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Impact of Electricity Price Expectation in the Planning Period on the Evolution of Generation Expansion Planning in the Market Environment

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  • Xian Huang

    (School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China)

  • Kun Liu

    (School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China)

Abstract

With the continuous promotion of China’s electricity market reform, the introduction of competition in the power generation market provides a new research direction for the generation expansion planning (GEP) problem, which is of great significance in the promotion of the optimization of the power energy structure. In the context of marketization, the electricity price expectation during the planning period is a key factor of GEP for independent power generation groups. There is some literature showing that the electricity price expectation in the planning period can be estimated according to certain laws of market supply and demand, while it seems to us that a future Pay as Bid (PAB) mechanism is better to determine the electricity price expectation. In this paper, to explore the impact of these two different electricity price formation mechanisms on the evolution of the generation market, a multi-agent framework is first established to describe the interaction process among the generation market agents; then, a GEP model for independent power generation groups is developed in the market competition environment, and four representative scenarios are finally designed for detailed comparative studies. Based on these case studies, the conclusion can be summarized as: (1) the PAB bidding mechanism has a lower electricity price and higher market installed capacity almost all the time during the whole planning period for all four scenarios; (2) it is more important that PAB can reduce the impact of parameter uncertainty in the laws of market supply and demand, which can obtain more reliable and reasonable results regarding the long-term evolution of the generation market.

Suggested Citation

  • Xian Huang & Kun Liu, 2023. "Impact of Electricity Price Expectation in the Planning Period on the Evolution of Generation Expansion Planning in the Market Environment," Energies, MDPI, vol. 16(8), pages 1-21, April.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:8:p:3328-:d:1118974
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    References listed on IDEAS

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    1. Villalobos, Cristian & Negrete-Pincetic, Matías & Figueroa, Nicolás & Lorca, Álvaro & Olivares, Daniel, 2021. "The impact of short-term pricing on flexible generation investments in electricity markets," Energy Economics, Elsevier, vol. 98(C).
    2. Seddighi, Amir Hossein & Ahmadi-Javid, Amir, 2015. "Integrated multiperiod power generation and transmission expansion planning with sustainability aspects in a stochastic environment," Energy, Elsevier, vol. 86(C), pages 9-18.
    3. Mason, Karl & Qadrdan, Meysam & Jenkins, Nicholas, 2021. "Investing in generation and storage capacity in a liberalised electricity market: An agent based approach," Applied Energy, Elsevier, vol. 294(C).
    4. Radhanon Diewvilai & Kulyos Audomvongseree, 2022. "Optimal Loss of Load Expectation for Generation Expansion Planning Considering Fuel Unavailability," Energies, MDPI, vol. 15(21), pages 1-17, October.
    5. Aliabadi, Danial Esmaeili & Kaya, Murat & Şahin, Güvenç, 2017. "An agent-based simulation of power generation company behavior in electricity markets under different market-clearing mechanisms," Energy Policy, Elsevier, vol. 100(C), pages 191-205.
    6. Wu, Jiahui & Wang, Jidong & Kong, Xiangyu, 2022. "Strategic bidding in a competitive electricity market: An intelligent method using Multi-Agent Transfer Learning based on reinforcement learning," Energy, Elsevier, vol. 256(C).
    7. Sharan, Ishan & Balasubramanian, R., 2012. "Integrated generation and transmission expansion planning including power and fuel transportation constraints," Energy Policy, Elsevier, vol. 43(C), pages 275-284.
    8. Budi, Rizki Firmansyah Setya & Sarjiya, & Hadi, Sasongko Pramono, 2021. "Multi-level game theory model for partially deregulated generation expansion planning," Energy, Elsevier, vol. 237(C).
    9. Pereira, Adelino J.C. & Saraiva, João Tomé, 2011. "Generation expansion planning (GEP) – A long-term approach using system dynamics and genetic algorithms (GAs)," Energy, Elsevier, vol. 36(8), pages 5180-5199.
    10. Santiago Lemos-Cano & James McCalley, 2019. "Co-Optimized Analysis and Design of Electric and Natural Gas Infrastructures," Energies, MDPI, vol. 12(10), pages 1-16, May.
    11. Carlos Roberto de Sousa Costa & Paula Ferreira, 2023. "A Review on the Internalization of Externalities in Electricity Generation Expansion Planning," Energies, MDPI, vol. 16(4), pages 1-19, February.
    12. Choi, Dong Gu & Thomas, Valerie M., 2012. "An electricity generation planning model incorporating demand response," Energy Policy, Elsevier, vol. 42(C), pages 429-441.
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