW19
) Year
Mexico20
0,63 2018
Western Europe21
1,14 2020
Africa22
5,1 2020
Source: (IRENA, 2014a).
4.5 Energy system assessment
4.5.1 Availability of resources
The future deployment of CSP technologies will be limited to regions with at least an average
Direct Normal Irradiance class (DNI) of 2 000 kWh/m2 year (Trieb et al., 2009), see Figure 4.3.
Additionally, the CSP potential will be constrained even further due to land availability, e.g.
Farming land, protected areas and other areas of exclusion which could eventually be
considered as competitors of CSP plants, in terms of land use, see Figure 4.4.
Figure 4.3: Annual average DNI (KWh/m2 year)
19
Gigawatt. 20
According to IRENA, (2014a) this value represent both CSP and PV capacities aggregated. Here we assumed that 0,63GW corresponds to only CSP installed capacity. 21
The CSP targets of Western Europe correspond to Italy and France respectively with 0.60 and 0.54 GW of installed capacity in 2020. 22
To estimate the total installed capacity target for Africa, target values from Egypt (1.1GW), Morocco (2GW assumed only for CSP) and Nigeria (2GW) were aggregated.
D6.1: Socio-economic assessment and energy system analysis
47
Note: Resulting map of the annual sum of direct normal irradiance for potential global CSP
sites as identified within the EU-project REACCESS.
Source: (Trieb et al., 2009).
According to (Trieb et al., 2009) Mexico has a technical CSP potential of 146 430 PJ23/year
while India has a technical CSP potential of 39 341 PJ/year. Africa has the larger technical CSP
potential among the REACCESS24 world regions.
Figure 4.4: Worldwide exclusion of sites for CSP plant construction
Note: Dark areas indicate suitable sites from the point of view of land suitability.
Source: (Trieb et al., 2009).
This section compares solar energy and land resources availability based on the analysis made
by (Trieb et al., 2009) and by (Biberacher, 2010). For the first case, the methodology of site
exclusion was described in (Trieb et al., 2005). Exclusion criteria comprise: slope > 2.1 %, land
cover like permanent or non-permanent water, forests, swamps, agricultural areas, shifting
sands including a security margin of 10 km, salt pans, glaciers, settlements, airports, oil or gas
fields, mines, quarries, desalination plants, protected areas and restricted areas. Spatial
resolution of the data was 1 km². Similar approach was used in (Biberacher, 2010) where the
main differences are described as follows: instead of constraint the CSP availability to DNI
above 2 000 kWh/m2 year, it was constraint to above 1 800 kWh/m2 year. Additionally,
suitable areas in each of the regions of the model and maximum production of solar electricity
23
Petajoule. 24
REACCESS project, Risk of Energy Availability: Common Corridors for Europe Supply Security
http://reaccess.epu.ntua.gr/Home.aspx
D6.1: Socio-economic assessment and energy system analysis
48
in these areas was considering a 16% solar to electricity efficiency while in (Trieb et al., 2009)
solar to electricity efficiency considered corresponds to 12%, moreover, this factor was
multiplied by the land use factor (37% in average for CSP parabolic trough). Therefore, the land
use efficiency calculated is 4.4% as shown in Table 4.3. These differences in the calculations of
land availability could explain the difference of technical potential for the CSP technologies as
outlined in Table 4.4.
Table 4.3: Comparison of criteria between Biberacher (2010) and Trieb et al (2009) study
Unit (RSA, 2010) (Trieb et al., 2009)
Minimum DNI (kWh/m2) >1 800 >2 000
Land use criteria % >2.1 >2.1
Electric efficiency % 16 12
Land use factor % N.A 37
Land use efficiency % N.A 4.4
Sources: (Biberacher, 2010) and (Trieb et al., 2009).
Table 4.4: Comparison between Biberacher (2010) and Trieb et al (2009) study
Region
DNI Potential
(PJ/year)25
DNI Potential
(PJ/year)26
Difference
(%)
Mexico 146 430 161 000 -9.95
India 39 341 8 700 77.89
USA 373 334 30 000 91.96
China 453 006 217 000 52.10
Africa 5 253 732 1 758 000 66.54
Australia 2 511 360 819 000 67.39
Central and South America 446 371 185 000 58.55
Central Asia, Caucasus 54 695 N.A N.C
Canada 0 142 000 N.C
Japan 0 80 N.C
Middle East 1 046 300 570 000 45.52
Other Developing Asia 272 020 143 000 47.43
Other East Europe 76 130 -71.96
Russia 0 539 000 N.C
EU27 8 672 240 97.23
Total 10 605 337 4 573 150 56.88
Sources: (Biberacher, 2010) and (Trieb et al., 2009).
25
Trieb et.al 2009. 26
Research Studies Austria (RSA) 2010.
D6.1: Socio-economic assessment and energy system analysis
49
N.C: Not Comparable
N.A: Not Available
Biberacher's approach was used in ETSAP-TIAM because is considered to be more conservative
than Trieb's approach. Therefore, these potentials are considered to be upper bound for our
modelling exercise.
4.6 Modelling
4.6.1 CSP technology overview
CSP is a power generation technology that uses mirrors to concentrate the sun’s rays and, in
most of today’s CSP systems, to heat a fluid that is used to produce steam. The steam is then
used to drive a conventional steam turbine and generate power in the same way as
conventional thermal power plants that use steam cycles. However, other concepts are being
explored and not all future CSP plants will necessarily use a steam cycle. CSP is at its infancy in
terms of deployment, with total installed capacity at the end of 2014 of around 5 gigawatts
(GW). New capacity additions in 2013 were estimated to have reached 0.9 GW, a new record.
Total installed capacity has grown rapidly since 2010, but policy uncertainty has reduced
growth prospects in key markets (IRENA, 2014b).
4.6.2 HYSOL implemented in ETSAP-TIAM
The HYSOL is a hybrid CSP parabolic trough plant in which the input parameters for the model
are outlined in Table 4.5.
Table 4.5: Inputs parameters for the HYSOL in ETSAP-TIAM
Input parameters
Start 2015
Life 25 years
Annual availability factor 0.99
Investment cost 2015 7 795 MUSD2014/GW
Investment cost 2020 5 725 MUSD2014/GW
Investment cost 2030 4 345 MUSD2014/GW
Investment cost 2040 3 145 MUSD2014/GW
Fix O&M cost 2015 106 MUSD2014/GW
Fix O&M cost 2020 95 MUSD2014/GW
Fix O&M cost 2030 86 MUSD2014/GW
Fix O&M cost 2040 77 MUSD2014/GW
Note: These values of investment and fix O&M cost are input in the model for all the regions
studied.
The learning curve cost for HYSOL was calculated based on (Viebahn et al., 2011). Multipliers
for the total investment and fix O&M costs were obtained by assuming linearity in the curves
D6.1: Socio-economic assessment and energy system analysis
50
depicted in the Figure 4.5. Then these multipliers were used to obtain the total investment and
fix O&M costs for the HYSOL as outlined in Table 4.5.
Figure 4.5: Overall learning curve and the contributions of the main parts for CSP plant in Spain
Source: (Viebahn et al., 2011).
4.7 Results
This section presents results on annual electricity production by fuel, total system cost and
direct CO2 emissions for Mexico, Western Europe and Africa.
4.7.1 Annual electricity production
In the Mexican reference scenario, HYSOL will not be deployed under normal market
conditions as depicted in Figure 4.6.
In HYSOL high penetration scenario, HYSOL replaces gas and oil power plants as illustrated in
Figure 4.7, this is valid for the midterm. Additionally, in the long term the model goes for
nuclear energy and geothermal, this is mainly due to the fact that Mexico has a large
geothermal potential and its decreases in future technology cost.
D6.1: Socio-economic assessment and energy system analysis
51
Figure 4.6: Electricity production by fuel in Mexico, reference scenario
Figure 4.7: Electricity production by fuel in Mexico, HYSOL high penetration scenario
In the reference scenario, HYSOL will not be deployed in Western Europe under normal market
conditions. In the midterm and long term, a significant deployment of wind and geothermal
plants are envisaged, while coal, nuclear, gas and oil power plants will be considerably reduced
as illustrated in Figure 4.8. HYSOL deployment is limited in WEU due to lack of land and DNI
availability. Therefore, HYSOL has a negligible impact on primary electricity production in this
region as shown in Figure 4.9.
0
500
1000
1500
2000
2500
3000
2010 2020 2030 2050
Pri
mar
y e
lect
rici
ty p
rod
uct
ion
(P
J)
Reference MEX
Wind
Solar Thermal
Solar PV
Nuclear
Hydro
Geo, Tidal and Wave
Gas and Oil
Coal
CH4 Options
Biomass
0
500
1000
1500
2000
2500
3000
2010 2020 2030 2050
Pri
mar
y e
lect
rici
ty p
rod
uct
ion
(P
J)
HYSOL high penetration MEX
Wind
Solar Thermal
Solar PV
Nuclear
Hydro
Geo, Tidal and Wave
Gas and Oil
Coal
CH4 Options
Biomass
D6.1: Socio-economic assessment and energy system analysis
52
Figure 4.8: Electricity production by fuel in Western Europe, reference scenario
Figure 4.9: Electricity production by fuel in Western Europe, HYSOL high penetration scenario
In the reference scenario, HYSOL will not be deployed in Africa under normal market
conditions as shown in Figure 4.10.
In HYSOL high penetration scenario, the deployment of HYSOL will help to phase-out gas and
oil power plants in the long term. In addition, HYSOL will partially replace hydro, geothermal
and wind power as illustrated in Figure 4.11.
0
2000
4000
6000
8000
10000
12000
14000
16000
2010 2020 2030 2050
Pri
mar
y e
lect
rici
ty p
rod
uct
ion
(P
J)
Reference WEU
Wind
Solar Thermal
Solar PV
Nuclear
Hydro
Geo, Tidal and Wave
Gas and Oil
Coal
CH4 Options
Biomass
0
2000
4000
6000
8000
10000
12000
14000
16000
2010 2020 2030 2050
Pri
mar
y e
lect
rici
ty p
rod
uct
ion
(P
J)
Hysol high penetration WEU
Wind
Solar Thermal
Solar PV
Nuclear
Hydro
Geo, Tidal and Wave
Gas and Oil
Coal
CH4 Options
Biomass
D6.1: Socio-economic assessment and energy system analysis
53
Figure 4.10: Electricity production by fuel in Africa, reference scenario
Figure 4.11: Electricity production by fuel in Africa, HYSOL high penetration scenario
4.7.2 Total system cost
The deployment of HYSOL has neither negative nor positive effect in the total system cost, this
is valid for all the regions analysed as outlined in
0
1000
2000
3000
4000
5000
6000
7000
2010 2020 2030 2050
Pri
mar
y e
lect
rici
ty p
rod
uct
ion
(P
J)
Reference AFR
Wind
Solar Thermal
Solar PV
Nuclear
Hydro
Geo, Tidal and Wave
Gas and Oil
Coal
CH4 Options
Biomass
0
1000
2000
3000
4000
5000
6000
7000
8000
2010 2020 2030 2050
Pri
mar
y e
lect
rici
ty p
rod
uct
ion
(P
J)
Hysol high penetration AFR Wind
Solar Thermal
Solar PV
Nuclear
Hydro
Geo, Tidal and Wave
Gas and Oil
Coal
CH4 Options
Biomass
D6.1: Socio-economic assessment and energy system analysis
54
Table 4.6. However, it may have an impact at power system level which it needs to be further
study.
Table 4.6: Total system cost in billion USD2005
Region Scenario Total Index27
AFR REFERENCE 19 717 1.00
AFR HYSOL 19 735 1.00
AFR HYSOL10 19 856 1.01
MEX REFERENCE 6 511 1.00
MEX HYSOL 6 508 1.00
MEX HYSOL1028
6 520 1.00
WEU REFERENCE 33 957 1.00
WEU HYSOL 33 961 1.00
WEU HYSOL629
33 968 1.00
4.7.3 Direct CO2 emissions
At system level, the impact of HYSOL on total direct CO2 emissions abatement is negligible as
outlined in Table 4.7.
Table 4.7: Total direct CO2 emissions in Gt of CO2.
Region Scenario 2050 Index205030
AFR REFERENCE 2 1.00
AFR HYSOL 2 1.00
AFR HYSOL10 2 1.00
MEX REFERENCE 1 1.00
MEX HYSOL 1 1.00
MEX HYSOL10 1 0.98
WEU REFERENCE 4 1.00
WEU HYSOL 4 0.99
WEU HYSOL6 4 0.99
27
This index shows total system cost from the HYSOL scenarios divided by the base scenario. 28
HYSOL10 stands for multiply country specific installed capacity CSP targets by ten. 29
HYSOL6 stands for multiply country specific installed capacity CSP targets by six (valid just for WEU). 30
Index2050 indicate the impact of HYSOL on direct CO2 emissions abatement.
D6.1: Socio-economic assessment and energy system analysis
55
4.8 Key findings
Despite the limitations of the ETSAP-TIAM model regarding time and geographical resolution,
there are interesting findings from this exercise which are highlighted below.
General findings:
The base scenario shows that HYSOL will not be deployed under normal market conditions.
This is due to the high investment cost of this technology. Therefore, HYSOL will need to be
supported;
the deployment of HYSOL has neither negative nor positive effect in the total system cost,
this is valid for all the regions analysed;
high deployment of HYSOL has a negligible impact on direct C02 emissions at total energy
system level.
Country-specific findings:
In Africa, the deployment of HYSOL will help to phase-out gas and oil power plants in the
long-term;
in Mexico, the deployment of HYSOL will help to decrease gas and oil power plants in the
mid-term;
in Western Europe, the deployment of HYSOL will have negligible impact on the power
system. This is due to the limited solar potential and land availability of the region.
D6.1: Socio-economic assessment and energy system analysis
56
5 Conclusion
The socio-economic analysis has shown that HYSOL is not economically feasible when it is
compared vs OCGT/CCGT under normal market conditions in KSA and Mexico, while this
technology is economically feasible for Chile in all the scenarios investigated, and it is partially
feasible for RSA when it competes with OCGT. This is due to the significantly high NG price in
Chile and in RSA respectively, which it corresponds to approximately three times as much as in
KSA or Mexico, which makes Chile and RSA attractive markets for the investment in HYSOL.
This analysis also has shown that the interest rate is critical for HYSOL solutions due to the high
initial investment. In Base Case a rate of calculation of 4% p.a. has been assumed, that
corresponds to typical socio-economic conditions. When assuming a higher rate of interest of
10% p.a., similar to a corporate economic situation, it is seen from the sensitivity analysis that
power production costs (LCOE) are increased substantially. In particular the HYSOL solution is
very sensitive to changes in the interest rate.
CO2 emission costs acts significantly in favour of HYSOL solutions. As seen from the sensitivity
analysis, in particular an OCGT plant solution is strongly exposed to potential rising CO2
emission costs.
Additionally, the energy system analysis has shown that HYSOL is not economically feasible
under current market conditions. However, when this technology is highly deployed, it
contributes to phase-out gas and oil power plants within the energy systems studied.
D6.1: Socio-economic assessment and energy system analysis
57
6 References
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[Accessed 2015 April 9].
Anon., n.d. Powermag. [Online]
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perspective/?pagenum=1
[Accessed 9 April 2015].
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Bataille, 2005. Design and application of a technologically explicit hybrid energy-economy
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Biberacher, 2010. Model benchmark with GIS data, Salzburg: Research Studios Austria
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Bierzwinsky, R. J. D. F. J., 2014. Chadbourne. [Online]
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D6.1: Socio-economic assessment and energy system analysis
60
7 Appendix
7.1 Section A: Energy system analysis
7.1.1 Calibration of TIAM model
The calibration of the ETSAP-TIAM model was done by comparing the reference scenario
versus historical data from the International Energy Agency (IEA) for Mexico and Western
Europe.
