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Probabilistic evaluation of the long-term power system resource adequacy: The Greek case

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  • Simoglou, Christos K.
  • Bakirtzis, Emmanouil A.
  • Biskas, Pandelis N.
  • Bakirtzis, Anastasios G.

Abstract

This paper deals with the probabilistic evaluation of the long-term resource adequacy of an interconnected power system. An integrated software tool that solves the long-term scheduling problem using a sophisticated unit commitment model is employed, while both traditional capacity and flexibility adequacy concepts are addressed. A novel methodology to assess the flexibility adequacy using the operational power system schedule is presented. Multi-year simulations of the Greek interconnected power system on an hour-by-hour basis for the forthcoming 10-year study horizon (period 2018–2027) under a set of scenarios regarding the future operating conditions have been performed, providing the key operational data for the calculation of all probabilistic indicators. Test results indicate that the existence of all currently available thermal generating units as well as the timely realization of all scheduled construction plans is of utmost importance for the long-term secure and reliable operation of the Greek interconnected power system. In a more generalized framework, the ambitious EU goals regarding decarbonization and increasing RES shares in electricity generation should be accompanied by detailed studies in order to ensure that no resource adequacy problems will arise in the near future due to the massive withdrawal of conventional base-load and, possibly, flexible generating units.

Suggested Citation

  • Simoglou, Christos K. & Bakirtzis, Emmanouil A. & Biskas, Pandelis N. & Bakirtzis, Anastasios G., 2018. "Probabilistic evaluation of the long-term power system resource adequacy: The Greek case," Energy Policy, Elsevier, vol. 117(C), pages 295-306.
    • Handle: RePEc:eee:enepol:v:117:y:2018:i:c:p:295-306
    DOI: 10.1016/j.enpol.2018.02.047
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    References listed on IDEAS

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    1. Sadeghi, Hadi & Rashidinejad, Masoud & Abdollahi, Amir, 2017. "A comprehensive sequential review study through the generation expansion planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 1369-1394.
    2. Simoglou, Christos K. & Biskas, Pandelis N. & Vagropoulos, Stylianos I. & Bakirtzis, Anastasios G., 2014. "Electricity market models and RES integration: The Greek case," Energy Policy, Elsevier, vol. 67(C), pages 531-542.
    3. Koltsaklis, Nikolaos E. & Georgiadis, Michael C., 2015. "A multi-period, multi-regional generation expansion planning model incorporating unit commitment constraints," Applied Energy, Elsevier, vol. 158(C), pages 310-331.
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    Cited by:

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    2. Zhong, Zhiming & Fan, Neng & Wu, Lei, 2024. "Multistage Stochastic optimization for mid-term integrated generation and maintenance scheduling of cascaded hydroelectric system with renewable energy uncertainty," European Journal of Operational Research, Elsevier, vol. 318(1), pages 179-199.
    3. Mladen Zeljko & Marko Aunedi & Goran Slipac & Dražen Jakšić, 2020. "Applications of Wien Automatic System Planning (WASP) Model to Non-Standard Power System Expansion Problems," Energies, MDPI, vol. 13(6), pages 1-17, March.
    4. Christos K. Simoglou & Pandelis N. Biskas, 2023. "Capacity Mechanisms in Europe and the US: A Comparative Analysis and a Real-Life Application for Greece," Energies, MDPI, vol. 16(2), pages 1-32, January.
    5. Abadie, Luis Ma & Chamorro, José M., 2019. "Physical adequacy of a power generation system: The case of Spain in the long term," Energy, Elsevier, vol. 166(C), pages 637-652.
    6. Gao, Jianwei & Ma, Zeyang & Guo, Fengjia, 2019. "The influence of demand response on wind-integrated power system considering participation of the demand side," Energy, Elsevier, vol. 178(C), pages 723-738.
    7. Tsai, Chen-Hao & Figueroa-Acevedo, Armando & Boese, Maire & Li, Yifan & Mohan, Nihal & Okullo, James & Heath, Brandon & Bakke, Jordan, 2020. "Challenges of planning for high renewable futures: Experience in the U.S. midcontinent electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).

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