Multi-Time Scale Reactive Power Optimization of Distribution Grid Based on Model Predictive Control and Including RDG Regulation
Yan Xiangwu1, Xu Yun1, Li Ruojin1, Jin Yongsheng1, Li Tie2
1. Key Laboratory of Distributed Energy Storage and Microgrid of Hebei Province North China Electric Power University Baoding 071003 China 2. State Grid Liaoning Electric Power Supply Co. Ltd Shenyang 110006 China
Abstract：Fully digging the dynamic reactive power and voltage regulation capability of renewable distributed generation (RDG) is of great significance for improving the voltage stability problem caused by randomness of RDG outputs and load fluctuations in the distribution system. A multi-time scale reactive power optimization model for distribution network based on model predictive control is established, which includes a day-ahead optimal regulation layer and a real-time rolling control layer. The day-ahead optimal regulation focuses on the economics of operation. Large-scale reactive power regulation is performed through the coordination and cooperation of various reactive power devices, and sufficient dynamic reactive power reserve is retained to response dynamic regulations and reduce operational risk. The real-time rolling control focuses on the stability of the system operation and is implemented based on the ultra-short-term forecast of RDG and load. According to the demand of reactive power compensation, correction of decision-making feedback is implemented timely. Then, “substantial adjustment”, “small-scale regulation” and “feedback adjustment” of reactive voltage of distribution network is realized through layer-by-layer refinement to suppress voltage over-limit caused by uncertain factors. Finally, the simulation results of IEEE33-bus examples are analyzed. The results show that the model and algorithm proposed in this paper can effectively reduce the influence of prediction errors and improve the system voltage stability and power quality.
颜湘武, 徐韵, 李若瑾, 金永盛, 李铁. 基于模型预测控制含可再生分布式电源参与调控的配电网多时间尺度无功动态优化[J]. 电工技术学报, 2019, 34(10): 2022-2037.
Yan Xiangwu, Xu Yun, Li Ruojin, Jin Yongsheng, Li Tie. Multi-Time Scale Reactive Power Optimization of Distribution Grid Based on Model Predictive Control and Including RDG Regulation. Transactions of China Electrotechnical Society, 2019, 34(10): 2022-2037.
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