For Mexico, the total electricity production difference is negligible, approximately 1 % of
difference in the results obtained by the ETSAP-TIAM model compare with the data from IEA
2010. Therefore, the ETSAP-TIAM model is well calibrated since the values for electricity
production are in a match with the historical values, as it is depicted in the figures below.
Figure A: comparison between historical data from (IEA, 2010b) vs. ETSAP-TIAM model, Mexico
7.1.2 Model Structure
As ETSAP-TIAM is based on the TIMES equations, it is a perfect foresight, linear optimization
model (ETSAP-TIAM optimizes all time periods simultaneously). The objective function that is
maximized is the discounted net present value of the total surplus for the entire world. The
surplus maximization can be subject to many exogenously-defined constraints on a regional,
sectoral or global basis, such as supply bounds (in the form of detailed supply curves) for the
primary resources, technical constraints governing the creation, operation, and abandonment
of each technology, balance constraints for all energy forms and emissions, timing of
investment payments and other cash flows, and the satisfaction of a set of demands for energy
services in all sectors of the economy.
As an integrated energy system model, ETSAP-TIAM is built to represent the total energy
chain, including energy extraction, conversion and demand (e.g., fossil and renewable
0
200
400
600
800
1000
1200
TIAM IEA
An
nu
al e
lect
rici
ty p
rod
uct
ion
[P
J]
Electricity production by fuel in Mexico 2010 Wind
Solar Thermal
Solar PV
Nuclear
Hydro
Geo and Tidal
Gas and Oil
Coal
CH4 Options
Biomass
D6.1: Socio-economic assessment and energy system analysis
61
resources), potentials of storage of CO2 (which comes into play with a carbon price and can be
adjusted via cost parameters) and region- specific demand developments. The region and
sector-specific demands for end-use energy and industrial products are driven by socio-
economic parameters which are described below. The model contains explicit detailed
descriptions of hundreds of technologies as well as hundreds of energy, emission and demand
flows within each region (region-specific parameters can be defined), logically interconnected
to form a Reference Energy System (Figure B). Such technological detail allows precise tracking
of optimal capital turnover, and provides a precise description of technology and fuel
competition. The long-distance trade of energy between the regions of ETSAP-TIAM is
endogenously modelled for coal, natural gas (gaseous or liquefied), crude oil, various refined
petroleum products, and biofuels. Global and regional (partial agreement) GHG emission
trading is also possible. ETSAP-TIAM is driven by a set of demands for energy services in
agriculture, residential buildings, commercial buildings, industry, and transportation. Each
technology has a hurdle rate that varies from 5% to 20%, depending on the sector. The hurdle
rate is used to convert the capital cost in an annual cash flow: discounted multi-year interest
rate payments are included when calculating an annual payment for an investment and
payback time (a technology with a high hurdle rate means a short payback rate is required,
while a technology with a low hurdle rate allows a longer payback time. Demands for energy
services are specified by the user in the Reference (BAU) scenario, and each have its own price
elasticity. Each demand may vary endogenously in alternative scenarios, in response to
endogenous price changes. Because energy services respond to changes in their respective
prices through end-use price elasticities within ETSAP-TIAM, savings of energy demand and
corresponding cost variations are accounted for in the objective function as well.
The model's variables include the investments, capacities, and activity levels of all technologies
at each period of time, as well as the amounts of energy, material, and emission flows in and
out of each technology, and the quantities of traded energy between all pairs or regions. For
sectors that use non-storable energy (electricity, heat), the flow variables are defined for each
of six time-slices: three seasons (summer, winter, autumn/spring) times two diurnal (day,
night) divisions. ETSAP-TIAM is a partial equilibrium model, and although it does not include
macroeconomic variables beyond the energy sector, there is evidence that accounting for
price elasticity of demands captures the majority of the feedback effects from the economy to
the energy system (Bataille, 2005) (Labriet et al., 2012) (Scheper & Kram, 1994).
D6.1: Socio-economic assessment and energy system analysis
62
Figure B. Reference Energy System within ETSAP-TIAM. Technological efficiencies are included in the Industrial, Agriculture, Commercial, Residential, and Transport Technology boxes. Other efficiency adjustments are possible within the fuel production chains
7.1.3 CO2 tax in ETSAP-TIAM
While ETSAP-TIAM is capable of simulating cap-and-trade carbon markets such as the ETS, for
simplicity, carbon markets were modelled as a tax by taking the current carbon price. Some
regions have several carbon prices applying to different sectors, and this was retained in the
ETSAP-TIAM input. Mexico has a carbon tax applying to fossil fuels, where the tax is the
difference between the emissions versus emissions from natural gas, in effect, creating a tax
on emissions from petroleum and coal. For Mexico, we applied a 25% ratio for petroleum, and
a 40% ratio for coal, representative of the approximate ratios in emissions per unit of energy
relative to natural gas. In the case where a country has both an upper and lower bound for
carbon, then the upper bound was used.
The carbon prices were then aggregated to the ETSAP-TIAM regions. This aggregation was
done by computing the nation’s share of energy (and cement production) carbon emissions
Climate
Module
Atm. Conc.
ΔForcing
ΔTemp
Used for
reporting &
setting
targets
Biomass
Potential
Renewable
Potential
Nuclear
Fossil Fuel
Reserves
(oil, coal, gas)
ExtractionUpstream
Fuels
Trade
Secondary
Transformation
OPEC/
NON-OPEC
regrouping
Electricity
Fuels
Electricity
Cogeneration
Heat
Hydrogen production
and distribution
End Use
Fuels
Industrial
Service
CompositionAuto Production
Cogeneration
Carbon
captureCH4 options
Carbon
sequestration
Terrestrial
sequestration
Landfills ManureBio burning, rice,
enteric fermWastewater
CH4 options
N2O options
CH4 options
OI****
GA****
CO****
Trade
ELC***
WIN SOL
GEO TDL
BIO***
NUC
HYD
BIO***
HETHET
ELCELC
SYNH2
BIO***
CO2
ELC
GAS***
COA***
Industrial
Tech.
Commercial
Tech.
Transport
Tech.
Residential
Tech.
Agriculture
Tech.I***
I** (6)T** (16)R** (11)C** (8)A** (1)
INDELC
INDELC
IS**
Demands
IND*** COM***AGR*** TRA***RES***
Non-energy
sectors (CH4)
OIL***
D6.1: Socio-economic assessment and energy system analysis
63
relative to the total emissions from it corresponding ETSAP-TIAM region. The carbon price was
then converted to 2005 US dollars31 and scaled by this amount.
7.1.4 Flow diagram in ETSAP -TIAM
The Figure C represents the flow diagram for the HYSOL, where the input commodities are
electricity from the sun (ELCSOL) and electricity from biogas (ELCBGS) while the output
commodity is electricity centralized (ELCC). From a modelling viewpoint, the HYSOL has been
implemented as a CSP parabolic trough plus a thermal storage unit of 12 hours, and a backup
capacity (50 MW gas turbine), an intermediate unit that aggregate the output commodities
from the CSP plus storage (ELCCSP) and the backup capacity (ELCB) was considered, the output
commodity of this "non-physical" unit corresponds to ELCC. Thus, it will be possible to
determinate the electricity generation contribution of the backup capacity during the lifetime
of the HYSOL.
Figure C: Flow diagram for the HYSOL (own source)
Note: This flow diagram represents the electricity flows in ETSAP-TIAM, and is not
representative of a process flow. Thus, heat flows such as heat recovered from the gas turbine
which it is sent later on to the heat storage is not supposed to be represented on the flow
diagram.
There are three mathematical relations that the HYSOL model must comply with in ETSAP-
TIAM, these are the following:
𝑪𝑨𝑷𝑪𝑺𝑷+𝒔𝒕𝒐𝒓𝒂𝒈𝒆 = 𝟐 ∗ 𝑪𝑨𝑷𝑩𝒂𝒄𝒌𝒖𝒑 1
31 Exchange rates from:
https://www.ecb.europa.eu/stats/exchange/eurofxref/html/eurofxref-graph-usd.en.html http://www.xe.com/ http://www.bankofcanada.ca/rates/exchange/daily-converter/
Intermediate Backup capacity
CSP + storage
ELCSOL
ELCBGS
ELCCSP
ELCB
ELCC
ELCNGA
D6.1: Socio-economic assessment and energy system analysis
64
𝑨𝑪𝑻𝑪𝑺𝑷+𝒔𝒕𝒐𝒓𝒂𝒈𝒆 ≤ 𝑴𝒂𝒙𝑷𝒐𝒕𝒆𝒏𝒕𝒊𝒂𝒍 2
𝑨𝑪𝑻𝑩𝒂𝒄𝒌𝒖𝒑 ≤ 𝑴𝒂𝒙𝑩𝒊𝒐𝒈𝒂𝒔 𝒑𝒐𝒕𝒆𝒏𝒕𝒊𝒂𝒍 3
The equation 1 establishes a relation between the power block capacity (100 MW steam
turbine), which it is been feed by the thermal storage and the solar field, and the backup
capacity (50 MW gas turbine). The equation 2 limits the generation of the CSP plus storage
plant to a maximum annual value by taking into account both land availability and direct
normal solar irradiance (Trieb et al., 2009). Finally, the equation 3 limits the generation of the
biogas turbine (backup capacity) to an upper limit.
7.2 Section B: Socio-economic feasibility assessment
D6.1: Socio-economic assessment and energy system analysis
65
7.2.1 Power price composition Mexico
LCOE results based on design point assumptions are presented below with a breakdown or
split into its components related to respectively Investment, O&M, and fuel cost parts.
CO2 emission costs of 0 USD/tCO2eq emitted is assumed:
HYSOL Table M MEX HYSOL alternative: Electricity production cost (LCOE on socio economic basis) for
'design basis' assumptions split on contributions from the Investment, O&M, and Fuel Cost
parts to the total cost. Natural gas has been assumed for the HYSOL GT component.
LCOE on socio-economic basis for MEX HYSOL
OCGT Table O MEX 150MW OCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and
Fuel Cost parts to the total cost. OCGT capacity: 150MW.
CCGT Table P MEX 150MW CCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and
Fuel Cost parts to the total cost. CCGT capacity: 150MW.
CO2 emission costs of 40 USD/tCO2eq emitted is included in the NG fuel costs shown:
HYSOL Table Q MEX HYSOL alternative: Electricity production cost (LCOE on socio economic basis) for
'design basis' assumptions split on contributions from the Investment, O&M, and Fuel Cost parts
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
75.55 100.0% 53.70 71.1% 8.76 11.6% 13.09 17.3%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
51.61 100.0% 7.89 15.3% 1.29 2.5% 42.43 82.2%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
35.95 100.0% 9.48 26.4% 1.92 5.3% 24.55 68.3%
at 'design basis point' data Investment O & M Fuel costs
Total
D6.1: Socio-economic assessment and energy system analysis
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to the total cost. Biogas use has been assumed for the HYSOL GT component.
OCGT Table R MEX 150MW OCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost. OCGT capacity: 150MW. CO2 emission costs are included in the
fuel costs shown.
CCGT Table S MEX 150MW CCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost. CCGT capacity: 150MW. CO2 emission costs are included in the
fuel costs shown.
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
83.58 100.0% 53.70 64.2% 8.76 10.5% 21.12 25.3%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
77.65 100.0% 7.89 10.2% 1.29 1.7% 68.47 88.2%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
51.02 100.0% 9.48 18.6% 1.92 3.8% 39.62 77.7%
at 'design basis point' data Investment O & M Fuel costs
Total
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7.2.2 Power price composition for Chile
LCOE results based on Design Point assumptions are presented below with a breakdown or
split into its components related to respectively Investment, O&M, and Fuel cost parts.
CO2 emission costs of 0 USD/tCO2eq emitted is assumed:
HYSOL Table T CHI HYSOL alternative: Electricity production cost (LCOE on socio economic basis) for
'design basis' assumptions split on contributions from the Investment, O&M, and Fuel Cost
parts to the total cost. Natural gas has been assumed for the HYSOL GT component.
OCGT Table U CHI 150MW OCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and
Fuel Cost parts to the total cost. OCGT capacity: 150MW.
CCGT Table V CHI 150MW CCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and
Fuel Cost parts to the total cost. CCGT capacity: 150MW.
CO2 emission costs of 40 USD/tCO2eq emitted is included in the NG fuel costs shown:
HYSOL Table W CHI HYSOL alternative: Electricity production cost (LCOE on socio economic basis) for
'design basis' assumptions split on contributions from the Investment, O&M, and Fuel Cost parts
to the total cost. Biogas use has been assumed for the HYSOL GT component.
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
89.05 100.0% 54.51 61.2% 9.11 10.2% 25.43 28.6%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
160.38 100.0% 8.85 5.5% 1.20 0.8% 150.33 93.7%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
99.79 100.0% 10.47 10.5% 1.75 1.7% 87.58 87.8%
at 'design basis point' data Investment O & M Fuel costs
Total
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OCGT Table X CHI 150MW OCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost. OCGT capacity: 150MW. CO2 emission costs are included in the fuel
costs shown.
CCGT Table Y CHI 150MW CCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost. CCGT capacity: 150MW. CO2 emission costs are included in the fuel
costs shown.
7.2.3 Power price composition for KSA
HYSOL Table Z KSA HYSOL alternative: Electricity production cost (LCOE on socio economic basis)
for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost.
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
93.73 100.0% 54.51 58.2% 9.11 9.7% 30.11 32.1%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
188.07 100.0% 8.85 4.7% 1.20 0.6% 178.02 94.7%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
115.92 100.0% 10.47 9.0% 1.75 1.5% 103.71 89.5%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
81.09 100.0% 60.91 75.1% 12.13 15.0% 8.05 9.9%
at 'design basis point' data Investment O & M Fuel costs
Total
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OCGT Table Z.1 KSA 130MW OCGT reference: Electricity production cost (LCOE on socio
economic basis) for 'design basis' assumptions split on contributions from the Investment,
O&M, and Fuel Cost parts to the total cost. OCGT capacity: 130MW.
CCGT Table Z.2 KSA 130MW CCGT reference: Electricity production cost (LCOE on socio
economic basis) for 'design basis' assumptions split on contributions from the Investment,
O&M, and Fuel Cost parts to the total cost. CCGT capacity: 130MW.
Table Z illustrates, as expected, that power production costs from the KSA HYSOL plant are
dominated by the investment cost component. On average for the period analysed of about
75% of the total electricity costs relates to the initial investment, whereas the fuel cost
component only contributes about 10% to the total costs. Compared to results for OCGT and
CCGT plants shown in Table Z.1 and Table Z.2, this illustrates that HYSOL plants are less
exposed and less vulnerable to gas price (and CO2 emission cost) uncertainty.
7.2.4 Power price composition for RSA
LCOE results based on Design Point assumptions (shown as yellow and black points in Figures
1-4) are presented below with a breakdown or split into its components related to respectively
Investment, O&M, and Fuel cost parts.
CO2 emission costs of 0 $/ton CO2 emitted is assumed:
HYSOL Table 8 RSA HYSOL alternative: Electricity production cost (LCOE on socio economic basis)
for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost.
OCGT Table 9 RSA 150MW OCGT reference: Electricity production cost (LCOE on socio economic
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
52.66 100.0% 8.31 15.8% 2.30 4.4% 42.05 79.8%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
39.93 100.0% 10.16 25.4% 3.41 8.6% 26.36 66.0%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
at 'design basis point' data Investment O & M Fuel costs
Total
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
66.78 100.0% 48.27 72.3% 2.12 3.2% 16.39 24.5%
D6.1: Socio-economic assessment and energy system analysis
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basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and
Fuel Cost parts to the total cost. OCGT capacity: 150MW.
CCGT Table 10 RSA 150MW CCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and
Fuel Cost parts to the total cost. CCGT capacity: 150MW.
