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Sustainable resource planning in energy markets

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  • Kamalinia, Saeed
  • Shahidehpour, Mohammad
  • Wu, Lei

Abstract

This study investigates the role of sustainable energy volatility in a market participant’s competitive expansion planning problem. The incomplete information non-cooperative game-theoretic method is utilized in which each generation company (GENCO) perceives strategies of other market participants in order to make a decision on its strategic generation capacity expansion. Sustainable generation incentives, carbon emission penalties, and fuel price forecast errors are considered in the strategic decisions. The market clearing process for energy and reserves is simulated by each GENCO for deriving generation expansion decisions. A merit criterion (i.e., the utility value) is proposed for a more realistic calculation of the expected payoff of a GENCO with sustainable energy resources. Finally, the impact of transmission constraints is investigated on the GENCO’s expansion planning decision. The case studies illustrate the effectiveness of the proposed method.

Suggested Citation

  • Kamalinia, Saeed & Shahidehpour, Mohammad & Wu, Lei, 2014. "Sustainable resource planning in energy markets," Applied Energy, Elsevier, vol. 133(C), pages 112-120.
    • Handle: RePEc:eee:appene:v:133:y:2014:i:c:p:112-120
    DOI: 10.1016/j.apenergy.2014.07.065
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    2. 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.
    3. Munoz, Francisco D. & van der Weijde, Adriaan Hendrik & Hobbs, Benjamin F. & Watson, Jean-Paul, 2017. "Does risk aversion affect transmission and generation planning? A Western North America case study," Energy Economics, Elsevier, vol. 64(C), pages 213-225.
    4. Chen, Qixin & Zou, Peng & Wu, Chenye & Zhang, Junliu & Li, Ming & Xia, Qing & Kang, Chongqing, 2017. "A Nash-Cournot approach to assessing flexible ramping products," Applied Energy, Elsevier, vol. 206(C), pages 42-50.
    5. Andoni, Merlinda & Robu, Valentin & Früh, Wolf-Gerrit & Flynn, David, 2017. "Game-theoretic modeling of curtailment rules and network investments with distributed generation," Applied Energy, Elsevier, vol. 201(C), pages 174-187.
    6. Motalleb, Mahdi & Ghorbani, Reza, 2017. "Non-cooperative game-theoretic model of demand response aggregator competition for selling stored energy in storage devices," Applied Energy, Elsevier, vol. 202(C), pages 581-596.
    7. Wang, Lixiao & Jing, Z.X. & Zheng, J.H. & Wu, Q.H. & Wei, Feng, 2018. "Decentralized optimization of coordinated electrical and thermal generations in hierarchical integrated energy systems considering competitive individuals," Energy, Elsevier, vol. 158(C), pages 607-622.
    8. Motalleb, Mahdi & Annaswamy, Anuradha & Ghorbani, Reza, 2018. "A real-time demand response market through a repeated incomplete-information game," Energy, Elsevier, vol. 143(C), pages 424-438.
    9. Dehghani, Hamed & Vahidi, Behrooz & Hosseinian, Seyed Hossein, 2017. "Wind farms participation in electricity markets considering uncertainties," Renewable Energy, Elsevier, vol. 101(C), pages 907-918.
    10. Shi, Kaifang & Chen, Yun & Yu, Bailang & Xu, Tingbao & Chen, Zuoqi & Liu, Rui & Li, Linyi & Wu, Jianping, 2016. "Modeling spatiotemporal CO2 (carbon dioxide) emission dynamics in China from DMSP-OLS nighttime stable light data using panel data analysis," Applied Energy, Elsevier, vol. 168(C), pages 523-533.
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    12. He, Qiao-Chu & Yang, Yun & Bai, Lingquan & Zhang, Baosen, 2020. "Smart energy storage management via information systems design," Energy Economics, Elsevier, vol. 85(C).

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