Ye Zhang, Qianpeng Hao, Qi Guo, Shun Yao, Yifan Zhang, Qiang Li
Multiple devices; State awareness; Transmission section limit; Automatic search; SVM optimization algorithm; Whale optimization algorithm
Considering the variability of dynamic factors such as load fluctu- ations and power generation output in the power system, and the increased complexity of searching for transmission line limits. This study proposes a support vector machine (SVM) optimization al- gorithm based on multi device state perception technology for au- tomatic search of the maximum power of transmission sections in power systems. Firstly, the topology structure of the power system is constructed using graph theory methods. Multiple device state data are collected through PMU devices, and the power composition matrix of the transmission line is solved using power flow tracking method as the input sample for SVM. The Whale Optimization Algo- rithm (WOA) is used to optimize the SVM parameters. To evaluate the transmission line power data based on the transmission line limit type, and achieve automatic search for transmission line limits. The experimental results show that the algorithm has a minimum search error of 0.1% in the IEEE 14 node system, and can accurately identify the maximum power of the section without manual review, achiev- ing precise early warning of abnormal periods in temporary power trading scenarios.
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