CO2 emission costs of 40 $/ton CO2 emitted are included in the NG fuel costs shown:
HYSOL Table 11 RSA HYSOL alternative: Electricity production cost (LCOE on socio economic basis) for
'design basis' assumptions split on contributions from the Investment, O&M, and Fuel Cost parts
to the total cost. Biogas use has been assumed for the HYSOL GT component.
OCGT Table 12 RSA 150MW OCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost. OCGT capacity: 150MW. CO2 emission costs are included in the
fuel costs shown.
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
84.39 100.0% 7.23 8.6% 1.00 1.2% 76.15 90.2%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
53.52 100.0% 8.69 16.2% 1.49 2.8% 43.34 81.0%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
at 'design basis point' data Investment O & M Fuel costs
Total
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
72.39 100.0% 48.27 66.7% 2.12 2.9% 22.00 30.4%
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
110.44 100.0% 7.23 6.6% 1.00 0.9% 102.20 92.5%
at 'design basis point' data Investment O & M Fuel costs
Total
D6.1: Socio-economic assessment and energy system analysis
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CCGT Table 13 RSA 150MW CCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost. CCGT capacity: 150MW. CO2 emission costs are included in the
fuel costs shown.
Table illustrates, as expected, that power production costs from the RSA HYSOL plant are
dominated by the investment cost component. On average for the period analysed of about
75% of the total electricity costs relates to the initial investment, whereas the fuel cost
component only contributes about 10% to the total costs. Compared to results for OCGT and
CCGT plants shown in Table and Table , this illustrates that HYSOL plants are less exposed and
less vulnerable to gas price (and CO2 emission cost) uncertainty.
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
68.35 100.0% 8.69 12.7% 1.49 2.2% 58.17 85.1%
at 'design basis point' data Investment O & M Fuel costs
Total
Kingdom of Saudi Arabia (KSA): Economic
assessment and energy system analysis
Deliverable nº: 6.1.1
EC-GA nº: 308912 Project full title: Innovative Configuration for a Fully
Renewable Hybrid CSP Plant WP: Responsible partner: DTU/MAN/SYS Dissemination level:
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TABLE OF CONTENTS
1 DOCUMENT HISTORY ..................................................................................................... 5
2 EXECUTIVE SUMMARY ................................................................................................... 5
2.1 ABSTRACT ......................................................................................................................... 5
3 FEASIBILITY STUDY ON HYSOL CSP .................................................................................. 6
3.1 INTRODUCTION .................................................................................................................. 6
3.1.1 Example studied .......................................................................................... 6
3.1.2 The HYSOL alternative and competing technology .................................... 7
4 APPROACH AND BASIC ASSUMPTIONS ........................................................................... 7
4.1 ECONOMIC INDICATOR ........................................................................................................ 7
4.2 BASE CASE ASSUMPTIONS ................................................................................................... 7
4.3 BASE CASE FOR KSA HYSOL PLANT ...................................................................................... 8
4.4 BASE CASE OVERVIEW AND ISSUES ADDRESSED VIA SENSITIVITY ANALYSES ................................... 8
4.5 ELECTRICITY COSTS AS FUNCTION OF LOAD FACTOR AND NG PRICE ............................................. 9
4.6 DESIGN POINT ASSUMPTIONS .............................................................................................. 9
5 HYSOL RELATIVE TO OCGT AND CCGT ........................................................................... 10
5.1 BASIC PRESENTATIONS ...................................................................................................... 10
5.1.1 Assumption on CO2 emission costs .......................................................... 10
5.1.2 Assumption on NG and Biogas price relation ........................................... 11
5.2 RESULTS: HYSOL COMPARED TO OCGT .............................................................................. 11
5.3 RESULTS: HYSOL COMPARED TO CCGT .............................................................................. 13
5.4 POWER PRICE COMPOSITION .............................................................................................. 14
6 SENSITIVITY ANALYSES AND CONCLUSIONS .................................................................. 16
6.1 OVERVIEW OF SENSITIVITY ANALYSES ................................................................................... 16
6.2 CONCLUSIONS ................................................................................................................. 18
7 APPENDIX .................................................................................................................... 19
7.1 ASSUMPTION ON NG AND BIOGAS PRICE RELATION ............................................................... 19
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Acronyms
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1 Document History
Version Status Date
vX.Y Draft day/month/year
vX.Y Final day/month/year
Approval Name Date
Prepared day/month/year
Reviewed day/month/year
Authorised day/month/year
2 Executive Summary
2.1 Abstract
Concentrating Solar Power (CSP) plants utilize thermal conversion of direct solar irradiation. A
trough or tower configuration focuses solar radiation and heats up oil or molten salt that
subsequently in high temperature heat exchangers generate steam for power generation.
High temperature molten salt can be stored and the stored heat can thus increase the load
factor and the usability for a CSP plant, e.g. to cover evening peak demand. In the HYSOL
concept (HYbrid SOLar) such configuration is extended further to include a gas turbine fuelled
by upgraded biogas or natural gas. The optimised integrated HYSOL concept, therefore,
becomes a fully dispatchable (offering firm power) and fully renewable energy source (RES)
based power supply alternative, offering CO2-free electricity in regions with sufficient solar
resources.
The economic feasibility of HYSOL configurations is addressed in this report. The CO2 free
HYSOL alternative is discussed relative to conventional reference firm power generation
technologies. In particular the HYSOL performance relative to new power plants based on
natural gas (NG) such as open cycle or combined cycle gas turbines (OCGT or CCGT) are in
focus. The feasibility of renewable based HYSOL power plant configurations attuned to specific
electricity consumption patterns in selected regions with promising solar energy potentials are
discussed
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3 Feasibility study on HYSOL CSP
Feasibility study on HYSOL CSP configurations with High Temperature Storage and NG/Bio-gas
fuelled Gas Turbine providing Fully Dispatchable and Renewable Power Supplies.
3.1 Introduction
Concentrating Solar Power (CSP) plants utilize thermal conversion of direct solar irradiation. A
trough or tower configuration focus solar radiation and heat up oil or molten salt that
subsequently in high temperature heat exchangers generate steam for power generation.
High temperature molten salt can be stored (HTS) and the stored heat can thus increase the
load factor and the usability for a CSP plant, e.g. to cover night (peak) demand. In the HYSOL
concept (HYbrid SOLar) such configuration is extended further to include a gas turbine fuelled
by upgraded biogas or natural gas. The optimised integrated HYSOL concept, therefore,
becomes a fully dispatchable (offering firm power) and a fully renewable energy (RES) based
power supply alternative, offering CO2-free electricity in regions with sufficient solar
resources.
The economic feasibility of HYSOL configurations is addressed. The CO2 free HYSOL alternative
is discussed relative to conventional reference firm power generation technologies. In
particular the HYSOL performance relative to new power plants based on natural gas (NG) such
as open cycle or combined cycle gas turbines (OCGT or CCGT) are in focus. The feasibility of
renewable based HYSOL power plant configurations attuned to specific electricity consumption
patterns in selected regions with promising solar energy potentials are discussed.
3.1.1 Example studied
The analytical approach used is illustrated for a HYSOL configuration optimised to conditions
seen in the Kingdom of Saudi Arabia (KSA). The HYSOL Power Plant studied has been attuned
to solar potentials and power system characteristics resembling conditions in the Kingdom of
Saudi Arabia (KSA).
The KSA HYSOL plant configuration particularizes the basic HYSOL outline by the choices:
- A CSP Tower configuration has been assumed. HYSOL configurations can also be
applied with CSP trough design.
- No biogas plant and biogas supply have been assumed for this KSA case. HYSOL’s
100% renewable configuration would have a biogas plant included and would use biogas
upgraded to NG quality.
The KSA HYSOL configuration analysed uses natural gas (NG) and not biogas based methane,
and may thus not be termed fully renewable, - though being a firm, fully dispatch-able and
mainly renewables based power plant.
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3.1.2 The HYSOL alternative and competing technology
This present analyses compare electricity production costs for a HYSOL plant alternative to
production cost for conventional power plant solutions or reference plants.
In this KSA case it has been assumed that the main competing reference technologies are an
Open Cycle Gas Turbine (OCGT) and an
Combined Cycle Gas Turbine (CCGT)
using natural gas (NG).
4 Approach and basic assumptions
4.1 Economic indicator
Basically a socio-economic approach is applied. And generally main focus is placed on the
economic indicator LCOE (the levelized cost of electricity), and on the sensitivity of the LCOE in
particular to variations in the two parameters:
• load factor or the number of full load hours per year, and the
• price of natural gas (given as the levelized NG price covering the period analysed)
The solar potential and the annual power production heavily impact the HYSOL power plant
economy. And for fossil based competing reference technologies fuel cost and CO2 emission
cost developments constitute important framework conditions. LCOE dependency on in
particular these major parameters will be in focus in this study of (predominantly) renewable
energy source (RES) based HYSOL solutions relative to fossil based conventional reference
power plant solutions.
4.2 Base Case assumptions
For the present socio-economic analyses the following general assumptions have been
adopted as 'Base Case':
Price level: Year 2015
Socio economic rate of calculation (rate of interest): 4 % p.a.
Project base year: 2020
Period analysed: Time period: 2021-2045
Period in years: 25 years
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4.3 Base Case for KSA HYSOL plant
Chosen Base Case for the KSA HYSOL plant annual production, assigned capacity and load
factor are:
Annual electricity production: 812.7 GWh/year
Assigned HYSOL capacity (PH): PH = 130MWel
Annual full load hours (HFLH) and Load factor (LF):
HFLH = 812.7GWh / 130MW = 6251 hours/year
and LF= 6251/8760= 0.714
As mentioned, gas consumed in the KSA HYSOL gas turbine (GT) component is assumed to be
natural gas (NG). The KSA Base Case NG price and the sensitivity variations analysed for the
NG price are:
NG price Base case: 13.65 $/MWh (4$/MMBtu)
Sensitivity: Base Case +/- 20%, +/-40%
Data on investments, operation and maintenance costs for the KSA HYSOL configuration are
found in the Appendix.
4.4 Base Case overview and issues addressed via sensitivity analyses
Electricity production costs (LCOE) are furthermore analysed for its dependence on or
sensitivity to variations in the following parameters:
• Natural Gas price: Sensitivity Base Case -/+40%
• CO2 emission quota market price Base case: 0 $ / ton CO2
Sensitivity: 40 $ / ton CO2
• Capacity assignment: assignment Base case: 130 MW
Sensitivity: 100MW <--> 180MW
• Lifetime of initial investment: Base case: 25 years
Sensitivity: 20 years
• Rate of calculation (interest rate) Base case: 4.0 % p.a.
Sensitivity: 10.0 % p.a.
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• Initial investment (CAPEX) Sensitivity: Base Case +/- 20%
The combined steam turbine (ST) and gas turbine (GT) capacity in the KSA HYSOL configuration
plant has been assigned a total combined capacity of 130MW. The peak power generated by
the plant is limited to 130 MW, and the plant is made to follow a demand curve congruent or
analogous to that of country altogether. This implies that the number of full load hours for the
combined KSA HYSOL configuration can be calculated as 812.7GWh/130MW = 6251
hours/year, and the demand coverage rate is above 99.9%.
4.5 Electricity costs as function of load factor and NG price
In Figures 1-4 results on the LCOE (given along the y-axis) are shown as a function of the
annual load. The annual load or electricity production, - here expressed through its equivalent,
the number of full load hours per year, is shown along the x-axis.
HYSOL plant operation at different load factors is assumed to maintain the relative ST and GT
contribution to the electricity production. Thus, even the annual power production may differ
from the Base Case assumption the %-split of production contributions from the ST and GT
HYSOL plant components is assumed constant. And the share of the annual production based
on gas (via the GT directly and indirectly via GT flue gas heat recovered and utilized by the ST)
is kept constant.
Furthermore, for this feasibility analysis the HYSOL plant operation efficiency is assumed
constant, - even at e.g. lower annual production levels. And gas consumption per MWh
electricity generated, accordingly, is assumed constant and independent of the annual
production. This may be a somewhat rough assumption.
4.6 Design Point assumptions
Assumptions used as basis for optimizing and configuring the HYSOL plant, will in the following
be termed the 'Design Point' data assumptions. Yellow points, 'Design Points', shown in Figures
1-4 represent results for the KSA HYSOL plant assuming Base Case operation conditions. Black
points, correspondingly, represent (OCGT or CCGT) reference technology results based on
equivalent assumptions. Other results presented may thus be considered as sensitivity and
parameter analyses.
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5 HYSOL relative to OCGT and CCGT
5.1 Basic presentations
In what follows the KSA HYSOL plant alternative is compared to competing 'conventional' or
reference plant solutions based on equivalent system framework condition. Benchmarked via
the LCOE the competing technologies are evaluated using equivalent general assumptions. The
so-called Base Case data assumptions form the core for this feasibility comparison. For
selected key parameters LCOE consequences of data deviating from Base Case are covered via
sensitivity analyses.
As mentioned above the competing reference technologies assumed are the Open Cycle Gas
Turbine (OCGT) and the Combined Cycle Gas Turbine (CCGT).
For consistency of the comparison it is assumed, that the average annual electricity production
is the same for the HYSOL alternative and for the reference plants. Furthermore, plants being
compared are assumed to have the same capacity value in the Saudi Arabian power system,
and the plants are assumed to be fully dispatchable (firm power). Thus, all plants are assumed
to be able to occupy the same position of operation in the overall power system dispatch.
Data for the KSA HYSOL alternative and for the assumed KSA OCGT and KSA CCGT reference
power plants are found in the Appendix.
It can be observed from Figures 1-4 that the annual number of full load operation hours for the
HYSOL plant, shown along the x-axis, is extremely important for the electricity production cost
achieved, - and the plant economy. Low annual power production results in high production
costs. For the overall economy of a HYSOL plant, therefore, it is very important to achieve high
annual power production, as the total production costs are much dominated by high initial
investments. Natural gas prices, however, have minor impact on the HYSOL power production
cost due to the relatively low electricity production contribution via the GT part of the KSA
HYSOL configuration.
5.1.1 Assumption on CO2 emission costs
Comparison of HYSOL solutions relative to conventional OCGT and CCGT power plant solutions
are carried out for cases with and without inclusion of an assumed CO2 emission cost. For this
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sensitivity analysis it has been assumed, as an example, that CO2 emission costs amounts to
40$/tonCO2 emitted. For natural gas (NG) this CO2 emission cost is equivalent to 8.17$/MWh
NG. The CO2 emission cost assumed thus rises the NG price with an extra 8.17$/MWh NG.
5.1.2 Assumption on NG and Biogas price relation
It has been assumed that the price of Biogas can be estimated to equal the price of natural gas
(NG) plus the cost for the CO2 emission using the NG.
A CO2 emission cost, as assumed in our case study, of 40$/ton CO2 emitted corresponds to a
rise of the NG price with an extra 8.17$/MWh NG. Thus, for the case of 40$/ton CO2 emitted
this means that the Biogas price will equal the NG price plus 8.17$/MWh NG.
With a NG price of 13.65 $/MWh NG the assumption thus implies:
Biogas price = NG price + 8.17$/MWh
= 13.65 $/MWh + 8.17$/MWh = 21.82$/MWh NG
If it is furthermore assumed that Biogas has zero CO2 emission the economic consequence of
the use of biogas as fuel in HYSOL plant solutions will correspond to fuel costs as for NG plus its
CO2 cost. The fuel price relations for HYSOL, OCGT and CCGT solutions thus correspond to the
NG price including CO2 costs. However in this case the HYSOL solution using Biogas has no
CO2 emission.
The economic calculations shown in Figure 2 and Figure 4 showing power production costs
(LCOE) for the HYSOL solution relative to the OCGT and CCGT solutions, therefore, will hold
also for the case where HYSOL use Biogas (and thus has no CO2 emission) and the OCGT and
CCGT use NG and emit CO2 at a cost of 40$/ton CO2 emitted.
