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A robust model for aggregated bidding of energy storages and wind resources in the joint energy and reserve markets

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  • Khojasteh, Meysam
  • Faria, Pedro
  • Vale, Zita

Abstract

The high reliability and flexibility of Battery Energy Storage (BES) resources in comparison with other renewable technologies promote the development of this technology in smart grids. The fast response of BES to load variations could help the power system operators to maintain the balance of generation and consumption in real-time, and improve the flexibility of the smart grid, effectively. In this work, a new model is presented that determines the aggregated scheduling of BES and Wind Power Resource (WPR) in the joint energy and reserve markets. To evaluate the performance of BES in different markets, the proposed model is divided into day-ahead and real-time planning horizons. According to market prices, ramp rates, marginal costs, and technical constraints of units, the optimal participation levels in different markets are determined. The deployed power in real-time and wind power are considered as the uncertain parameters and the Robust Optimization (RO) framework is proposed to manage the related financial risk based on the worst-case realizations of uncertain parameters. The robust strategy is formulated based on the Mixed Integer Linear Programming (MILP) technique, which can be solved via the branch-and-bound method. Finally, the performance and effectiveness of the model are analyzed via different case studies. Simulation results show that the day-ahead and real-time markets are the best options for buying and selling the energy of BESs, and participation in the reserve market and regulation service increases their profit, significantly. Furthermore, the expected profit greatly depends on the risk preferences of decision-makers, and reducing the variation interval of wind generation by 40 % leads to an increase of 74.65 % in revenues.

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  • Khojasteh, Meysam & Faria, Pedro & Vale, Zita, 2022. "A robust model for aggregated bidding of energy storages and wind resources in the joint energy and reserve markets," Energy, Elsevier, vol. 238(PB).
    • Handle: RePEc:eee:energy:v:238:y:2022:i:pb:s0360544221019836
    DOI: 10.1016/j.energy.2021.121735
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    1. Gomes, I.L.R. & Pousinho, H.M.I. & Melício, R. & Mendes, V.M.F., 2017. "Stochastic coordination of joint wind and photovoltaic systems with energy storage in day-ahead market," Energy, Elsevier, vol. 124(C), pages 310-320.
    2. Pandžić, H. & Dvorkin, Y. & Carrión, M., 2018. "Investments in merchant energy storage: Trading-off between energy and reserve markets," Applied Energy, Elsevier, vol. 230(C), pages 277-286.
    3. Aliasghari, Parinaz & Zamani-Gargari, Milad & Mohammadi-Ivatloo, Behnam, 2018. "Look-ahead risk-constrained scheduling of wind power integrated system with compressed air energy storage (CAES) plant," Energy, Elsevier, vol. 160(C), pages 668-677.
    4. Khojasteh, Meysam & Jadid, Shahram, 2015. "Decision-making framework for supplying electricity from distributed generation-owning retailers to price-sensitive customers," Utilities Policy, Elsevier, vol. 37(C), pages 1-12.
    5. Fernando Lezama & Ricardo Faia & Pedro Faria & Zita Vale, 2020. "Demand Response of Residential Houses Equipped with PV-Battery Systems: An Application Study Using Evolutionary Algorithms," Energies, MDPI, vol. 13(10), pages 1-18, May.
    6. Berrada, Asmae & Loudiyi, Khalid & Zorkani, Izeddine, 2016. "Valuation of energy storage in energy and regulation markets," Energy, Elsevier, vol. 115(P1), pages 1109-1118.
    7. 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).
    8. Qin, Zhijun & Mo, Yuhong & Liu, Hui & Zhang, Yihui, 2021. "Operational flexibility enhancements using mobile energy storage in day-ahead electricity market by game-theoretic approach," Energy, Elsevier, vol. 232(C).
    9. Díaz-González, Francisco & Sumper, Andreas & Gomis-Bellmunt, Oriol & Villafáfila-Robles, Roberto, 2012. "A review of energy storage technologies for wind power applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(4), pages 2154-2171.
    10. Stougie, Lydia & Del Santo, Giulia & Innocenti, Giulia & Goosen, Emil & Vermaas, David & van der Kooi, Hedzer & Lombardi, Lidia, 2019. "Multi-dimensional life cycle assessment of decentralised energy storage systems," Energy, Elsevier, vol. 182(C), pages 535-543.
    11. Ricardo Faia & Pedro Faria & Zita Vale & João Spinola, 2019. "Demand Response Optimization Using Particle Swarm Algorithm Considering Optimum Battery Energy Storage Schedule in a Residential House," Energies, MDPI, vol. 12(9), pages 1-18, April.
    12. Sousa, Tiago & Vale, Zita & Carvalho, Joao Paulo & Pinto, Tiago & Morais, Hugo, 2014. "A hybrid simulated annealing approach to handle energy resource management considering an intensive use of electric vehicles," Energy, Elsevier, vol. 67(C), pages 81-96.
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    6. Khojasteh, Meysam & Faria, Pedro & Lezama, Fernando & Vale, Zita, 2023. "A novel adaptive robust model for scheduling distributed energy resources in local electricity and flexibility markets," Applied Energy, Elsevier, vol. 342(C).
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    8. Zhang, Rufeng & Sun, Haihang & Li, Guoqing & Jiang, Tao & Li, Xue & Chen, Houhe & Zou, He, 2023. "Reserve provision of combined-cycle unit in joint day-ahead energy and reserve markets," Applied Energy, Elsevier, vol. 336(C).
    9. Meysam Khojasteh & Pedro Faria & Fernando Lezama & Zita Vale, 2023. "A Robust Model for Portfolio Management of Microgrid Operator in the Balancing Market," Energies, MDPI, vol. 16(4), pages 1-12, February.
    10. Sai, Wei & Pan, Zehua & Liu, Siyu & Jiao, Zhenjun & Zhong, Zheng & Miao, Bin & Chan, Siew Hwa, 2023. "Event-driven forecasting of wholesale electricity price and frequency regulation price using machine learning algorithms," Applied Energy, Elsevier, vol. 352(C).
    11. Sohani, Ali & Cornaro, Cristina & Shahverdian, Mohammad Hassan & Moser, David & Pierro, Marco & Olabi, Abdul Ghani & Karimi, Nader & Nižetić, Sandro & Li, Larry K.B. & Doranehgard, Mohammad Hossein, 2023. "Techno-economic evaluation of a hybrid photovoltaic system with hot/cold water storage for poly-generation in a residential building," Applied Energy, Elsevier, vol. 331(C).
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    13. Khojasteh, Meysam & Faria, Pedro & Lezama, Fernando & Vale, Zita, 2022. "Optimal strategy of electricity and natural gas aggregators in the energy and balance markets," Energy, Elsevier, vol. 257(C).
    14. Zhihan Shi & Guangming Zhang & Xiaoxiong Zhou & Weisong Han & Mingxiang Zhu & Zhiqing Bai & Xiaodong Lv, 2023. "Research on Integrated Energy Distributed Sharing in Distribution Network Considering AC Power Flow and Demand Response," Sustainability, MDPI, vol. 15(22), pages 1-23, November.
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