In order to solve the problem that the traditional fault diagnosis method for distribution network in low-voltage station area has limited application range and complex model,this paper proposes a fault diagnosis model based on computational intel-ligence.An improved multi-objective evolutionary algorithm is designed to solve the multi-objective fault diagnosis model based on the real-time PMU data,and the fault content is reported to the intelligent control center.In the experimental stage,a pow-er system connection model in a fault zone is taken as an example to validate the proposed model.Simulation results show that the proposed model can effectively overcome the effects of single or multiple protective relay faults,and thus efficiently identify fault components.At the same time,the average accuracy of the proposed model is 0.9171 by cross-comparison analysis.The simulation results further verify the robustness and stability of the proposed model.
关键词
电力系统/低压台区/故障诊断/优化模型/多目标进化算法
Key words
power system/low-voltage station area/fault diagnosis/optimization model/multi-objective evolutionary algorithm
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