5.2 Results: HYSOL compared to OCGT
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HYSOL and OCGT: Assuming 0 $/ton CO2 emitted
Figure 1 Electricity production costs for Open Cycle Gas Turbine (OCGT) and KSA HYSOL
configuration, as function of load factor and NG price. Assumed: CO2 costs = 0$/tonCO2,
R=4%p.a., Lifetime=25years. Unit: $/MWh el.
HYSOL and OCGT: Assuming 40 $/ton CO2 emitted
Figure 2 Electricity production costs for Open Cycle Gas Turbine (OCGT) and KSA HYSOL
configuration, as function of load factor and NG price. Assumed: CO2 costs = 40$/tonCO2,
R=4%p.a., Lifetime=25years. Unit: $/MWh el.
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5.3 Results: HYSOL compared to CCGT
HYSOL and CCGT: Assuming 0 $/ton CO2 emitted
Figure 3 Electricity production costs for Combined Cycle Gas Turbine (CCGT) and KSA HYSOL
configuration, as function of load factor and NG price. Assumed: CO2 costs = 0$/tonCO2,
R=4%p.a., Lifetime=25years. Unit: $/MWh el.
HYSOL and CCGT: Assuming 40 $/ton CO2 emitted
Figure 4 Electricity production costs for Combined Cycle Gas Turbine (CCGT) and KSA HYSOL
configuration, as function of load factor and NG price. Assumed: CO2 costs = 40$/tonCO2,
R=4%p.a., Lifetime=25years. Unit: $/MWh el.
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5.4 Power price composition
LCOE results based on Design Point assumptions (shown as yellow and black points in Figures
1-4) are presented below with a breakdown or split into its components related to respectively
Investment, O&M, and Fuel cost parts.
CO2 emission costs of 0 $/ton CO2 emitted is assumed:
HYSOL Table 1 KSA HYSOL alternative: Electricity production cost (LCOE on socio economic basis)
for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost.
OCGT Table 2 KSA 130MW OCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and
Fuel Cost parts to the total cost. OCGT capacity: 130MW.
CCGT Table 3 KSA 130MW CCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and
Fuel Cost parts to the total cost. CCGT capacity: 130MW.
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
81.09 100.0% 60.91 75.1% 12.13 15.0% 8.05 9.9%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
52.66 100.0% 8.31 15.8% 2.30 4.4% 42.05 79.8%
at 'design basis point' data Investment O & M Fuel costs
Total
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CO2 emission costs of 40 $/ton CO2 emitted are included in the NG fuel costs shown:
HYSOL Table 4 KSA HYSOL alternative: Electricity production cost (LCOE on socio economic basis) for
'design basis' assumptions split on contributions from the Investment, O&M, and Fuel Cost parts
to the total cost. Biogas use has been assumed for the HYSOL GT component.
OCGT Table 5 KSA 130MW OCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost. OCGT capacity: 150MW. CO2 emission costs are included in the
fuel costs shown.
CCGT Table 6 KSA 130MW CCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost. CCGT capacity: 150MW. CO2 emission costs are included in the
fuel costs shown.
Table 1 illustrates, as expected, that power production costs from the KSA HYSOL plant are
dominated by the investment cost component. On average for the period analysed of about
75% of the total electricity costs relates to the initial investment, whereas the fuel cost
component only contributes about 10% to the total costs. Compared to results for OCGT and
CCGT plants shown in Table 2 and Table 3, this illustrates that HYSOL plants are less exposed
and less vulnerable to gas price (and CO2 emission cost) uncertainty.
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6 Sensitivity analyses and conclusions
6.1 Overview of sensitivity analyses
Sensitivity analyses shown in Tables 7-9 describe how power productions costs (LCOE) deviate
from results based on Base Case and 'design point' assumptions, if one parameter only is
changed at a time.
Blue vertical lines in Tables 7-9 represent the LCOE calculated from Base Case assumptions.
Tables 1-3, shown above, thus give details on the Base Case results, that are 'starting points'
for the sensitive analysis results shown below, - for the KSA HYSOL, KSA OCGT and KSA CCGT
plants respectively.
KSA HYSOL
Table 7 KSA HYSOL results in overview: Electricity production costs (LCOE) - Sensitivity relative
to Base Case Assumptions. Units: $/MWh el.
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KSA OCGT
Table 8 KSA OCGT results in overview: Electricity production costs (LCOE) - Sensitivity relative
to Base Case Assumptions. Units: $/MWh el.
KSA CCGT
Table 9 KSA CCGT results in overview: Electricity production costs (LCOE) - Sensitivity relative
to Base Case Assumptions. Units: $/MWh el.
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6.2 Conclusions
The price of natural gas (NG) and its expected development strongly impacts the economic
attractiveness of HYSOL solutions relative to NG based competing technologies, such as OCGT
and CCGT power plants.
CO2 emission costs acts heavily in favour of HYSOL solutions. As seen from Tables 4-6 (as
expected) in particular an OCGT plant solution is strongly exposed to potential rising CO2
emission costs.
The capacity of a HYSOL plant is defined by the size of firm capacity it may substitute being
part the power system in question (KSA). This impacts the required capacity investments for
competing solutions (OCGT or CCGT) matching the HYSOL plant in the system. The economic
implication of different capacity assignments, however, as seen from Tables 4-6, is relatively
minor. This due to the relative low initial investment component for OCGT and CCGT plants,
which may be seen comparing power price composition results shown in Tables 1-3.
The period analysed and the lifetime of the initial investments has minor impact on the
electricity production cost for the OCGT and CCGT plant solutions. Being an initial investment
intensive RES based technology the HYSOL solution is seen to be impacted, though
moderately, from changes in lifetime of the investment.
The interest rate or the rate of calculation is important for initial investment intensive plants,
such as the HYSOL solution. In Base Case a rate of calculation of 4% p.a. has been assumed,
which may correspond to typical socio-economic conditions. Assuming a higher rate of interest
of 10% p.a., that may resemble a corporate economic situation, it is seen from Table 4 that
power production costs (LCOE) are increased substantially. Thus, in particular the HYSOL
solution is very sensitive to changes in the interest rate.
HYSOL solutions, being investment intensive are as such very sensitive to changes in the
overall investment costs, and the rate of interest, whereas the OCGT and CCGT solutions are
considerable less exposed to changes in the overall investment.
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7 Appendix
7.1 Assumption on NG and Biogas price relation
It has been assumed that the price of Biogas can be estimated to equal the price of natural
gas (NG) plus the cost for the CO2 emission using the NG.
A CO2 emission cost, as assumed in our case study, of 40$/ton CO2 emitted corresponds to a
rise of the NG price with an extra 8.17$/MWh NG. For the case of 40$/ton CO2 emitted this
means that the Biogas price will equal the NG price plus 8.17$/MWh NG.
With a NG price of 13.65 $/MWh NG the assumption thus implies:
Biogas price = NG price + 8.17$/MWh = 13.65 $/MWh + 8.17$/MWh = 21.82$/MWh NG
If it is furthermore assumed that Biogas has zero CO2 emission the economic consequence of
the use of biogas in a HYSOL plant solutions will correspond to the cost relations to the OCGT
and CCGT solutions assuming 40$/ton CO2 emitted . However in this case the HYSOL solution
using Biogas has no CO2 emission.
The economic calculations shown in Figure 2 and Figure 4 showing power production costs
(LCOE) for the HYSOL solution relative to the OCGT and CCGT solutions will hold also for the
case where HYSOL use Biogas and thus has no CO2 emission and the OCGT and CCGT use NG
and emit CO2 at a cost of 40$/ton CO2 emitted.
Chile: Economic assessment and energy system
analysis
Deliverable nº: 6.1.2
EC-GA nº: 308912 Project full title: Innovative Configuration for a Fully
Renewable Hybrid CSP Plant WP: Responsible partner: DTU/MAN/SYS Dissemination level:
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TABLE OF CONTENTS
1 DOCUMENT HISTORY ..................................................................................................... 4
2 EXECUTIVE SUMMARY ................................................................................................... 4
2.1 ABSTRACT ......................................................................................................................... 4
3 FEASIBILITY STUDY ON HYSOL CSP .................................................................................. 5
3.1 INTRODUCTION .................................................................................................................. 5
3.1.1 Example studied .......................................................................................... 5
3.1.2 The HYSOL alternative and competing technology .................................... 6
4 APPROACH AND BASIC ASSUMPTIONS ........................................................................... 6
4.1 ECONOMIC INDICATOR ........................................................................................................ 6
4.2 BASE CASE ASSUMPTIONS ................................................................................................... 6
4.3 BASE CASE FOR CHI HYSOL PLANT ....................................................................................... 7
4.4 BASE CASE OVERVIEW AND ISSUES ADDRESSED VIA SENSITIVITY ANALYSES ................................... 7
4.5 ELECTRICITY COSTS AS FUNCTION OF LOAD FACTOR AND NG PRICE ............................................. 8
4.6 DESIGN POINT ASSUMPTIONS .............................................................................................. 8
5 HYSOL RELATIVE TO OCGT AND CCGT ............................................................................. 9
5.1 BASIC PRESENTATIONS ........................................................................................................ 9
5.1.1 Assumption on CO2 emission costs ............................................................ 9
5.1.2 Assumption on NG and Biogas price relation ........................................... 10
5.2 RESULTS: HYSOL COMPARED TO OCGT .............................................................................. 10
5.3 RESULTS: HYSOL COMPARED TO CCGT .............................................................................. 13
5.4 POWER PRICE COMPOSITION .............................................................................................. 14
6 SENSITIVITY ANALYSES AND CONCLUSIONS .................................................................. 16
6.1 OVERVIEW OF SENSITIVITY ANALYSES ................................................................................... 16
6.2 CONCLUSIONS ................................................................................................................. 18
7 APPENDIX .................................................................................................................... 20
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Acronyms
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1 Document History
Version Status Date
vX.Y Draft day/month/year
vX.Y Final day/month/year
Approval Name Date
Prepared day/month/year
Reviewed day/month/year
Authorised day/month/year
2 Executive Summary
2.1 Abstract
Concentrating Solar Power (CSP) plants utilize thermal conversion of direct solar irradiation. A
trough or tower configuration focuses solar radiation and heats up oil or molten salt that
subsequently in high temperature heat exchangers generate steam for power generation.
High temperature molten salt can be stored and the stored heat can thus increase the load
factor and the usability for a CSP plant, e.g. to cover evening peak demand. In the HYSOL
concept (HYbrid SOLar) such configuration is extended further to include a gas turbine fuelled
by upgraded biogas or natural gas. The optimised integrated HYSOL concept, therefore,
becomes a fully dispatchable (offering firm power) and fully renewable energy source (RES)
based power supply alternative, offering CO2-free electricity in regions with sufficient solar
resources.
The economic feasibility of HYSOL configurations is addressed in this report. The CO2 free
HYSOL alternative is discussed relative to conventional reference firm power generation
technologies. In particular the HYSOL performance relative to new power plants based on
natural gas (NG) such as open cycle or combined cycle gas turbines (OCGT or CCGT) are in
focus. The feasibility of renewable based HYSOL power plant configurations attuned to specific
electricity consumption patterns in selected regions with promising solar energy potentials are
discussed
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3 Feasibility study on HYSOL CSP
Feasibility study on HYSOL CSP configurations with High Temperature Storage and NG/Bio-gas
fuelled Gas Turbine providing Fully Dispatchable and Renewable Power Supplies.
3.1 Introduction
Concentrating Solar Power (CSP) plants utilize thermal conversion of direct solar irradiation. A
trough or tower configuration focus solar radiation and heat up oil or molten salt that
subsequently in high temperature heat exchangers generate steam for power generation.
High temperature molten salt can be stored (HTS) and the stored heat can thus increase the
load factor and the usability for a CSP plant, e.g. to cover night (peak) demand. In the HYSOL
concept (HYbrid SOLar) such configuration is extended further to include a gas turbine fuelled
by upgraded biogas or natural gas. The optimised integrated HYSOL concept, therefore,
becomes a fully dispatchable (offering firm power) and a fully renewable energy (RES) based
power supply alternative, offering CO2-free electricity in regions with sufficient solar resources.
The economic feasibility of HYSOL configurations is addressed. The CO2 free HYSOL alternative
is discussed relative to conventional reference firm power generation technologies. In
particular the HYSOL performance relative to new power plants based on natural gas (NG) such
as open cycle or combined cycle gas turbines (OCGT or CCGT) are in focus. The feasibility of
renewable based HYSOL power plant configurations attuned to specific electricity consumption
patterns in selected regions with promising solar energy potentials are discussed.
3.1.1 Example studied
The analytical approach used is illustrated from an example where a HYSOL configuration is
optimised to conditions seen in the state of Chile (CHI). Thus, the HYSOL Power Plant studied
has been attuned to solar potentials and power system characteristics resembling conditions
in Chile (CHI).
The CHI HYSOL plant configuration particularizes the basic HYSOL outline by the choices:
- A CSP Tower configuration has been assumed. HYSOL configurations can also be
applied with CSP trough design.
- Biogas supply have been assumed for this CHI case. The HYSOL plant investments do
not include investments in biogas plants. The HYSOL plant is assumed to purchase biogas at a
price that equals the price of natural gas (NG) plus the value of the reduced CO2 emission
when Biogas is used. HYSOL’s 100% renewable configuration use biogas upgraded to NG
quality.
The CHI HYSOL configuration analysed uses natural gas (NG) and not biogas based methane,
and may thus not be termed fully renewable, - though being a firm, fully dispatch-able and
mainly renewables based power plant.
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3.1.2 The HYSOL alternative and competing technology
This present analyses compare electricity production costs for a HYSOL plant alternative to
production cost for conventional power plant solutions or reference plants.
In this CHI case it has been assumed that the main competing reference technologies are an
Open Cycle Gas Turbine (OCGT) and a
Combined Cycle Gas Turbine (CCGT)
using natural gas (NG).
4 Approach and basic assumptions
4.1 Economic indicator
Basically a socio-economic approach is applied. And generally main focus is placed on the
economic indicator LCOE (the levelized cost of electricity), and on the sensitivity of the LCOE in
particular to variations in the two parameters:
• load factor or the number of full load hours per year, and the
• price of natural gas (given as the levelized NG price covering the period analysed)
The solar potential and the annual power production heavily impact the HYSOL power plant
economy. And for fossil based competing reference technologies fuel cost and CO2 emission
cost developments constitute important framework conditions. LCOE dependency on in
particular these major parameters will be in focus in this study of (predominantly) renewable
energy source (RES) based HYSOL solutions relative to fossil based conventional reference
power plant solutions.
4.2 Base Case assumptions
For the present socio-economic analyses the following general assumptions have been
adopted as 'Base Case':
Price level: Year 2015
Socio economic rate of calculation (rate of interest): 4 % p.a.
Project base year: 2020
Period analysed: Time period: 2021-2045
Period in years: 25 years
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4.3 Base Case for CHI HYSOL plant
Chosen Base Case for the CHI HYSOL plant annual production, assigned capacity and load
factor are:
Annual electricity production: 868.48 GWh/year
Assigned HYSOL capacity (PH): PH = 150MWel
Annual full load hours (HFLH) and Load factor (LF):
HFLH = 868.48GWh / 150MW = 5790 h/year
and LF= 5790/8760= 0.661
As mentioned, gas consumed in the CHI HYSOL gas turbine (GT) component is assumed to be
natural gas (NG). The CHI Base Case NG price and the sensitivity variations analysed for the NG
price are:
NG price Base case: 44.36 $/MWh (13$/MMBtu)
Sensitivity: Base Case +/- 20%, +/-40%
Data on investments, operation and maintenance costs for the CHI HYSOL configuration are
found in the Appendix.
