Journal
IEEE TRANSACTIONS ON POWER SYSTEMS
Volume 27, Issue 4, Pages 2127-2137Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2012.2190430
Keywords
Mix of Normals distribution; power generation economics; thermal power generation; wind power generation
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Funding
- UK Research Councils under NERC award [NE/C513169/1]
- U.K. EPSRC Supergen Flexnet program
- U.S. National Science Foundation through EFRI Grant [0835879]
- Natural Environment Research Council [NE/C513169/1] Funding Source: researchfish
- Directorate For Engineering
- Emerging Frontiers & Multidisciplinary Activities [0835879] Funding Source: National Science Foundation
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Modeling the dynamics of merchant generation investment in market environments can inform the making of policies whose goals are to promote investment in renewable generation while maintaining security of supply. Such models need to calculate expected output, costs and revenue of thermal generation subject to varying load and random generator outages in a power system with high penetrations of wind. This paper presents a dynamic investment simulation model where the short-term energy market is simulated using probabilistic production costing using the Mix of Normals distribution (MOND) technique to represent residual load (load net of wind output). Price mark-ups due to market power are accounted for. An energy-only market setting is used to estimate the economic profitability of investments and forecast the evolution of security of supply. Simulated results for a Great Britain (GB) market case study show a pattern of increased relative security of supply risk during the 2020s. In addition, many new investments can recover their fixed costs only during years in which more frequent supply shortages push energy prices higher.
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