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An effective stochastic framework for smart coordinated operation of wind park and energy storage unit

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  • Mohamed, Mohamed A.
  • Jin, Tao
  • Su, Wencong

Abstract

This paper proposes a stochastic transmission switching integrated interval robust chance-constrained (TSIRC) approach to assess the operation of a wind park-energy storage system (WPES) in a day ahead electricity market considering the system technical constraints. To this end, the WPES is assumed as a price-maker, making it possible to alter the market price based on its own profit. The problem formulation is constructed as a tri-level max-min-max structure during a 24-h time horizon. The first level maximizes the hourly profit of the WPES. In the second level, the system operation cost is minimized in the form of a security constrained unit commitment (SCUC) in which the contingency effect associated with the generation units and transmission lines (TLs) as well as the congestion of the TLs is modelled. Considering the independent system operator (ISO) preferences, the third level is dedicated to the robustness of the WPES, which would maximize the allowable output variation of the wind turbines. The proposed tri-level model is then formulated in an efficient bi-level structure using the Karush-Kuhn-Tacker (KKT) conditions. Since the operation of the wind turbine is inherently associated with uncertainty, the TSIRC approach as an effective tool is able to model the uncertainties of the wind units by increasing the WPES profit as a strategic producer while reducing the system operation cost. In addition, unscented transform (UT) as an effective tool is considered to model the uncertainty of the stochastic parameters. The performance evaluation of this work is assessed on an IEEE test system. Different case studies are provided which show the authenticity and effectiveness of the proposed model. The simulation results show that the proposed TSIRC has effectively reduced the amount of lines’ switching, and increased the power output of the wind park by 95% on average compared to the conventional TS-based model. In addition, the robustness of the system has increased, and the TSIRC has led the WPES’s profit to increase by almost 11.5% compared to the TS-based approach.

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  • Mohamed, Mohamed A. & Jin, Tao & Su, Wencong, 2020. "An effective stochastic framework for smart coordinated operation of wind park and energy storage unit," Applied Energy, Elsevier, vol. 272(C).
    • Handle: RePEc:eee:appene:v:272:y:2020:i:c:s0306261920307406
    DOI: 10.1016/j.apenergy.2020.115228
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    5. Mohamed, Mohamed A., 2022. "A relaxed consensus plus innovation based effective negotiation approach for energy cooperation between smart grid and microgrid," Energy, Elsevier, vol. 252(C).
    6. Mohamed, Mohamed A. & Jin, Tao & Su, Wencong, 2020. "Multi-agent energy management of smart islands using primal-dual method of multipliers," Energy, Elsevier, vol. 208(C).
    7. Tomasz Wołowiec & Iuliia Myroshnychenko & Ihor Vakulenko & Sylwester Bogacki & Anna Maria Wiśniewska & Svitlana Kolosok & Vitaliy Yunger, 2022. "International Impact of COVID-19 on Energy Economics and Environmental Pollution: A Scoping Review," Energies, MDPI, vol. 15(22), pages 1-26, November.
    8. Chabok, Hossein & Aghaei, Jamshid & Sheikh, Morteza & Roustaei, Mahmoud & Zare, Mohsen & Niknam, Taher & Lehtonen, Matti & Shafi-khah, Miadreza & Catalão, João P.S., 2022. "Transmission-constrained optimal allocation of price-maker wind-storage units in electricity markets," Applied Energy, Elsevier, vol. 310(C).
    9. Rujie Zhu & Kaushik Das & Poul Ejnar Sørensen & Anca Daniela Hansen, 2023. "Optimal Participation of Co-Located Wind–Battery Plants in Sequential Electricity Markets," Energies, MDPI, vol. 16(15), pages 1-17, July.
    10. Fahd A. Alturki & Emad Mahrous Awwad, 2021. "Sizing and Cost Minimization of Standalone Hybrid WT/PV/Biomass/Pump-Hydro Storage-Based Energy Systems," Energies, MDPI, vol. 14(2), pages 1-20, January.
    11. Tan, Hong & Li, Zhenxing & Wang, Qiujie & Mohamed, Mohamed A., 2023. "A novel forecast scenario-based robust energy management method for integrated rural energy systems with greenhouses," Applied Energy, Elsevier, vol. 330(PB).

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