4.4 Base Case overview and issues addressed via sensitivity analyses
Electricity production costs (LCOE) are furthermore analysed for its dependence on or
sensitivity to variations in the following parameters:
• Natural Gas price: Sensitivity Base Case -/+40%
• CO2 emission quota market price Base case: 0 $ / ton CO2
Sensitivity: 40 $ / ton CO2
• Capacity assignment: assignment Base case: 150 MW
Sensitivity: 100MW <--> 180MW
• Lifetime of initial investment: Base case: 25 years
Sensitivity: 20 years
• Rate of calculation (interest rate) Base case: 4.0 % p.a.
Sensitivity: 10.0 % p.a.
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• Initial investment (CAPEX) Sensitivity: Base Case +/- 20%
The combined steam turbine (ST) and gas turbine (GT) capacity in the CHI HYSOL configuration
plant has been assigned a total combined capacity of 150MW. The peak power generated by
the plant is limited to 150 MW, and the plant is made to follow a demand curve congruent or
analogous to that of country altogether. This implies that the number of full load hours for the
combined CHI HYSOL configuration can be calculated as 868.48GWh/150MW = 5790
hours/year, and the demand coverage rate is above 99.9%.
4.5 Electricity costs as function of load factor and NG price
In Figures 1-4 results on the LCOE (given along the y-axis) are shown as a function of the
annual load. The annual load or electricity production, - here expressed through its equivalent,
the number of full load hours per year, is shown along the x-axis.
HYSOL plant operation at different load factors is assumed to maintain the relative ST and GT
contribution to the electricity production. Thus, even the annual power production may differ
from the Base Case assumption the %-split of production contributions from the ST and GT
HYSOL plant components is assumed constant. And the share of the annual production based
on gas (via the GT directly and indirectly via GT flue gas heat recovered and utilized by the ST)
is kept constant.
Furthermore, for this feasibility analysis the HYSOL plant operation efficiency is assumed
constant, - even at e.g. lower annual production levels. And gas consumption per MWh
electricity generated, accordingly, is assumed constant and independent of the annual
production. This may be a somewhat rough assumption.
4.6 Design Point assumptions
Assumptions used as basis for optimizing and configuring the HYSOL plant, will in the following
be termed the 'Design Point' data assumptions. Yellow points, 'Design Points', shown in Figures
1-4 represent results for the CHI HYSOL plant assuming Base Case operation conditions. Black
points, correspondingly, represent (OCGT or CCGT) reference technology results based on
equivalent assumptions. Other results presented may thus be considered as sensitivity and
parameter analyses.
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5 HYSOL relative to OCGT and CCGT
5.1 Basic presentations
In what follows the CHI HYSOL plant alternative is compared to competing 'conventional' or
reference plant solutions based on equivalent system framework condition. Benchmarked via
the LCOE the competing technologies are evaluated using equivalent general assumptions. The
so-called Base Case data assumptions form the core for this feasibility comparison. For
selected key parameters LCOE consequences of data deviating from Base Case are covered via
sensitivity analyses.
As mentioned above the competing reference technologies assumed are the Open Cycle Gas
Turbine (OCGT) and the Combined Cycle Gas Turbine (CCGT).
For consistency of the comparison it is assumed, that the average annual electricity production
is the same for the HYSOL alternative and for the reference plants. Furthermore, plants being
compared are assumed to have the same capacity value in the Chilean power system, and the
plants are assumed to be fully dispatchable (firm power). Thus, all plants are assumed to be
able to occupy the same position of operation in the overall power system dispatch.
Data for the CHI HYSOL alternative and for the assumed CHI OCGT and CHI CCGT reference
power plants are found in the Appendix.
It can be observed from Figures 1-4 that the annual number of full load operation hours for the
HYSOL plant, shown along the x-axis, is extremely important for the electricity production cost
achieved, - and the plant economy. Low annual power production results in high production
costs. For the overall economy of a HYSOL plant, therefore, it is very important to achieve high
annual power production, as the total production costs are much dominated by high initial
investments. Natural gas prices, however, have minor impact on the HYSOL power production
cost due to the relatively low electricity production contribution via the GT part of the CHI
HYSOL configuration.
5.1.1 Assumption on CO2 emission costs
Comparison of HYSOL solutions relative to conventional OCGT and CCGT power plant solutions
are carried out for cases with and without inclusion of an assumed CO2 emission cost. For this
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sensitivity analysis it has been assumed, as an example, that CO2 emission costs amounts to
40$/tonCO2 emitted. For natural gas (NG) this CO2 emission cost is equivalent to 8.17$/MWh
NG. The CO2 emission cost assumed thus rises the NG price with an extra 8.17$/MWh NG.
5.1.2 Assumption on NG and Biogas price relation
It has been assumed that the price of Biogas can be estimated to equal the price of natural gas
(NG) plus the cost for the CO2 emission using the NG.
A CO2 emission cost, as assumed in our case study, of 40$/ton CO2 emitted corresponds to a
rise of the NG price with an extra 8.17$/MWh NG. Thus, for the case of 40$/ton CO2 emitted
this means that the Biogas price will equal the NG price plus 8.17$/MWh NG.
With a NG price of 44.36$/MWh NG the assumption thus implies:
Biogas price = NG price + 8.17$/MWh
= 44.36$/MWh + 8.17$/MWh = 52.53$/MWh NG
If it is furthermore assumed that Biogas has zero CO2 emission the economic consequence of
the use of biogas as fuel in HYSOL plant solutions will correspond to fuel costs as for NG plus its
CO2 cost. The fuel price relations for HYSOL, OCGT and CCGT solutions thus correspond to the
NG price including CO2 costs. However in this case the HYSOL solution using Biogas has no
CO2 emission.
The economic calculations shown in Figure 2 and Figure 4 showing power production costs
(LCOE) for the HYSOL solution relative to the OCGT and CCGT solutions, therefore, will hold
also for the case where HYSOL use Biogas (and thus has no CO2 emission) and the OCGT and
CCGT use NG and emit CO2 at a cost of 40$/ton CO2 emitted.
5.2 Results: HYSOL compared to OCGT
In Figure 1 below it has been assumed that the CO2 emission costs are 0 $/ton CO2 emitted. In
such scenario the CO2 reduction achieved by using (CO2 emission free biogas) thus has no
value. Therefore, in the 0 $/ton CO2 emitted scenario, it has been assumed that both the
HYSOL plant and the OCGT plant use NG.
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HYSOL and OCGT: Assuming 0 $/ton CO2 emitted
Figure 1 Electricity production costs for Open Cycle Gas Turbine (OCGT) and CHI HYSOL
configuration, as function of load factor and NG price. Assumed: CO2 costs = 0$/tonCO2,
R=4%p.a., Lifetime=25years. Unit: $/MWh el.
HYSOL and OCGT: Assuming 40 $/ton CO2 emitted
In Figure 2 it has been assumed that the CO2 emission costs are 40 $/ton CO2 emitted. In this
case it has been assumed that the HYSOL plant use (CO2 emission free) biogas. The price of
biogas has been assumed to equal the price of NG plus the value of CO2 emission reduction
achieved by using biogas substituting NG.
However, the reference OCGT plant that solely relies on gas as fuel has been assumed use NG
priced as the NG price plus the cost of the CO2 emitted. (A cost of 40 $/ton CO2 emitted
equals a price increase for the NG with an extra 8.17$/MWh NG.)
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Figure 2 Electricity production costs for Open Cycle Gas Turbine (OCGT) and CHI HYSOL
configuration, as function of load factor and NG price. Assumed: CO2 costs = 40$/tonCO2,
R=4%p.a., Lifetime=25years. Unit: $/MWh el.
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5.3 Results: HYSOL compared to CCGT
HYSOL and CCGT: Assuming 0 $/ton CO2 emitted
Figure 3 Electricity production costs for Combined Cycle Gas Turbine (CCGT) and CHI HYSOL
configuration, as function of load factor and NG price. Assumed: CO2 costs = 0$/tonCO2,
R=4%p.a., Lifetime=25years. Unit: $/MWh el.
HYSOL and CCGT: Assuming 40 $/ton CO2 emitted
Figure 4 Electricity production costs for Combined Cycle Gas Turbine (CCGT) and CHI HYSOL
configuration, as function of load factor and NG price. Assumed: CO2 costs = 40$/tonCO2,
R=4%p.a., Lifetime=25years. Unit: $/MWh el.
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5.4 Power price composition
LCOE results based on Design Point assumptions (shown as yellow and black points in Figures
2&4) are presented below with a breakdown or split into its components related to
respectively Investment, O&M, and Fuel cost parts.
CO2 emission costs of 0 $/ton CO2 emitted is assumed:
HYSOL Table 1 CHI HYSOL alternative: Electricity production cost (LCOE on socio economic basis) for
'design basis' assumptions split on contributions from the Investment, O&M, and Fuel Cost
parts to the total cost. Natural gas has been assumed for the HYSOL GT component.
OCGT Table 2 CHI 150MW OCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and
Fuel Cost parts to the total cost. OCGT capacity: 150MW.
CCGT Table 3 CHI 150MW CCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and
Fuel Cost parts to the total cost. CCGT capacity: 150MW.
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
89.05 100.0% 54.51 61.2% 9.11 10.2% 25.43 28.6%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
160.38 100.0% 8.85 5.5% 1.20 0.8% 150.33 93.7%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
99.79 100.0% 10.47 10.5% 1.75 1.7% 87.58 87.8%
at 'design basis point' data Investment O & M Fuel costs
Total
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CO2 emission costs of 40 $/ton CO2 emitted is included in the NG fuel costs shown:
HYSOL Table 4 CHI HYSOL alternative: Electricity production cost (LCOE on socio economic basis) for
'design basis' assumptions split on contributions from the Investment, O&M, and Fuel Cost parts
to the total cost. Biogas use has been assumed for the HYSOL GT component.
OCGT Table 5 CHI 150MW OCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost. OCGT capacity: 150MW. CO2 emission costs are included in the
fuel costs shown.
CCGT Table 6 CHI 150MW CCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost. CCGT capacity: 150MW. CO2 emission costs are included in the
fuel costs shown.
Table 4 illustrates, as expected, that power production costs from the CHI HYSOL plant are
dominated by the investment cost component. On average for the period analysed of about
58% of the total electricity costs relates to the initial investment, whereas the fuel cost
component only contributes about 32% to the total costs. Compared to results for OCGT and
CCGT plants shown in Table 5 and Table 6, this illustrates that HYSOL plants are less exposed
and less vulnerable to gas price (and CO2 emission cost) uncertainty.
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
93.73 100.0% 54.51 58.2% 9.11 9.7% 30.11 32.1%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
188.07 100.0% 8.85 4.7% 1.20 0.6% 178.02 94.7%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
115.92 100.0% 10.47 9.0% 1.75 1.5% 103.71 89.5%
at 'design basis point' data Investment O & M Fuel costs
Total
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6 Sensitivity analyses and conclusions
6.1 Overview of sensitivity analyses
Sensitivity analyses shown in Tables 7-9 describe how power productions costs (LCOE) deviate
from results based on Base Case and 'design point' assumptions, if one parameter only is
changed at a time.
Blue vertical lines in Tables 7-9 represent the LCOE calculated from Base Case assumptions.
Tables 1-3, shown above, thus give details on the Base Case results, that are 'starting points'
for the sensitive analysis results shown below, - for the CHI HYSOL, CHI OCGT and CHI CCGT
plants respectively.
CHI HYSOL
Table 7 CHI HYSOL results in overview: Electricity production costs (LCOE) - Sensitivity relative
to Base Case Assumptions. Units: $/MWh el.
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CHI OCGT
Table 8 CHI OCGT results in overview: Electricity production costs (LCOE) - Sensitivity relative
to Base Case Assumptions. Units: $/MWh el.
CHI CCGT
Table 9 CHI CCGT results in overview: Electricity production costs (LCOE) - Sensitivity relative to
Base Case Assumptions. Units: $/MWh el.
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6.2 Conclusions
The price of natural gas (NG) and its expected development strongly impacts the economic
attractiveness of HYSOL solutions relative to NG based competing technologies, such as OCGT
and CCGT power plants.
CO2 emission costs acts heavily in favour of HYSOL solutions. As seen from Tables 4-6 (as
expected) in particular an OCGT plant solution is strongly exposed to potential rising CO2
emission costs.
The capacity of a HYSOL plant is defined by the size of firm capacity it may substitute being
part the power system in question (CHI). This impacts the required capacity investments for
competing solutions (OCGT or CCGT) matching the HYSOL plant in the system. The economic
implication of different capacity assignments, however, as seen from Tables 4-6, is relatively
minor. This due to the relative low initial investment component for OCGT and CCGT plants,
which may be seen comparing power price composition results shown in Tables 1-3.
The period analysed and the lifetime of the initial investments has minor impact on the
electricity production cost for the OCGT and CCGT plant solutions. Being an initial investment
intensive RES based technology the HYSOL solution is seen to be impacted, though
moderately, from changes in lifetime of the investment.
The interest rate or the rate of calculation is important for initial investment intensive plants,
such as the HYSOL solution. In Base Case a rate of calculation of 4% p.a. has been assumed,
which may correspond to typical socio-economic conditions. Assuming a higher rate of interest
of 10% p.a., that may resemble a corporate economic situation, it is seen from Table 4 that
power production costs (LCOE) are increased substantially. Thus, in particular the HYSOL
solution is very sensitive to changes in the interest rate.
HYSOL solutions, being investment intensive are as such very sensitive to changes in the
overall investment costs, and the rate of interest, whereas the OCGT and CCGT solutions are
considerable less exposed to changes in the overall investment.
Summary CHI conclusion:
The HYSOL solution in Chile competes very favourable relative to the Open Cycle Gas Turbine
(OCGT) reference as can be seen from comparing results, when base case data are assumed.
The Base Case assumption on the level of future NG-prices in the region is an important factor
for the conclusion. This conclusion holds even without taking into account an assumed cost on
emission of CO2. When compared to a Combined Cycle Gas Turbine (CCGT) reference plant the
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CHI HYSOL alternative is still favourable. And introducing an assumed CO2 emission costs of
40$/ton CO2 emitted, adds much in favour of the CHI HYSOL solution.
Sensitivity (or robustness) analyses carried out emphasize that HYSOL solutions, as expected,
are less exposed to CO2 emission cost uncertainty and fuel price uncertainty than the
reference OCGT/CCGT solutions. OCGT/CCGT solutions are more exposed to CO2 emission cost
uncertainty, and more exposed to NG-price uncertainty, but less exposed to investment cost
uncertainty.
However, as observed from Figures 1-4 the annual number of full load operation hours for
HYSOL solutions, and thus the annual power production, is very important the plant economy.
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7 Appendix
7.1 Assumption on NG and Biogas price relation
It has been assumed that the price of Biogas can be estimated to equal the price of natural
gas (NG) plus the cost for the CO2 emission using the NG.
A CO2 emission cost, as assumed in our case study, of 40$/ton CO2 emitted corresponds to a
rise of the NG price with an extra 8.17$/MWh NG. For the case of 40$/ton CO2 emitted this
means that the Biogas price will equal the NG price plus 8.17$/MWh NG.
With a NG price of 44.36 $/MWh NG the assumption thus implies:
Biogas price = NG price + 8.17$/MWh = 44.36 $/MWh + 8.17 $/MWh = 52.53 $/MWh NG
If it is furthermore assumed that Biogas has zero CO2 emission the economic consequence of
the use of biogas in a HYSOL plant solutions will correspond to the cost relations to the OCGT
and CCGT solutions assuming 40$/ton CO2 emitted . However in this case the HYSOL solution
using Biogas has no CO2 emission.
