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Risk Assessment with Generic Energy Storage under Exogenous and Endogenous Uncertainty

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  • Ning Qi
  • Lin Cheng
  • Yuxiang Wan
  • Yingrui Zhuang
  • Zeyu Liu

Abstract

Current risk assessment ignores the stochastic nature of energy storage availability itself and thus lead to potential risk during operation. This paper proposes the redefinition of generic energy storage (GES) that is allowed to offer probabilistic reserve. A data-driven unified model with exogenous and endogenous uncertainty (EXU & EDU) description is presented for four typical types of GES. Moreover, risk indices are proposed to assess the impact of overlooking (EXU & EDU) of GES. Comparative results between EXU & EDU are illustrated in distribution system with day-ahead chance-constrained optimization (CCO) and more severe risks are observed for the latter, which indicate that system operator (SO) should adopt novel strategies for EDU uncertainty.

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  • Ning Qi & Lin Cheng & Yuxiang Wan & Yingrui Zhuang & Zeyu Liu, 2022. "Risk Assessment with Generic Energy Storage under Exogenous and Endogenous Uncertainty," Papers 2203.13991, arXiv.org.
    • Handle: RePEc:arx:papers:2203.13991
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    References listed on IDEAS

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    1. Qi, Ning & Cheng, Lin & Xu, Helin & Wu, Kuihua & Li, XuLiang & Wang, Yanshuo & Liu, Rui, 2020. "Smart meter data-driven evaluation of operational demand response potential of residential air conditioning loads," Applied Energy, Elsevier, vol. 279(C).
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