Optimal mix analyses of renewable power generation in the ......Installed Capacity 2010 Total 6344...

Optimal mix analyses of renewable power generation in the MENA region: A case study of Morocco

Under the Supervision of

By: Alaa Alhamwi

19.03.2013

Prof. Dr. Dirk Dahlhaus Prof. Dr. Adel Khalil

Dr. Thomas Vogt

This study aims to quantify the optimal mix of renewables in Morocco by 2020

for three different scenarios.

2/27 19.03.2013 Alaa Alhamwi - Optimal Mix Analyses

Source: (Dii , 2012)

Outline

Introduction

Country Electricity Profile

Methodology

» Optimal mix analysis

» Scenarios definition

Results and Findings

Discussion and Conclusion

Recommendations

References

19.03.2013 Alaa Alhamwi - Optimal Mix Analyses 3/27

Motivation

» “supply and demand for renewable energy are complementary in the south and north in all seasons” (Dii, 2012)

» “A well balanced mix of renewable energies can replace electricity from fossil fuels” (MED-CSP, 2005)

19.03.2013 Alaa Alhamwi - Optimal Mix Analyses

Introduction

Source: (Dii , 2012)

4/27

Introduction

» Renewables have a fluctuated and dynamic behaviour.

» What is the optimal mix of renewables?


Outline

Introduction


Methodology





Recommendations

References




Why Morocco?

» Renewables potential

» Strategy for renewable power supply

» Data availability and accessibility

58% 14%

14%

14%

Installed Capacity 2020 Total 14580 MW

6000 MW Renewables

Fossils

Hydro

Wind

Solar

27.9%

68.6%

3.5%

Installed Capacity 2010 Total 6344 MW

1991 MW Renewables

Hydro

Fossils

Wind

Source: (MEMEEE ,2009) Source: (COMELEC, 2010)



Load curve in Morocco

Morocco Load curve for 365 days in 2010 (hourly resolution)

Morocco Load curve for the first week in 2010 (hourly resolution)



2000

2200

2400

2600

2800

3000

3200

3400

3600

3800

4000

1 3 5 7 9 11 13 15 17 19 21 23 Day [Hours]

Load

[MW

]

Load curve

» Two peak periods per day

» The average base load is about 2400 MW and average highest load is almost 4000 MW

Load curve for an average day in 2010

Outline

Introduction


Methodology





Recommendations

References


Limitations

» Data availability

» Geographical limitation (Morocco)

» Time horizon is 2020

The modeling between wind CSP, PV and hydropower power generations for three scenarios in Morocco by 2020

Assumptions

» Morocco is treated as ‘copper-plate’

» Maximum hydropower 20%

» Fossil and hydropower are time independent

» Load curve development 2020

19.03.2013 11/27 Alaa Alhamwi - Optimal Mix Analyses

Methodology

‘copper-plate’ means that electricity power can flow unconstrained from any generation site to any demand site

Methodology

Optimal mix model:

» Mismatch energy (Heide et al. 2011):

γ is the excess or surplus generation factor.

W(t): total wind power generation during time t.

<W>: average wind power generation over all the period.

Sc (t), Sp (t), Hy(t), F(t) and L (t) are the CSP, PV, hydropower, fossil fuels power generations and load power generations time series, respectively

Hydropower and fossil fuels are time independent

a, bc, bp , h and f are coefficients represent of how much of the load is covered by wind, solar and fossil power generation.

• a+ bc+bp+h+f= 1


1;L

L(t)F(t)f

Hy

Hy(t)h

Sp

(t)Sp

pb

Sc

(t)Scc

bW

W(t)a*γΔ(t)

F


L

L(t)fh

Sp

(t)Sp

pb

Sc

(t)Scc

bW

W(t)aγ*Δ(t)

Methodology

Development of optimal mix model:

» Standard deviation approach

» Storage model approach

H(t): total storage during time t

EH : required storage


22

Δ ΔΔσ

0)()(

0)()()1()(

1

tift

tifttHtH

in

out

)H(t'tt'

minH(t)t'

maxH

E

EH

Required storage

EH

Required storage

Methodology

Analytical Approach

Modelling for 3 scenarios Discussion of results

Electricity power output

Solar electricity output

(CSP and PV) Wind electricity output

Data collection and preparing

Meteorological Data Collection

(Solar and wind)