The economic calculations shown in Figure 2 and Figure 4 showing power production costs
(LCOE) for the HYSOL solution relative to the OCGT and CCGT solutions will hold also for the
case where HYSOL use Biogas and thus has no CO2 emission and the OCGT and CCGT use NG
and emit CO2 at a cost of 40$/ton CO2 emitted.
Mexico: Economic assessment and energy system
analysis
Deliverable nº: 6.1.3
EC-GA nº: 308912 Project full title: Innovative Configuration for a Fully
Renewable Hybrid CSP Plant WP: Responsible partner: DTU/MAN/SYS Dissemination level:
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TABLE OF CONTENTS
1 DOCUMENT HISTORY ..................................................................................................... 4
2 EXECUTIVE SUMMARY ................................................................................................... 4
2.1 ABSTRACT ......................................................................................................................... 4
3 FEASIBILITY STUDY ON HYSOL CSP .................................................................................. 5
3.1 INTRODUCTION .................................................................................................................. 5
3.1.1 Example studied .......................................................................................... 5
3.1.2 The HYSOL alternative and competing technology .................................... 6
4 APPROACH AND BASIC ASSUMPTIONS ........................................................................... 6
4.1 ECONOMIC INDICATOR ........................................................................................................ 6
4.2 BASE CASE ASSUMPTIONS ................................................................................................... 6
4.3 BASE CASE FOR MEX HYSOL PLANT ..................................................................................... 7
4.4 BASE CASE OVERVIEW AND ISSUES ADDRESSED VIA SENSITIVITY ANALYSES ................................... 7
4.5 ELECTRICITY COSTS AS FUNCTION OF LOAD FACTOR AND NG PRICE ............................................. 8
4.6 DESIGN POINT ASSUMPTIONS .............................................................................................. 8
5 HYSOL RELATIVE TO OCGT AND CCGT ............................................................................. 9
5.1 BASIC PRESENTATIONS ........................................................................................................ 9
5.1.1 Assumption on CO2 emission costs ............................................................ 9
5.1.2 Assumption on NG and Biogas price relation ........................................... 10
5.2 RESULTS: HYSOL COMPARED TO OCGT .............................................................................. 10
5.3 RESULTS: HYSOL COMPARED TO CCGT .............................................................................. 13
5.4 POWER PRICE COMPOSITION .............................................................................................. 14
6 SENSITIVITY ANALYSES AND CONCLUSIONS .................................................................. 16
6.1 OVERVIEW OF SENSITIVITY ANALYSES ................................................................................... 16
6.2 CONCLUSIONS ................................................................................................................. 18
7 APPENDIX .................................................................................................................... 19
7.1 ASSUMPTION ON NG AND BIOGAS PRICE RELATION ............................................................... 19
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Acronyms
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1 Document History
Version Status Date
vX.Y Draft day/month/year
vX.Y Final day/month/year
Approval Name Date
Prepared day/month/year
Reviewed day/month/year
Authorised day/month/year
2 Executive Summary
2.1 Abstract
Concentrating Solar Power (CSP) plants utilize thermal conversion of direct solar irradiation. A
trough or tower configuration focuses solar radiation and heats up oil or molten salt that
subsequently in high temperature heat exchangers generate steam for power generation.
High temperature molten salt can be stored and the stored heat can thus increase the load
factor and the usability for a CSP plant, e.g. to cover evening peak demand. In the HYSOL
concept (HYbrid SOLar) such configuration is extended further to include a gas turbine fuelled
by upgraded biogas or natural gas. The optimised integrated HYSOL concept, therefore,
becomes a fully dispatchable (offering firm power) and fully renewable energy source (RES)
based power supply alternative, offering CO2-free electricity in regions with sufficient solar
resources.
The economic feasibility of HYSOL configurations is addressed in this report. The CO2 free
HYSOL alternative is discussed relative to conventional reference firm power generation
technologies. In particular the HYSOL performance relative to new power plants based on
natural gas (NG) such as open cycle or combined cycle gas turbines (OCGT or CCGT) are in
focus. The feasibility of renewable based HYSOL power plant configurations attuned to specific
electricity consumption patterns in selected regions with promising solar energy potentials are
discussed
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3 Feasibility study on HYSOL CSP
Feasibility study on HYSOL CSP configurations with High Temperature Storage and NG/Bio-gas
fuelled Gas Turbine providing Fully Dispatchable and Renewable Power Supplies.
3.1 Introduction
Concentrating Solar Power (CSP) plants utilize thermal conversion of direct solar irradiation. A
trough or tower configuration focus solar radiation and heat up oil or molten salt that
subsequently in high temperature heat exchangers generate steam for power generation.
High temperature molten salt can be stored (HTS) and the stored heat can thus increase the
load factor and the usability for a CSP plant, e.g. to cover night (peak) demand. In the HYSOL
concept (HYbrid SOLar) such configuration is extended further to include a gas turbine fuelled
by upgraded biogas or natural gas. The optimised integrated HYSOL concept, therefore,
becomes a fully dispatchable (offering firm power) and a fully renewable energy (RES) based
power supply alternative, offering CO2-free electricity in regions with sufficient solar resources.
The economic feasibility of HYSOL configurations is addressed. The CO2 free HYSOL alternative
is discussed relative to conventional reference firm power generation technologies. In
particular the HYSOL performance relative to new power plants based on natural gas (NG) such
as open cycle or combined cycle gas turbines (OCGT or CCGT) are in focus. The feasibility of
renewable based HYSOL power plant configurations attuned to specific electricity consumption
patterns in selected regions with promising solar energy potentials are discussed.
3.1.1 Example studied
The analytical approach used is illustrated from an example where a HYSOL configuration is
optimised to conditions seen e.g. in the state of Mexico (MEX). Thus, the HYSOL Power Plant
studied has been attuned to solar potentials and power system characteristics resembling
conditions in Mexico (MEX).
The MEX HYSOL plant configuration particularizes the basic HYSOL outline by the choices:
- A CSP Tower configuration has been assumed. HYSOL configurations can also be
applied with CSP trough design.
- Biogas supply have been assumed for this MEX case. The HYSOL plant investments do
not include investments in biogas plants. The HYSOL plant is assumed to purchase biogas at a
price that equals the price of natural gas (NG) plus the value of the reduced CO2 emission
when Biogas is used. HYSOL’s 100% renewable configuration use biogas upgraded to NG
quality.
The MEX HYSOL configuration analysed uses natural gas (NG) and not biogas based methane,
and may thus not be termed fully renewable, - though being a firm, fully dispatch-able and
mainly renewables based power plant.
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3.1.2 The HYSOL alternative and competing technology
This present analyses compare electricity production costs for a HYSOL plant alternative to
production cost for conventional power plant solutions or reference plants.
In this MEX case it has been assumed that the main competing reference technologies are an
Open Cycle Gas Turbine (OCGT) and an
Combined Cycle Gas Turbine (CCGT)
using natural gas (NG).
4 Approach and basic assumptions
4.1 Economic indicator
Basically a socio-economic approach is applied. And generally main focus is placed on the
economic indicator LCOE (the levelized cost of electricity), and on the sensitivity of the LCOE in
particular to variations in the two parameters:
• load factor or the number of full load hours per year, and the
• price of natural gas (given as the levelized NG price covering the period analysed)
The solar potential and the annual power production heavily impact the HYSOL power plant
economy. And for fossil based competing reference technologies fuel cost and CO2 emission
cost developments constitute important framework conditions. LCOE dependency on in
particular these major parameters will be in focus in this study of (predominantly) renewable
energy source (RES) based HYSOL solutions relative to fossil based conventional reference
power plant solutions.
4.2 Base Case assumptions
For the present socio-economic analyses the following general assumptions have been
adopted as 'Base Case':
Price level: Year 2015
Socio economic rate of calculation (rate of interest): 4 % p.a.
Project base year: 2020
Period analysed: Time period: 2021-2045
Period in years: 25 years
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4.3 Base Case for MEX HYSOL plant
Chosen Base Case for the MEX HYSOL plant annual production, assigned capacity and load
factor are:
Annual electricity production: 929.2 GWh/year
Assigned HYSOL capacity (PH): PH = 150MWel
Annual full load hours (HFLH) and Load factor (LF):
HFLH = 929.2 GWh / 150MW = 6195 hours/year
and LF= 6251/8760= 0.707
As mentioned, gas consumed in the MEX HYSOL gas turbine (GT) component is assumed to be
natural gas (NG). The MEX Base Case NG price and the sensitivity variations analysed for the
NG price are:
NG price Base case: 13.31 $/MWh (3.9$/MMBtu)
Sensitivity: Base Case +/- 20%, +/-40%
Data on investments, operation and maintenance costs for the MEX HYSOL configuration are
found in the Appendix.
4.4 Base Case overview and issues addressed via sensitivity analyses
Electricity production costs (LCOE) are furthermore analysed for its dependence on or
sensitivity to variations in the following parameters:
• Natural Gas price: Sensitivity Base Case -/+40%
• CO2 emission quota market price Base case: 0 $ / ton CO2
Sensitivity: 40 $ / ton CO2
• Capacity assignment: assignment Base case: 150 MW
Sensitivity: 100MW <--> 180MW
• Lifetime of initial investment: Base case: 25 years
Sensitivity: 20 years
• Rate of calculation (interest rate) Base case: 4.0 % p.a.
Sensitivity: 10.0 % p.a.
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• Initial investment (CAPEX) Sensitivity: Base Case +/- 20%
The combined steam turbine (ST) and gas turbine (GT) capacity in the MEX HYSOL
configuration plant has been assigned a total combined capacity of 150MW. The peak power
generated by the plant is limited to 150 MW, and the plant is made to follow a demand curve
congruent or analogous to that of country altogether. This implies that the number of full load
hours for the combined MEX HYSOL configuration can be calculated as 929.2GWh/150MW =
6195 hours/year, and the demand coverage rate is above 99.9%.
4.5 Electricity costs as function of load factor and NG price
In Figures 1-4 results on the LCOE (given along the y-axis) are shown as a function of the
annual load. The annual load or electricity production, - here expressed through its equivalent,
the number of full load hours per year, is shown along the x-axis.
HYSOL plant operation at different load factors is assumed to maintain the relative ST and GT
contribution to the electricity production. Thus, even the annual power production may differ
from the Base Case assumption the %-split of production contributions from the ST and GT
HYSOL plant components is assumed constant. And the share of the annual production based
on gas (via the GT directly and indirectly via GT flue gas heat recovered and utilized by the ST)
is kept constant.
Furthermore, for this feasibility analysis the HYSOL plant operation efficiency is assumed
constant, - even at e.g. lower annual production levels. And gas consumption per MWh
electricity generated, accordingly, is assumed constant and independent of the annual
production. This may be a somewhat rough assumption.
4.6 Design Point assumptions
Assumptions used as basis for optimizing and configuring the HYSOL plant, will in the following
be termed the 'Design Point' data assumptions. Yellow points, 'Design Points', shown in Figures
1-4 represent results for the MEX HYSOL plant assuming Base Case operation conditions. Black
points, correspondingly, represent (OCGT or CCGT) reference technology results based on
equivalent assumptions. Other results presented may thus be considered as sensitivity and
parameter analyses.
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5 HYSOL relative to OCGT and CCGT
5.1 Basic presentations
In what follows the MEX HYSOL plant alternative is compared to competing 'conventional' or
reference plant solutions based on equivalent system framework condition. Benchmarked via
the LCOE the competing technologies are evaluated using equivalent general assumptions. The
so-called Base Case data assumptions form the core for this feasibility comparison. For
selected key parameters LCOE consequences of data deviating from Base Case are covered via
sensitivity analyses.
As mentioned above the competing reference technologies assumed are the Open Cycle Gas
Turbine (OCGT) and the Combined Cycle Gas Turbine (CCGT).
For consistency of the comparison it is assumed, that the average annual electricity production
is the same for the HYSOL alternative and for the reference plants. Furthermore, plants being
compared are assumed to have the same capacity value in the Mexican power system, and the
plants are assumed to be fully dispatchable (firm power). Thus, all plants are assumed to be
able to occupy the same position of operation in the overall power system dispatch.
Data for the MEX HYSOL alternative and for the assumed MEX OCGT and MEX CCGT reference
power plants are found in the Appendix.
It can be observed from Figures 1-4 that the annual number of full load operation hours for the
HYSOL plant, shown along the x-axis, is extremely important for the electricity production cost
achieved, - and the plant economy. Low annual power production results in high production
costs. For the overall economy of a HYSOL plant, therefore, it is very important to achieve high
annual power production, as the total production costs are much dominated by high initial
investments. Natural gas prices, however, have minor impact on the HYSOL power production
cost due to the relatively low electricity production contribution via the GT part of the MEX
HYSOL configuration.
5.1.1 Assumption on CO2 emission costs
Comparison of HYSOL solutions relative to conventional OCGT and CCGT power plant solutions
are carried out for cases with and without inclusion of an assumed CO2 emission cost. For this
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sensitivity analysis it has been assumed, as an example, that CO2 emission costs amounts to
40$/tonCO2 emitted. For natural gas (NG) this CO2 emission cost is equivalent to 8.17$/MWh
NG. The CO2 emission cost assumed thus rises the NG price with an extra 8.17$/MWh NG.
5.1.2 Assumption on NG and Biogas price relation
It has been assumed that the price of Biogas can be estimated to equal the price of natural gas
(NG) plus the cost for the CO2 emission using the NG.
A CO2 emission cost, as assumed in our case study, of 40$/ton CO2 emitted corresponds to a
rise of the NG price with an extra 8.17$/MWh NG. Thus, for the case of 40$/ton CO2 emitted
this means that the Biogas price will equal the NG price plus 8.17$/MWh NG.
With a NG price of 13.65 $/MWh NG the assumption thus implies:
Biogas price = NG price + 8.17$/MWh
= 13.31 $/MWh + 8.17$/MWh = 21.48$/MWh NG
If it is furthermore assumed that Biogas has zero CO2 emission the economic consequence of
the use of biogas as fuel in HYSOL plant solutions will correspond to fuel costs as for NG plus its
CO2 cost. The fuel price relations for HYSOL, OCGT and CCGT solutions thus correspond to the
NG price including CO2 costs. However in this case the HYSOL solution using Biogas has no
CO2 emission.
The economic calculations shown in Figure 2 and Figure 4 showing power production costs
(LCOE) for the HYSOL solution relative to the OCGT and CCGT solutions, therefore, will hold
also for the case where HYSOL use Biogas (and thus has no CO2 emission) and the OCGT and
CCGT use NG and emit CO2 at a cost of 40$/ton CO2 emitted.
5.2 Results: HYSOL compared to OCGT
In Figure 1 below it has been assumed that the CO2 emission costs are 0 $/ton CO2 emitted. In
such scenario the CO2 reduction achieved by using (CO2 emission free biogas) thus has no
value. Therefore, in the 0 $/ton CO2 emitted scenario, it has been assumed that both the
HYSOL plant and the OCGT plant use NG.
HYSOL and OCGT: Assuming 0 $/ton CO2 emitted
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Figure 1 Electricity production costs for Open Cycle Gas Turbine (OCGT) and MEX HYSOL
configuration, as function of load factor and NG price. Assumed: CO2 costs = 0$/tonCO2,
R=4%p.a., Lifetime=25years. Unit: $/MWh el.
HYSOL and OCGT: Assuming 40 $/ton CO2 emitted
In Figure 2 it has been assumed that the CO2 emission costs are 40 $/ton CO2 emitted. In this
case it has been assumed that the HYSOL plant use (CO2 emission free) biogas. The price of
biogas has been assumed to equal the price of NG plus the value of CO2 emission reduction
achieved by using biogas substituting NG.
However, the reference OCGT plant that solely relies on gas as fuel has been assumed use NG
priced as the NG price plus the cost of the CO2 emitted. (A cost of 40 $/ton CO2 emitted
equals a price increase for the NG with an extra 8.17$/MWh NG.)
