christos tourkolias energy expert division for energy policy and planning
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LCOE as a policy tool to design RES-E support schemes Tourkolias C., Vougiouklakis Y., Papandreou V., Tigas K., Nakos C., Theofilidi M. Christos Tourkolias Energy expert Division for Energy Policy and Planning email: [email protected]. Problem. - PowerPoint PPT PresentationTRANSCRIPT
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Christos TourkoliasEnergy expert
Division for Energy Policy and Planningemail: [email protected]
LCOE as a policy tool to design RES-E support schemesTourkolias C., Vougiouklakis Y., Papandreou V., Tigas K., Nakos C., Theofilidi M.
6th International Scientific Conference on "Energy and Climate Change” Athens, 10/10/2013
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Problem Significant variations of RES-E production cost
Source: Ministry of Energy, Environment and Climate Change (2012) 10/10/2013
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Aim of the paper
Development of a methodological framework for the effective: evaluation of the existing RES-E support mechanisms design of the future RES-E support mechanisms
Examination of the potential fluctuations of RES-E production cost due to the uncertainties of the input parameters.
Indicative implementation of the proposed methodology for a typical wind and photovoltaic plant.
Potential utilization of the methodology for the rest types of RES.
6th International Scientific Conference on "Energy and Climate Change” 10/10/2013
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Methodological approach
6th International Scientific Conference on "Energy and Climate Change” 10/10/2013
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LCOE The Levelized Cost of Electricity (LCOE) refers to the overall
costs for the generation of electricity on the basis of net power supplied to the grid.
6th International Scientific Conference on "Energy and Climate Change” 10/10/2013
CC: Capital cost minus any investment tax credit or grantOM: Annual operational and maintenance costDR: Discount rateRV: Residual valueDEG: Degradation rateN: LifetimeDP: DepreciationIT : Interest paymentLN: Loan paymentTR: Taxation rate
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Monte Carlo simulation
Monte Carlo simulation evaluates iteratively the specified output using sets of random numbers for the examined input parameters.
6th International Scientific Conference on "Energy and Climate Change” 10/10/2013
Step I: Identification of input and output parameters.Step II: Generation of a set of random values for all input parameters from a probability distribution for a specified number of iterations. Step III: Assessment of the obtained results of output parameters.Step IV: Reiteration of the procedure utilizing different assumptions regarding the input parameters.Step V: Analysis of the results with the demonstration of appropriate histograms and summary statistics like mean or median value, variance etc.
Steps for the implementation of Monte Carlo analysis
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Study
7 different scenarios were evaluated for three different time slides, namely 2013, 2015 and 2020.
Input parameters (expressed with triangular distributions): Capital cost Operational & Maintenance cost Capacity factor Discount rate Loan share Interest rate All parameters
Output parameters: LCOE
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Assumptions
Wind2013 2015 2020
min mode max min mode max min mode maxCapital cost (€/kW) 1,100 1,200 1,400 1,070 1,100 1,250 990 1,040 1,200Discount rate (%) 8.0% 9.0% 11.0% 8.0% 9.0% 11.0% 7.0% 8.0% 10.0%
Loan (%) 30.0% 60.0% 70.0% 30.0% 60.0% 70.0% 30.0% 60.0% 80.0%Interest rate (%) 8.0% 9.0% 9.5% 6.0% 7.0% 8.0% 5.0% 6.0% 7.0%
Capacity factor (%) 21.0% 26.0% 35.0% 21% 26.0% 35.0% 21% 26.0% 35.0%O&M (%) 3.0% 3.4% 4.0% 2.0% 3.2% 4.0% 2.0% 3.0% 4.0%
PV2013 2015 2020
min mode max min mode max min mode maxCapital cost (€/kW) 1,000 1,250 1,400 950 1,100 1,184 865 1,000 1,075Discount rate (%) 8.0% 9.0% 11.0% 8.0% 9.0% 11.0% 7.0% 8.0% 10.0%
Loan (%) 0.0% 40.0% 70.0% 0.0% 50.0% 70.0% 30.0% 60.0% 80.0%Interest rate (%) 8.0% 9.0% 10.0% 6.0% 7.0% 9.0% 5.0% 6.0% 8.0%
Capacity factor (%) 16.0% 17.0% 18.7% 16.2% 18.0% 19.8% 17.1% 19.0% 20.9%O&M (%) 1.5% 2.5% 3.0% 1.5% 2.0% 3.0% 1.5% 2.0% 3.0%
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Results Wind - Variation
6th International Scientific Conference on "Energy and Climate Change” 10/10/2013
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Results Wind - Percentiles 2013
6th International Scientific Conference on "Energy and Climate Change” 10/10/2013
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Results Wind - Percentiles 2015
6th International Scientific Conference on "Energy and Climate Change” 10/10/2013
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Results Wind - Percentiles 2020
6th International Scientific Conference on "Energy and Climate Change” 10/10/2013
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Results PV- Variation
6th International Scientific Conference on "Energy and Climate Change” 10/10/2013
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Results PV- Percentiles 2013
6th International Scientific Conference on "Energy and Climate Change” 10/10/2013
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Results PV- Percentiles 2015
6th International Scientific Conference on "Energy and Climate Change” 10/10/2013
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Results PV- Percentiles 2020
6th International Scientific Conference on "Energy and Climate Change” 10/10/2013
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Conclusions
Significant decrease of LCOE until 2020 for both wind and photovoltaic energy.
Capacity factor for the case of wind energy and capital cost for photovoltaic energy are considered as the most uncertain parameters.
The continuous monitoring of LCOE with the simultaneous implementation of Monte Carlo analysis constitute as priority for the effective development of RES market.
Implementation of the proposed methodology for the rest types of RES.
Additional uncertainty techniques can be integrated into the methodology such as Fuzzy sets, ROV method etc.
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Thank you for your attention!
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