4.7 Article

Risk-Averse Storage Planning for Improving RES Hosting Capacity Under Uncertain Siting Choices

期刊

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
卷 12, 期 4, 页码 1984-1995

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2021.3075615

关键词

Capacity planning; Stochastic processes; Renewable energy sources; Energy storage; Distribution networks; Reactive power; Risk-averse planning; energy storage; renewable energy hosting capacity; trilevel stochastic program; column-and-constraint generation

资金

  1. National Natural Science Foundation of China [61803297, 61773308, U1766205]
  2. China Postdoctoral Science Foundation [2019M663722]
  3. Fundamental Research Funds for the Central Universities [xpt012020010, xxj022019033, TSTE01308-2020]

向作者/读者索取更多资源

This study introduces a novel three-level risk-averse strategy for configuring grid-scale energy storage systems, and develops a formulation that includes a scenario-based stochastic program model to handle the random fluctuations in renewable energy outputs.
This paper presents a trilevel risk-averse strategy to configure the grid-scale energy storage systems (ESS) in active distribution network. Unlike the traditional planning framework, which presumes that ESS and renewable energy sources (RES) are cooperatively planned, we consider a practical situation that the siting choice of individual RES owners could be conflict with systems operation target of hosting capacity improvement. To address this challenge, a trilevel ESS planning formulation with min-max risk constraint is developed. Also, a scenario-based stochastic program model is incorporated in the lower level problem to handle the random fluctuation of RES outputs. As the resulting risk-constrained trilevel formulation is computationally difficult, we develop a customized column-and-constraint generation algorithm with finite convergence. Numerical studies on 33-bus test system and a real-world 56-bus distribution network indicate that the proposed methodology can effectively enhance the robustness of look-ahead ESS configuration against those non-cooperative and uncertain integration choices for renewable energy construction. Moreover, our customized algorithm demonstrates a superior solution capacity and scalability to support the efficient decisions for risk-averse storage planning.

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