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Optimal bidding and offering strategies of merchant compressed air energy storage in deregulated electricity market using robust optimization approach

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  • Nojavan, Sayyad
  • Najafi-Ghalelou, Afshin
  • Majidi, Majid
  • Zare, Kazem

Abstract

Nowadays, severe uncertainty of electricity market price is a challenge issue in power systems that market players are faced. As one of market players, merchant compressed air energy storage system can be studied to investigate how energy is purchased/sold in the presence of electricity market price uncertainty. Therefore, this paper proposes, robust optimization approach is employed to achieve the offering and bidding curves of compressed air energy storage which should be submitted to the pool market. In the proposed method, the minimum and maximum amounts of electricity market prices are considered instead of the forecasted prices which allows formulating a collection of robust mixed-integer linear programming problem problems. The offering and bidding curves of compressed air energy storage are obtained based on sufficient data from results of these problems to be offered to the market operator. A case study is used to show the performance of proposed method.

Suggested Citation

  • Nojavan, Sayyad & Najafi-Ghalelou, Afshin & Majidi, Majid & Zare, Kazem, 2018. "Optimal bidding and offering strategies of merchant compressed air energy storage in deregulated electricity market using robust optimization approach," Energy, Elsevier, vol. 142(C), pages 250-257.
    • Handle: RePEc:eee:energy:v:142:y:2018:i:c:p:250-257
    DOI: 10.1016/j.energy.2017.10.028
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    8. Bartosz Uniejewski, 2023. "Electricity price forecasting with Smoothing Quantile Regression Averaging: Quantifying economic benefits of probabilistic forecasts," Papers 2302.00411, arXiv.org, revised Jan 2024.
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    11. Bazdar, Elaheh & Sameti, Mohammad & Nasiri, Fuzhan & Haghighat, Fariborz, 2022. "Compressed air energy storage in integrated energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    12. Cai, Wei & Mohammaditab, Rasoul & Fathi, Gholamreza & Wakil, Karzan & Ebadi, Abdol Ghaffar & Ghadimi, Noradin, 2019. "Optimal bidding and offering strategies of compressed air energy storage: A hybrid robust-stochastic approach," Renewable Energy, Elsevier, vol. 143(C), pages 1-8.
    13. Akbari, Ebrahim & Hooshmand, Rahmat-Allah & Gholipour, Mehdi & Parastegari, Moein, 2019. "Stochastic programming-based optimal bidding of compressed air energy storage with wind and thermal generation units in energy and reserve markets," Energy, Elsevier, vol. 171(C), pages 535-546.
    14. Zhong, Zhiming & Fan, Neng & Wu, Lei, 2023. "A hybrid robust-stochastic optimization approach for day-ahead scheduling of cascaded hydroelectric system in restructured electricity market," European Journal of Operational Research, Elsevier, vol. 306(2), pages 909-926.
    15. Lak, Omidreza & Rastegar, Mohammad & Mohammadi, Mohammad & Shafiee, Soroush & Zareipour, Hamidreza, 2021. "Risk-constrained stochastic market operation strategies for wind power producers and energy storage systems," Energy, Elsevier, vol. 215(PB).
    16. Guo, Hongye & Chen, Qixin & Shahidehpour, Mohammad & Xia, Qing & Kang, Chongqing, 2022. "Bidding behaviors of GENCOs under bounded rationality with renewable energy," Energy, Elsevier, vol. 250(C).
    17. Mirzaei, Mohammad Amin & Sadeghi-Yazdankhah, Ahmad & Mohammadi-Ivatloo, Behnam & Marzband, Mousa & Shafie-khah, Miadreza & Catalão, João P.S., 2019. "Integration of emerging resources in IGDT-based robust scheduling of combined power and natural gas systems considering flexible ramping products," Energy, Elsevier, vol. 189(C).
    18. Ak{i}n Tac{s}cikaraou{g}lu & Ozan Erdinc{c}, 2018. "A Profit Optimization Approach Based on the Use of Pumped-Hydro Energy Storage Unit and Dynamic Pricing," Papers 1806.05211, arXiv.org.
    19. Guo, Hongye & Chen, Qixin & Zhang, Yan & Liu, Kai & Xia, Qing & Kang, Chongqing, 2020. "Constraining the oligopoly manipulation in electricity market: A vertical integration perspective," Energy, Elsevier, vol. 194(C).
    20. Li-Peng Shao & Jia-Jia Chen & Lu-Wen Pan & Zi-Juan Yang, 2022. "A Credibility Theory-Based Robust Optimization Model to Hedge Price Uncertainty of DSO with Multiple Transactions," Mathematics, MDPI, vol. 10(23), pages 1-20, November.
    21. Xiao, Xiangsheng & Wang, Jianxiao & Lin, Rui & Hill, David J. & Kang, Chongqing, 2020. "Large-scale aggregation of prosumers toward strategic bidding in joint energy and regulation markets," Applied Energy, Elsevier, vol. 271(C).
    22. Nouri, Alireza & Khodaei, Hossein & Darvishan, Ayda & Sharifian, Seyedmehdi & Ghadimi, Noradin, 2018. "Optimal performance of fuel cell-CHP-battery based micro-grid under real-time energy management: An epsilon constraint method and fuzzy satisfying approach," Energy, Elsevier, vol. 159(C), pages 121-133.
    23. Liu, Youbo & Zuo, Kunyu & Liu, Xueqin (Amy) & Liu, Junyong & Kennedy, Jason M., 2018. "Dynamic pricing for decentralized energy trading in micro-grids," Applied Energy, Elsevier, vol. 228(C), pages 689-699.
    24. Ostadi, Bakhtiar & Motamedi Sedeh, Omid & Husseinzadeh Kashan, Ali, 2020. "Risk-based optimal bidding patterns in the deregulated power market using extended Markowitz model," Energy, Elsevier, vol. 191(C).
    25. Khaloie, Hooman & Abdollahi, Amir & Shafie-khah, Miadreza & Anvari-Moghaddam, Amjad & Nojavan, Sayyad & Siano, Pierluigi & Catalão, João P.S., 2020. "Coordinated wind-thermal-energy storage offering strategy in energy and spinning reserve markets using a multi-stage model," Applied Energy, Elsevier, vol. 259(C).

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