Online Voltage Regulation With Minimum Disturbance for Distribution Grid Without System Knowledge

作     者：Alduaij, Hamad Weng, Yang 

作者机构：Arizona State Univ Dept Elect Engn Tempe AZ 85281 USA Arizona State Univ Dept Elect Comp & Energy Engn Tempe AZ 85281 USA 

出 版 物：《IEEE OPEN ACCESS JOURNAL OF POWER AND ENERGY》 (IEEE Open Access J. Power Energy)

年 卷 期：2024年第11卷

页      面：520-531页

核心收录：

基　　金：US National Science Foundation 

主　　题：Voltage control Mathematical models Regulators Voltage measurement Load flow Stochastic processes Reinforcement learning Distribution grid distributed energy resources voltage control data driven minimum disturbance optimal control systems kernel methods 

摘      要：Distribution systems have limited observability, as they were a passive grid to consume power. Nowadays, increasing distributed energy resources turns individual customers into generators, and two-way power flow between customers makes the grid prone to power outages. This calls for new control methods with performance guarantees in the presence of limited system information. However, limited system information makes it difficult to employ model-based control, making performance guarantees difficult. To gain information about the model, active learning methods propose to disturb the system consistently to learn the nonlinearity. The exploration process also introduces uncertainty for further outages. To address the issue of frequent perturbation, we propose to disturb the system with decreasing frequency by minimizing exploration. Based on such a proposal, we superposed the design with a physical kernel to embed system non-linearity from power flow equations. These designs lead to a highly robust adaptive online policy, which reduces the perturbation gradually but monotonically based on the optimal control guarantee. For extensive validation, we test our controller on various IEEE test systems, including the 4-bus, 13-bus, 30-bus, and 123-bus grids, with different penetrations of renewables, various set-ups of meters, and diversified regulators. Numerical results show significantly improved voltage control with limited perturbation compared to those of the state-of-the-art data-driven methods.