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Figure 2 Electricity production costs for Open Cycle Gas Turbine (OCGT) and MEX HYSOL
configuration, as function of load factor and NG price. Assumed: CO2 costs = 40$/tonCO2,
R=4%p.a., Lifetime=25years. Unit: $/MWh el.
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5.3 Results: HYSOL compared to CCGT
HYSOL and CCGT: Assuming 0 $/ton CO2 emitted
Figure 3 Electricity production costs for Combined Cycle Gas Turbine (CCGT) and MEX HYSOL
configuration, as function of load factor and NG price. Assumed: CO2 costs = 0$/tonCO2,
R=4%p.a., Lifetime=25years. Unit: $/MWh el.
HYSOL and CCGT: Assuming 40 $/ton CO2 emitted
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Figure 4 Electricity production costs for Combined Cycle Gas Turbine (CCGT) and MEX HYSOL
configuration, as function of load factor and NG price. Assumed: CO2 costs = 40$/tonCO2,
R=4%p.a., Lifetime=25years. Unit: $/MWh el.
5.4 Power price composition
LCOE results based on Design Point assumptions (shown as yellow and black points in Figures
2&4) are presented below with a breakdown or split into its components related to
respectively Investment, O&M, and Fuel cost parts.
CO2 emission costs of 0 $/ton CO2 emitted is assumed:
HYSOL Table 1 MEX HYSOL alternative: Electricity production cost (LCOE on socio economic basis) for
'design basis' assumptions split on contributions from the Investment, O&M, and Fuel Cost
parts to the total cost. Natural gas has been assumed for the HYSOL GT component.
OCGT Table 2 MEX 150MW OCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and
Fuel Cost parts to the total cost. OCGT capacity: 150MW.
CCGT Table 3 MEX 150MW CCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and
Fuel Cost parts to the total cost. CCGT capacity: 150MW.
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
75.55 100.0% 53.70 71.1% 8.76 11.6% 13.09 17.3%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
51.61 100.0% 7.89 15.3% 1.29 2.5% 42.43 82.2%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
35.95 100.0% 9.48 26.4% 1.92 5.3% 24.55 68.3%
at 'design basis point' data Investment O & M Fuel costs
Total
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CO2 emission costs of 40 $/ton CO2 emitted is included in the NG fuel costs shown:
HYSOL Table 4 MEX HYSOL alternative: Electricity production cost (LCOE on socio economic basis) for
'design basis' assumptions split on contributions from the Investment, O&M, and Fuel Cost parts
to the total cost. Biogas use has been assumed for the HYSOL GT component.
OCGT Table 5 MEX 150MW OCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost. OCGT capacity: 150MW. CO2 emission costs are included in the
fuel costs shown.
CCGT Table 6 MEX 150MW CCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost. CCGT capacity: 150MW. CO2 emission costs are included in the
fuel costs shown.
Table 4 illustrates, as expected, that power production costs from the MEX HYSOL plant are
dominated by the investment cost component. On average for the period analysed of about
54% of the total electricity costs relates to the initial investment, whereas the fuel cost
component only contributes about 21% to the total costs. Compared to results for OCGT and
CCGT plants shown in Table 5 and Table 6, this illustrates that HYSOL plants are less exposed
and less vulnerable to gas price (and CO2 emission cost) uncertainty.
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
83.58 100.0% 53.70 64.2% 8.76 10.5% 21.12 25.3%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
77.65 100.0% 7.89 10.2% 1.29 1.7% 68.47 88.2%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
51.02 100.0% 9.48 18.6% 1.92 3.8% 39.62 77.7%
at 'design basis point' data Investment O & M Fuel costs
Total
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6 Sensitivity analyses and conclusions
6.1 Overview of sensitivity analyses
Sensitivity analyses shown in Tables 7-9 describe how power productions costs (LCOE) deviate
from results based on Base Case and 'design point' assumptions, if one parameter only is
changed at a time.
Blue vertical lines in Tables 7-9 represent the LCOE calculated from Base Case assumptions.
Tables 1-3, shown above, thus give details on the Base Case results, that are 'starting points'
for the sensitive analysis results shown below, - for the MEX HYSOL, MEX OCGT and MEX CCGT
plants respectively.
MEX HYSOL
Table 7 MEX HYSOL results in overview: Electricity production costs (LCOE) - Sensitivity relative
to Base Case Assumptions. Units: $/MWh el.
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MEX OCGT
Table 8 MEX OCGT results in overview: Electricity production costs (LCOE) - Sensitivity relative
to Base Case Assumptions. Units: $/MWh el.
MEX CCGT
Table 9 MEX CCGT results in overview: Electricity production costs (LCOE) - Sensitivity relative
to Base Case Assumptions. Units: $/MWh el.
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6.2 Conclusions
The price of natural gas (NG) and its expected development strongly impacts the economic
attractiveness of HYSOL solutions relative to NG based competing technologies, such as OCGT
and CCGT power plants.
CO2 emission costs acts heavily in favour of HYSOL solutions. As seen from Tables 4-6 (as
expected) in particular an OCGT plant solution is strongly exposed to potential rising CO2
emission costs.
The capacity of a HYSOL plant is defined by the size of firm capacity it may substitute being
part the power system in question (MEX). This impacts the required capacity investments for
competing solutions (OCGT or CCGT) matching the HYSOL plant in the system. The economic
implication of different capacity assignments, however, as seen from Tables 4-6, is relatively
minor. This due to the relative low initial investment component for OCGT and CCGT plants,
which may be seen comparing power price composition results shown in Tables 1-3.
The period analysed and the lifetime of the initial investments has minor impact on the
electricity production cost for the OCGT and CCGT plant solutions. Being an initial investment
intensive RES based technology the HYSOL solution is seen to be impacted, though
moderately, from changes in lifetime of the investment.
The interest rate or the rate of calculation is important for initial investment intensive plants,
such as the HYSOL solution. In Base Case a rate of calculation of 4% p.a. has been assumed,
which may correspond to typical socio-economic conditions. Assuming a higher rate of interest
of 10% p.a., that may resemble a corporate economic situation, it is seen from Table 4 that
power production costs (LCOE) are increased substantially. Thus, in particular the HYSOL
solution is very sensitive to changes in the interest rate.
HYSOL solutions, being investment intensive are as such very sensitive to changes in the
overall investment costs, and the rate of interest, whereas the OCGT and CCGT solutions are
considerable less exposed to changes in the overall investment.
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7 Appendix
7.1 Assumption on NG and Biogas price relation
It has been assumed that the price of Biogas can be estimated to equal the price of natural
gas (NG) plus the cost for the CO2 emission using the NG.
A CO2 emission cost, as assumed in our case study, of 40$/ton CO2 emitted corresponds to a
rise of the NG price with an extra 8.17$/MWh NG. For the case of 40$/ton CO2 emitted this
means that the Biogas price will equal the NG price plus 8.17$/MWh NG.
With a NG price of 13.31 $/MWh NG the assumption thus implies:
Biogas price = NG price + 8.17$/MWh = 13.31 $/MWh + 8.17$/MWh = 21.48$/MWh NG
If it is furthermore assumed that Biogas has zero CO2 emission the economic consequence of
the use of biogas in a HYSOL plant solutions will correspond to the cost relations to the OCGT
and CCGT solutions assuming 40$/ton CO2 emitted . However in this case the HYSOL solution
using Biogas has no CO2 emission.
The economic calculations shown in Figure 2 and Figure 4 showing power production costs
(LCOE) for the HYSOL solution relative to the OCGT and CCGT solutions will hold also for the
case where HYSOL use Biogas and thus has no CO2 emission and the OCGT and CCGT use NG
and emit CO2 at a cost of 40$/ton CO2 emitted.
Republic of South Africa (RSA): Economic
assessment and energy system analysis
Deliverable nº: 6.1.4
EC-GA nº: 308912 Project full title: Innovative Configuration for a Fully
Renewable Hybrid CSP Plant WP: Responsible partner: DTU/MAN/SYS Dissemination level:
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TABLE OF CONTENTS
1 DOCUMENT HISTORY ..................................................................................................... 4
2 EXECUTIVE SUMMARY ................................................................................................... 4
2.1 ABSTRACT ......................................................................................................................... 4
3 FEASIBILITY STUDY ON HYSOL CSP .................................................................................. 5
3.1 INTRODUCTION .................................................................................................................. 5
3.1.1 Example studied .......................................................................................... 5
3.1.2 The HYSOL alternative and competing technology .................................... 6
4 APPROACH AND BASIC ASSUMPTIONS ........................................................................... 6
4.1 ECONOMIC INDICATOR ........................................................................................................ 6
4.2 BASE CASE ASSUMPTIONS ................................................................................................... 6
4.3 BASE CASE FOR RSA HYSOL PLANT ...................................................................................... 7
4.4 BASE CASE OVERVIEW AND ISSUES ADDRESSED VIA SENSITIVITY ANALYSES ................................... 7
4.5 ELECTRICITY COSTS AS FUNCTION OF LOAD FACTOR AND NG PRICE ............................................. 8
4.6 DESIGN POINT ASSUMPTIONS .............................................................................................. 8
5 HYSOL RELATIVE TO OCGT AND CCGT ............................................................................. 9
5.1 BASIC PRESENTATIONS ........................................................................................................ 9
5.1.1 Assumption on CO2 emission costs ............................................................ 9
5.1.2 Assumption on NG and Biogas price relation ........................................... 10
5.2 RESULTS: HYSOL COMPARED TO OCGT .............................................................................. 11
5.3 RESULTS: HYSOL COMPARED TO CCGT .............................................................................. 12
5.4 POWER PRICE COMPOSITION .............................................................................................. 13
6 SENSITIVITY ANALYSES AND CONCLUSIONS .................................................................. 15
6.1 OVERVIEW OF SENSITIVITY ANALYSES ................................................................................... 15
6.2 CONCLUSIONS ................................................................................................................. 17
7 APPENDIX .................................................................................................................... 19
7.1 ASSUMPTION ON NG AND BIOGAS PRICE RELATION ............................................................... 19
Acronyms
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1 Document History
Version Status Date
vX.Y Draft day/month/year
vX.Y Final day/month/year
Approval Name Date
Prepared day/month/year
Reviewed day/month/year
Authorised day/month/year
2 Executive Summary
2.1 Abstract
Concentrating Solar Power (CSP) plants utilize thermal conversion of direct solar irradiation. A
trough or tower configuration focuses solar radiation and heats up oil or molten salt that
subsequently in high temperature heat exchangers generate steam for power generation.
High temperature molten salt can be stored and the stored heat can thus increase the load
factor and the usability for a CSP plant, e.g. to cover evening peak demand. In the HYSOL
concept (HYbrid SOLar) such configuration is extended further to include a gas turbine fuelled
by upgraded biogas or natural gas. The optimised integrated HYSOL concept, therefore,
becomes a fully dispatchable (offering firm power) and fully renewable energy source (RES)
based power supply alternative, offering CO2-free electricity in regions with sufficient solar
resources.
The economic feasibility of HYSOL configurations is addressed in this report. The CO2 free
HYSOL alternative is discussed relative to conventional reference firm power generation
technologies. In particular the HYSOL performance relative to new power plants based on
natural gas (NG) such as open cycle or combined cycle gas turbines (OCGT or CCGT) are in
focus. The feasibility of renewable based HYSOL power plant configurations attuned to specific
electricity consumption patterns in selected regions with promising solar energy potentials are
discussed
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3 Feasibility study on HYSOL CSP
Feasibility study on HYSOL CSP configurations with High Temperature Storage and NG/Bio-gas
fuelled Gas Turbine providing Fully Dispatchable and Renewable Power Supplies.
3.1 Introduction
Concentrating Solar Power (CSP) plants utilize thermal conversion of direct solar irradiation. A
trough or tower configuration focus solar radiation and heat up oil or molten salt that
subsequently in high temperature heat exchangers generate steam for power generation.
High temperature molten salt can be stored (HTS) and the stored heat can thus increase the
load factor and the usability for a CSP plant, e.g. to cover night (peak) demand. In the HYSOL
concept (HYbrid SOLar) such configuration is extended further to include a gas turbine fuelled
by upgraded biogas or natural gas. The optimised integrated HYSOL concept, therefore,
becomes a fully dispatchable (offering firm power) and a fully renewable energy (RES) based
power supply alternative, offering CO2-free electricity in regions with sufficient solar
resources.
The economic feasibility of HYSOL configurations is addressed. The CO2 free HYSOL alternative
is discussed relative to conventional reference firm power generation technologies. In
particular the HYSOL performance relative to new power plants based on natural gas (NG) such
as open cycle or combined cycle gas turbines (OCGT or CCGT) are in focus. The feasibility of
renewable based HYSOL power plant configurations attuned to specific electricity consumption
patterns in selected regions with promising solar energy potentials are discussed.
3.1.1 Example studied
The analytical approach used is illustrated for a HYSOL configuration optimised to conditions
seen in the Republic of South Africa (RSA). The HYSOL Power Plant studied has been attuned to
solar potentials and power system characteristics resembling conditions in the Republic of
South Africa (RSA).
The RSA HYSOL plant configuration particularizes the basic HYSOL outline by the choices:
- A CSP Tower configuration has been assumed. HYSOL configurations can also be
applied with CSP trough design.
- No biogas plant and biogas supply have been assumed for this RSA case. HYSOL’s
100% renewable configuration would have a biogas plant included and would use biogas
upgraded to NG quality.
The RSA HYSOL configuration analysed uses natural gas (NG) and not biogas based methane,
and may thus not be termed fully renewable, - though being a firm, fully dispatch-able and
mainly renewables based power plant.
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3.1.2 The HYSOL alternative and competing technology
This present analyses compare electricity production costs for a HYSOL plant alternative to
production cost for conventional power plant solutions or reference plants.
In this RSA case it has been assumed that the main competing reference technologies are an
Open Cycle Gas Turbine (OCGT) and an
Combined Cycle Gas Turbine (CCGT)
using natural gas (NG).
4 Approach and basic assumptions
4.1 Economic indicator
Basically a socio-economic approach is applied. And generally main focus is placed on the
economic indicator LCOE (the levelized cost of electricity), and on the sensitivity of the LCOE in
particular to variations in the two parameters:
• load factor or the number of full load hours per year, and the
• price of natural gas (given as the levelized NG price covering the period analysed)
The solar potential and the annual power production heavily impact the HYSOL power plant
economy. And for fossil based competing reference technologies fuel cost and CO2 emission
cost developments constitute important framework conditions. LCOE dependency on in
particular these major parameters will be in focus in this study of (predominantly) renewable
energy source (RES) based HYSOL solutions relative to fossil based conventional reference
power plant solutions.
4.2 Base Case assumptions
For the present socio-economic analyses the following general assumptions have been
adopted as 'Base Case':
Price level: Year 2015
Socio economic rate of calculation (rate of interest): 4 % p.a.
Project base year: 2020
Period analysed: Time period: 2021-2045
Period in years: 25 years
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4.3 Base Case for RSA HYSOL plant
Chosen Base Case for the RSA HYSOL plant annual production, assigned capacity and load
factor are:
Annual electricity production: 1014.06 GWh/year
Assigned HYSOL capacity (PH): PH = 150MWel
Annual full load hours (HFLH) and Load factor (LF):
HFLH = 1014.06GWh / 150MW = 6760.4 hours/year
and LF= 6760.4/8760= 0.772
As mentioned, gas consumed in the RSA HYSOL gas turbine (GT) component is assumed to be
natural gas (NG). The RSA Base Case NG price and the sensitivity variations analysed for the
NG price are:
NG price Base case: 23.88 $/MWh (7$/MMBtu)
Sensitivity: Base Case +/- 20%, +/-40%
Data on investments, operation and maintenance costs for the RSA HYSOL configuration are
found in the Appendix.
