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Flexibility pricing of integrated unit of electric spring and EVs parking in microgrids

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  • Norouzi, Mohammadali
  • Aghaei, Jamshid
  • Pirouzi, Sasan
  • Niknam, Taher
  • Fotuhi-Firuzabad, Mahmud

Abstract

Electric spring (ES) as a breakthrough in power electronics has led to a revolution in demand-side management. This paper presents flexible power management (FPM) of a networked microgrid (MG) in the presence of renewable energy sources (RESs) and flexibility sources (FSs). The FSs include the novel topology of the integrated unit of ES with electric vehicles (EVs) parking (IUEE) and incentive-based demand response program (DRP). The proposed FPM model is formulated as an optimization problem that minimizes the difference between the expected energy cost and the expected profit of FSs' flexibility subject to the AC optimal power flow (AC-OPF), RESs, FSs, and MG flexibility constraints. In the proposed model, flexibility pricing is performed for both upward and downward flexibility services in which the expected flexibility profit is proportional to the product of the FSs' flexibility and flexibility incentive price (FIP). Further, this paper uses a stochastic programming to model uncertain parameters associated with load demand, energy prices, maximum RES generation capacity, and EVs’ parameters. Finally, the potential of the proposed FPM model in improving the economic, operational and flexibility conditions of the MG is investigated through implementation of the proposed model on the 32-bus radial MG.

Suggested Citation

  • Norouzi, Mohammadali & Aghaei, Jamshid & Pirouzi, Sasan & Niknam, Taher & Fotuhi-Firuzabad, Mahmud, 2022. "Flexibility pricing of integrated unit of electric spring and EVs parking in microgrids," Energy, Elsevier, vol. 239(PB).
    • Handle: RePEc:eee:energy:v:239:y:2022:i:pb:s0360544221023288
    DOI: 10.1016/j.energy.2021.122080
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    References listed on IDEAS

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    7. Khan, Waqas & Somers, Ward & Walker, Shalika & de Bont, Kevin & Van der Velden, Joep & Zeiler, Wim, 2023. "Comparison of electric vehicle load forecasting across different spatial levels with incorporated uncertainty estimation," Energy, Elsevier, vol. 283(C).
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    9. Artis, Reza & Shivaie, Mojtaba & Weinsier, Philip D., 2024. "A flexible urban load density-dependent framework for low-carbon distribution expansion planning in the presence of hybrid hydrogen/battery/wind/solar energy systems," Applied Energy, Elsevier, vol. 364(C).
    10. Zhang, Kaizhe & Xu, Yinliang & Sun, Hongbin, 2024. "Bilevel optimal coordination of active distribution network and charging stations considering EV drivers' willingness," Applied Energy, Elsevier, vol. 360(C).
    11. Bu, Yuntao & Yu, Hao & Ji, Haoran & Song, Guanyu & Xu, Jing & Li, Juan & Zhao, Jinli & Li, Peng, 2024. "Hybrid data-driven operation method for demand response of community integrated energy systems utilizing virtual and physical energy storage," Applied Energy, Elsevier, vol. 366(C).
    12. Pan, Yushu & Ju, Liwei & Yang, Shenbo & Guo, Xinyu & Tan, Zhongfu, 2024. "A multi-objective robust optimal dispatch and cost allocation model for microgrids-shared hybrid energy storage system considering flexible ramping capacity," Applied Energy, Elsevier, vol. 369(C).
    13. Al-Quraan, A. & Al-Mhairat, B., 2024. "Economic predictive control-based sizing and energy management for grid-connected hybrid renewable energy systems," Energy, Elsevier, vol. 302(C).

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