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Joint active and reactive for allocation of renewable energy and energy storage under uncertain coupling

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  • Jiao, P.H.
  • Chen, J.J.
  • Cai, X.
  • Wang, L.L.
  • Zhao, Y.L.
  • Zhang, X.H.
  • Chen, W.G.

Abstract

Growing energy storage systems for intermittent renewable energy to maintain the power balance has expanded the investment cost in distribution network planning. Existing works on the energy storage system and intermittent renewable energy allocation, however, do not adequately consider the joint operation of active and reactive power under uncertain coupling, leading to a lack of economic efficiency in the investment decision. Regarding this, a techno-economic framework is urgently needed to take the responsibility of accommodating intermittent renewable energy. To do so, a joint active and reactive operation strategy is developed to fully harness the potential flexibility existed in intermittent renewable energy and energy storage system, and to determine their optimal allocation under uncertain coupling. In the proposed strategy, the state of energy is simulated via the Fourier-Legendre series to capture the charging/discharging characteristic of the energy storage system. The expected reserve and expected curtailment to address the risk caused by uncertainties are respectively modeled by a joint probability-based value of loss load and value of power curtailment. To tackle the net load fluctuation imposed by intermittent renewable energy, a price-based active and reactive integrated demand response is established. Case studies prove the feasibility and effectiveness of the proposed model in reducing annual cost, flattening net load curve as well as improving voltage quality for stochastic distribution network planning.

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  • Jiao, P.H. & Chen, J.J. & Cai, X. & Wang, L.L. & Zhao, Y.L. & Zhang, X.H. & Chen, W.G., 2021. "Joint active and reactive for allocation of renewable energy and energy storage under uncertain coupling," Applied Energy, Elsevier, vol. 302(C).
    • Handle: RePEc:eee:appene:v:302:y:2021:i:c:s0306261921009582
    DOI: 10.1016/j.apenergy.2021.117582
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    2. Wu, Yunyun & Fang, Jiakun & Ai, Xiaomeng & Xue, Xizhen & Cui, Shichang & Chen, Xia & Wen, Jinyu, 2023. "Robust co-planning of AC/DC transmission network and energy storage considering uncertainty of renewable energy," Applied Energy, Elsevier, vol. 339(C).
    3. Li, Hongze & Li, Xumeng & Zhang, Yuanyuan & Zhao, Yihang & Pan, Jiaqi & Zhao, Huiru, 2024. "Declaration strategy of wind power and pumped storage participating in the power market considering multiple uncertainties," Energy, Elsevier, vol. 293(C).
    4. Li, J.Y. & Chen, J.J. & Wang, Y.X. & Chen, W.G., 2024. "Combining multi-step reconfiguration with many-objective reduction as iterative bi-level scheduling for stochastic distribution network," Energy, Elsevier, vol. 290(C).
    5. Jiao, P.H. & Chen, J.J. & Cai, X. & Zhao, Y.L., 2024. "Fuzzy semi-entropy based downside risk to low-carbon oriented multi-energy dispatch considering multiple dependent uncertainties," Energy, Elsevier, vol. 287(C).

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