4.4 Base Case overview and issues addressed via sensitivity analyses
Electricity production costs (LCOE) are furthermore analysed for its dependence on or
sensitivity to variations in the following parameters:
• Natural Gas price: Sensitivity Base Case -/+40%
• CO2 emission quota market price Base case: 0 $ / ton CO2
Sensitivity: 40 $ / ton CO2
• Capacity assignment: assignment Base case: 150 MW
Sensitivity: 100MW <--> 180MW
• Lifetime of initial investment: Base case: 25 years
Sensitivity: 20 years
• Rate of calculation (interest rate) Base case: 4.0 % p.a.
Sensitivity: 10.0 % p.a.
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• Initial investment (CAPEX) Sensitivity: Base Case +/- 20%
The combined steam turbine (ST) and gas turbine (GT) capacity in the RSA HYSOL configuration
plant has been assigned a total combined capacity of 150MW. The peak power generated by
the plant is thus limited to 150 MW, and the plant is made to follow a demand curve
congruent or analogous to that of country altogether. This implies that the number of full load
hours for the combined RSA HYSOL configuration can be calculated as 1014.06GWh/150MW =
6760 hours/year, and the demand coverage rate is above 99.9%.
4.5 Electricity costs as function of load factor and NG price
In Figures 1-4 results on the LCOE (given along the y-axis) are shown as a function of the
annual load. The annual load or electricity production, - here expressed through its equivalent,
the number of full load hours per year, is shown along the x-axis.
HYSOL plant operation at different load factors is assumed to maintain the relative ST and GT
contribution to the electricity production. Thus, even the annual power production may differ
from the Base Case assumption the %-split of production contributions from the ST and GT
HYSOL plant components is assumed constant. And the share of the annual production based
on gas (via the GT directly and indirectly via GT flue gas heat recovered and utilized by the ST)
is kept constant.
Furthermore, for this feasibility analysis the HYSOL plant operation efficiency is assumed
constant, - even at e.g. lower annual production levels. And gas consumption per MWh
electricity generated, accordingly, is assumed constant and independent of the annual
production. This may be a somewhat rough assumption.
4.6 Design Point assumptions
Assumptions used as basis for optimizing and configuring the HYSOL plant, will in the following
be termed the 'Design Point' data assumptions. Yellow points, 'Design Points', shown in Figures
1-4 represent results for the RSA HYSOL plant assuming Base Case operation conditions. Black
points, correspondingly, represent (OCGT or CCGT) reference technology results based on
equivalent assumptions. Other results presented may thus be considered as sensitivity and
parameter analyses.
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5 HYSOL relative to OCGT and CCGT
5.1 Basic presentations
In what follows the RSA HYSOL plant alternative is compared to competing 'conventional' or
reference plant solutions based on equivalent system framework condition. Benchmarked via
the LCOE the competing technologies are evaluated using equivalent general assumptions. The
so-called Base Case data assumptions form the core for this feasibility comparison. For
selected key parameters LCOE consequences of data deviating from Base Case are covered via
sensitivity analyses.
As mentioned above the competing reference technologies assumed are the Open Cycle Gas
Turbine (OCGT) and the Combined Cycle Gas Turbine (CCGT).
For consistency of the comparison it is assumed, that the average annual electricity production
is the same for the HYSOL alternative and for the reference plants. Furthermore, plants being
compared are assumed to have the same capacity value in the South African power system,
and the plants are assumed to be fully dispatchable (firm power). Thus, all plants are assumed
to be able to occupy the same position of operation in the overall power system dispatch.
Data for the RSA HYSOL alternative and for the assumed RSA OCGT and RSA CCGT reference
power plants are found in the Appendix.
It can be observed from Figures 1-4 that the annual number of full load operation hours for the
HYSOL plant, shown along the x-axis, is extremely important for the electricity production cost
achieved, - and the plant economy. Low annual power production results in high production
costs. For the overall economy of a HYSOL plant, therefore, it is very important to achieve high
annual power production, as the total production costs are much dominated by high initial
investments. Natural gas prices, however, have minor impact on the HYSOL power production
cost due to the relatively low electricity production contribution via the GT part of the RSA
HYSOL configuration.
5.1.1 Assumption on CO2 emission costs
Comparison of HYSOL solutions relative to conventional OCGT and CCGT power plant solutions
are carried out for cases with and without inclusion of an assumed CO2 emission cost. For this
sensitivity analysis it has been assumed, as an example, that CO2 emission costs amounts to
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40$/tonCO2 emitted. For natural gas (NG) this CO2 emission cost is equivalent to 8.17$/MWh
NG. The CO2 emission cost assumed thus rises the NG price with an extra 8.17$/MWh NG.
5.1.2 Assumption on NG and Biogas price relation
It has been assumed that the price of Biogas can be estimated to equal the price of natural gas
(NG) plus the cost for the CO2 emission using the NG.
A CO2 emission cost, as assumed in our case study, of 40$/ton CO2 emitted corresponds to a
rise of the NG price with an extra 8.17$/MWh NG. Thus, for the case of 40$/ton CO2 emitted
this means that the Biogas price will equal the NG price plus 8.17$/MWh NG.
With a NG price of 23.88$/MWh NG the assumption thus implies:
Biogas price = NG price + 8.17$/MWh
= 23.88$/MWh + 8.17$/MWh = 32.05$/MWh NG
If it is furthermore assumed that Biogas has zero CO2 emission the economic consequence of
the use of biogas as fuel in HYSOL plant solutions will correspond to fuel costs as for NG plus its
CO2 cost. The fuel price relations for HYSOL, OCGT and CCGT solutions thus correspond to the
NG price including CO2 costs. However in this case the HYSOL solution using Biogas has no
CO2 emission.
The economic calculations shown in Figure 2 and Figure 4 showing power production costs
(LCOE) for the HYSOL solution relative to the OCGT and CCGT solutions, therefore, will hold
also for the case where HYSOL use Biogas (and thus has no CO2 emission) and the OCGT and
CCGT use NG and emit CO2 at a cost of 40$/ton CO2 emitted.
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5.2 Results: HYSOL compared to OCGT
HYSOL and OCGT: Assuming 0 $/ton CO2 emitted
Figure 1 Electricity production costs for Open Cycle Gas Turbine (OCGT) and RSA HYSOL
configuration, as function of load factor and NG price. Assumed: CO2 costs = 0$/tonCO2,
R=4%p.a., Lifetime=25years. Unit: $/MWh el.
HYSOL and OCGT: Assuming 40 $/ton CO2 emitted
Figure 2 Electricity production costs for Open Cycle Gas Turbine (OCGT) and RSA HYSOL
configuration, as function of load factor and NG price. Assumed: CO2 costs = 40$/tonCO2,
R=4%p.a., Lifetime=25years. Unit: $/MWh el.
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5.3 Results: HYSOL compared to CCGT
HYSOL and CCGT: Assuming 0 $/ton CO2 emitted
Figure 3 Electricity production costs for Combined Cycle Gas Turbine (CCGT) and RSA HYSOL
configuration, as function of load factor and NG price. Assumed: CO2 costs = 0$/tonCO2,
R=4%p.a., Lifetime=25years. Unit: $/MWh el.
HYSOL and CCGT: Assuming 40 $/ton CO2 emitted
Figure 4 Electricity production costs for Combined Cycle Gas Turbine (CCGT) and RSA HYSOL
configuration, as function of load factor and NG price. Assumed: CO2 costs = 40$/tonCO2,
R=4%p.a., Lifetime=25years. Unit: $/MWh el.
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5.4 Power price composition
LCOE results based on Design Point assumptions (shown as yellow and black points in Figures
1-4) are presented below with a breakdown or split into its components related to respectively
Investment, O&M, and Fuel cost parts.
CO2 emission costs of 0 $/ton CO2 emitted is assumed:
HYSOL Table 1 RSA HYSOL alternative: Electricity production cost (LCOE on socio economic basis)
for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost.
OCGT Table 2 RSA 150MW OCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and
Fuel Cost parts to the total cost. OCGT capacity: 150MW.
CCGT Table 3 RSA 150MW CCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and
Fuel Cost parts to the total cost. CCGT capacity: 150MW.
Electricity production costs (LCOE) split on cost components
at 'design basis point' data Investment O & M Fuel costs
Total
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
66.78 100.0% 48.27 72.3% 2.12 3.2% 16.39 24.5%
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
84.39 100.0% 7.23 8.6% 1.00 1.2% 76.15 90.2%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
53.52 100.0% 8.69 16.2% 1.49 2.8% 43.34 81.0%
at 'design basis point' data Investment O & M Fuel costs
Total
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CO2 emission costs of 40 $/ton CO2 emitted are included in the NG fuel costs shown:
HYSOL Table 4 RSA HYSOL alternative: Electricity production cost (LCOE on socio economic basis) for
'design basis' assumptions split on contributions from the Investment, O&M, and Fuel Cost parts
to the total cost. Biogas use has been assumed for the HYSOL GT component.
OCGT Table 5 RSA 150MW OCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost. OCGT capacity: 150MW. CO2 emission costs are included in the
fuel costs shown.
CCGT Table 6 RSA 150MW CCGT reference: Electricity production cost (LCOE on socio economic
basis) for 'design basis' assumptions split on contributions from the Investment, O&M, and Fuel
Cost parts to the total cost. CCGT capacity: 150MW. CO2 emission costs are included in the
fuel costs shown.
Table 1 illustrates, as expected, that power production costs from the RSA HYSOL plant are
dominated by the investment cost component. On average for the period analysed of about
75% of the total electricity costs relates to the initial investment, whereas the fuel cost
component only contributes about 10% to the total costs. Compared to results for OCGT and
CCGT plants shown in Table 2 and Table 3, this illustrates that HYSOL plants are less exposed
and less vulnerable to gas price (and CO2 emission cost) uncertainty.
Electricity production costs (LCOE) split on cost components
at 'design basis point' data Investment O & M Fuel costs
Total
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
72.39 100.0% 48.27 66.7% 2.12 2.9% 22.00 30.4%
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
110.44 100.0% 7.23 6.6% 1.00 0.9% 102.20 92.5%
at 'design basis point' data Investment O & M Fuel costs
Total
Electricity production costs (LCOE) split on cost components
$/MWh el % of tot $/MWh el % of tot $/MWh el % of tot $/MWh el % of tot
68.35 100.0% 8.69 12.7% 1.49 2.2% 58.17 85.1%
at 'design basis point' data Investment O & M Fuel costs
Total
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6 Sensitivity analyses and conclusions
6.1 Overview of sensitivity analyses
Sensitivity analyses shown in Tables 7-9 describe how power productions costs (LCOE) deviate
from results based on Base Case and 'design point' assumptions, if one parameter only is
changed at a time.
Blue vertical lines in Tables 7-9 represent the LCOE calculated from Base Case assumptions.
Tables 1-3, shown above, thus give details on the Base Case results, that are 'starting points'
for the sensitive analysis results shown below, - for the RSA HYSOL, RSA OCGT and RSA CCGT
plants respectively.
RSA HYSOL
Table 7 RSA HYSOL results in overview: Electricity production costs (LCOE) - Sensitivity relative
to Base Case Assumptions. Units: $/MWh el.
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RSA OCGT
Table 8 RSA OCGT results in overview: Electricity production costs (LCOE) - Sensitivity relative
to Base Case Assumptions. Units: $/MWh el.
RSA CCGT
Table 9 RSA CCGT results in overview: Electricity production costs (LCOE) - Sensitivity relative
to Base Case Assumptions. Units: $/MWh el.
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6.2 Conclusions
The price of natural gas (NG) and its expected development strongly impacts the economic
attractiveness of HYSOL solutions relative to NG based competing technologies, such as OCGT
and CCGT power plants.
CO2 emission costs acts heavily in favour of HYSOL solutions. As seen from Tables 4-6 (as
expected) in particular an OCGT plant solution is strongly exposed to potential rising CO2
emission costs.
The capacity of a HYSOL plant is defined by the size of firm capacity it may substitute being
part the power system in question (RSA). This impacts the required capacity investments for
competing solutions (OCGT or CCGT) matching the HYSOL plant in the system. The economic
implication of different capacity assignments, however, as seen from Tables 4-6, is relatively
minor. This due to the relative low initial investment component for OCGT and CCGT plants,
which may be seen comparing power price composition results shown in Tables 1-3.
The period analysed and the lifetime of the initial investments has minor impact on the
electricity production cost for the OCGT and CCGT plant solutions. Being an initial investment
intensive RES based technology the HYSOL solution is seen to be impacted, though
moderately, from changes in lifetime of the investment.
The interest rate or the rate of calculation is important for initial investment intensive plants,
such as the HYSOL solution. In Base Case a rate of calculation of 4% p.a. has been assumed,
which may correspond to typical socio-economic conditions. Assuming a higher rate of interest
of 10% p.a., that may resemble a corporate economic situation, it is seen from Table 4 that
power production costs (LCOE) are increased substantially. Thus, in particular the HYSOL
solution is very sensitive to changes in the interest rate.
HYSOL solutions, being investment intensive are as such very sensitive to changes in the
overall investment costs, and the rate of interest, whereas the OCGT and CCGT solutions are
considerable less exposed to changes in the overall investment.
Summary RSA conclusion:
The HYSOL solution in RSA competes favourable relative to the Open Cycle Gas Turbine (OCGT)
reference as can be seen from comparing results when base case data are assumed. This
conclusion holds even without taking into account an assumed cost on emission of CO2. When
compared to a Combined Cycle Gas Turbine (CCGT) reference plant the RSA HYSOL alternative
is less favourable. However, introducing an assumed CO2 emission costs of 40$/ton CO2
emitted, narrows the LCOE price difference considerable (- down to a LCOE difference of less
than 5$/MWh el). Sensitivity analyses shown illustrate the order of magnitude of LCOE price
impacts as consequence of potential uncertainties in the assumed base case data. And it can
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be noted that the narrow price difference calculated (HYSOL versus CCGT) in base case is
relatively small compared to the span in price variations seen via sensitivity analyses.
Sensitivity (or robustness) analyses carried out emphasize that HYSOL solutions, as expected,
are less exposed to CO2 emission cost uncertainty and fuel price uncertainty than the
reference OCGT/CCGT solutions. OCGT/CCGT solutions are more exposed to CO2 emission cost
uncertainty, and more exposed to NG-price uncertainty, but less exposed to investment cost
uncertainty.
However, as observed from Figures 1-4 the annual number of full load operation hours for
HYSOL solutions, and thus the annual power production, is very important the plant economy.
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7 Appendix
7.1 Assumption on NG and Biogas price relation
It has been assumed that the price of Biogas can be estimated to equal the price of natural
gas (NG) plus the cost for the CO2 emission using the NG.
A CO2 emission cost, as assumed in our case study, of 40$/ton CO2 emitted corresponds to a
rise of the NG price with an extra 8.17$/MWh NG. For the case of 40$/ton CO2 emitted this
means that the Biogas price will equal the NG price plus 8.17$/MWh NG.
With a NG price of 23.88 $/MWh NG the assumption thus implies:
Biogas price = NG price + 8.17$/MWh = 23.88 $/MWh + 8.17 $/MWh = 32.05 $/MWh NG
If it is furthermore assumed that Biogas has zero CO2 emission the economic consequence of
the use of biogas in a HYSOL plant solutions will correspond to the cost relations to the OCGT
and CCGT solutions assuming 40$/ton CO2 emitted . However in this case the HYSOL solution
using Biogas has no CO2 emission.
The economic calculations shown in Figure 2 and Figure 4 showing power production costs
(LCOE) for the HYSOL solution relative to the OCGT and CCGT solutions will hold also for the
case where HYSOL use Biogas and thus has no CO2 emission and the OCGT and CCGT use NG
and emit CO2 at a cost of 40$/ton CO2 emitted.