Load curve Data Collection

(2010)


Methodology

Scenarios definition by 2020:


Wind a

Solar b CSP&PV

Hydro h

Fossil f

Share of renewables

Scenario 1 14% Optimal mix 14% 58% 42%

Scenario 2 Optimal mix of technologies 58% a+b+h=42%

Scenario 3 Optimal mix of technologies -------

a+b+h=100%

Outline

Introduction

Country Electricity Profile:

Methodology





Recommendations

References




Storage model approach

» Case 1: Ideal storage and no excess energy



Storage model approach

» Case 1: Ideal storage and no excess energy


Scenarios Approach Wind

a CSP bc

PV bp

Hydro h

Fossil f

RE share

Scenario 1

Standard deviation 0.1 0.14 0.14 0 0.14 0.58 0.42

Storage Approach

η=1 , γ =1 269 0.14 0.12 0.02 0.14 0.58 0.42

η=0.9 , γ =1.1 50 0.14 0.14 0 0.14 0.58 0.42

Scenario 2

Standard deviation 0.3 0 0 0.22 0.2 0.58 0.42

Storage Approach

η=1 , γ =1 245 0.02 0.1 0.1 0.2 0.58 0.42

η=0.9 , γ =1.1 27 0.02 0.2 0 0.2 0.58 0.42

Scenario 3

Standard deviation 1.01 0 0 0.8 0.2 0 1

Storage Approach

η=1 , γ =1 364 0 0.12 0.68 0.2 0 1

η=0.9 , γ =1.1 189 0.31 0.05 0.44 0.2 0 1



Energy generated TWh Power capacity GW

Scenario 3: 100% renewables Scenario 3: 100% renewables

I

II

I

II

Case 1

η=1, γ =1

Case 2

η=0.9, γ =1.1

Case 1

η=1, γ =1

Case 2

η=0.9, γ =1.1

Wind 0 0 20 0 0 6.6

Solar CSP 0 7 3 0 3.2 1.5

Solar PV 46 39 28 15.5 18 12.8

Hydro 12 12 13 5.5 5.5 6.1

Total 58 58 64 21 26.7 27


Energy generated and capacity for scenario 3 Optimal mix approach I: 0% wind, 0% CSP, 80% PV and 20% hydropower Optimal mix approach II: Case 1: 0% wind, 12% CSP, 68% PV and 20% hydropower Case 2: 31% wind, 5% CSP, 44% PV and 20% hydropower

Load factors are: 34% for wind load factor, and 25% for CSP and PV and 24% for hydropower

Outline

Introduction


Methodology





Recommendations

References



Discussion

Supply and demand for Scenario 3:

Wind CSP PV Hydro Required

Storage

SM2 31% 5% 44% 20% 189

SM4 21% 13% 46% 20% 165


Discussion

Supply and demand for Scenario 3:

Wind CSP PV Hydro Required

Storage

SM2 31% 5% 44% 20% 189

SM4 21% 13% 46% 20% 165

Method insensitivity


Discussion

Normalized load, PV and CSP SM2 Power generations

Normalized load, PV and CSP SM4 Power generations

Conclusions

Nature could determine how to design a future power supply system based on renewables: in case of η=90% (pumped hydro storage) and γ=1.1

» Scenario 1: 14% wind, 14% CSP, 0% PV, 14% hydro and 58% fossil

» Scenario 2: 2% wind, 20% CSP, 0% PV, 20% hydro and 58% fossil

» Scenario 3: 31% wind, 5% CSP, 44% PV and 20% hydro

The transition towards the renewable power supply system implies multiple challenges of various dimensions:

» technology

» economics

» ecological sustainability and

» social acceptance


Outline

Introduction


Methodology





Recommendations

References


Recommendations for further work

Sensitivity analysis for 35% solar capacity factor

Transitional scenarios could be analyzed by finding the optimal mix between renewable and non-renewable power generation in MENA region

Quantifying the optimal mix of 100% renewables for the MENA region by 2050

Further development could be done on the model to improve the sensitivity towards different renewable power technologies



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Optimal mix analyses of renewable power generation in the ......Installed Capacity 2010 Total 6344...

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