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.
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Source: (Dii , 2012)
Outline
Introduction
Country Electricity Profile
Methodology
» Optimal mix analysis
» Scenarios definition
Results and Findings
Discussion and Conclusion
Recommendations
References
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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)
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Introduction
Source: (Dii , 2012)
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Introduction
» Renewables have a fluctuated and dynamic behaviour.
» What is the optimal mix of renewables?
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Outline
Introduction
Country Electricity Profile
Methodology
» Optimal mix analysis
» Scenarios definition
Results and Findings
Discussion and Conclusion
Recommendations
References
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Country Electricity Profile
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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)
Country Electricity Profile
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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)
Country Electricity Profile
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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
Country Electricity Profile
Methodology
» Optimal mix analysis
» Scenarios definition
Results and Findings
Discussion and Conclusion
Recommendations
References
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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
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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
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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
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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
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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)
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Methodology
Scenarios definition by 2020:
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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
» Optimal mix analysis
» Scenarios definition
Results and Findings
Discussion and Conclusion
Recommendations
References
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Results and Findings
Storage model approach
» Case 1: Ideal storage and no excess energy
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Results and Findings
Storage model approach
» Case 1: Ideal storage and no excess energy
Results and Findings
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
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Results and Findings
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
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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
Country Electricity Profile:
Methodology
» Optimal mix analysis
» Scenarios definition
Results and Findings
Discussion and Conclusion
Recommendations
References
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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
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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
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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
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Outline
Introduction
Country Electricity Profile:
Methodology
» Optimal mix analysis
» Scenarios definition
Results and Findings
Discussion and Conclusion
Recommendations
References
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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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