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LI Ruijie, CUI Shichang, ZHANG Yihan, XUE Xizhen, GAO Liqian, Al Xiaomeng, FANG Jiakun, WEN Jinyu. Real-time Cooperative Voltage Regulation Strategy of Distribution Network Based on Approximate Dynamic Programming[J]. Power System Technology, 2025, 49(2): 676-685. DOI: 10.13335/j.1000-3673.pst.2023.1996
Citation: LI Ruijie, CUI Shichang, ZHANG Yihan, XUE Xizhen, GAO Liqian, Al Xiaomeng, FANG Jiakun, WEN Jinyu. Real-time Cooperative Voltage Regulation Strategy of Distribution Network Based on Approximate Dynamic Programming[J]. Power System Technology, 2025, 49(2): 676-685. DOI: 10.13335/j.1000-3673.pst.2023.1996

Real-time Cooperative Voltage Regulation Strategy of Distribution Network Based on Approximate Dynamic Programming

  • Large-scale distributed generation with output uncertainty can lead to problems such as voltage over-limit and line overload. Meanwhile, the rapid expansion of electric vehicles also causes the power load of the distribution network to surge. Multiple factors lead to the voltage stability problem of the distribution network. Therefore, guaranteeing the real-time stability of distribution network voltage under an uncertain operating environment is an urgent problem that needs to be solved. In this paper, from the perspective of reducing the voltage offset, we consider using the on-load tap changer in the distribution network and electric vehicles for cooperative voltage regulation. Firstly, the characteristics of electric vehicle cluster scheduling are analyzed. With the minimum system voltage offset as the voltage optimization objective of the distribution network, the regulation model considers electric vehicle charging position, power, and other factors, and the multi-stall on-load tap changer regulation model is established. Subsequently, to realize real-time optimization and regulation of distribution network voltage under a stochastic environment, a real-time cooperative voltage regulation strategy between an on-load tap changer and electric vehicle based on approximate dynamic planning is proposed, and the segmented linear function is used to approximate the value function of Bellman equation, which avoids the problem of "dimensional explosion". The slopes of the segmented linear functions are obtained from a set of offline training scenarios generated by sampling the predicted data and are used for subsequent real-time online optimization. Example analysis shows that the proposed real-time cooperative voltage regulation strategy reduces the voltage offset of the distribution network while ensuring the optimization accuracy in the stochastic environment, which further validates the feasibility of the cooperative voltage regulation technology involving electric vehicles and on-load tap changers in the distribution network.
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