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A Disturbance Localization Method for Power System Based on Group Sparse Representation and Entropy Weight Method

Energy Engineering 2024年第8期121卷 2275-2291页

作者： Zeyi Wang Mingxi Jiao Daliang Wang Minxu Liu Minglei Jiang He Wang Shiqiang Li Changchun Power Supply Company State Grid Jilin Electric Power Co.Ltd.Changchun130021China Economic and Technical Research Institute State Grid Jilin Electric Power Co.Ltd.Changchun130022China Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Northeast Electric Power UniversityJilin132012China

This paper addresses the problem of complex and challenging disturbance localization in the current power system operation environment by proposing a disturbance localization method for power systems based on group sparse representation and entropy weight *** different electrical quantities are selected as observations in the compressed sensing *** entropy weighting method is employed to calculate the weights of different observations based on their relative disturbance ***,by leveraging the topological information of the power system and pre-designing an overcomplete dictionary of disturbances based on the corresponding system parameter variations caused by disturbances,an improved Joint Generalized Orthogonal Matching Pursuit(J-gomp)algorithm is utilized for *** reconstructed sparse vectors are divided into three *** at least two parts have consistent node identifiers,the node is identified as the disturbance *** the node identifiers in all three parts are inconsistent,further analysis is conducted considering the weights to determine the disturbance *** results based on the IEEE 39-bus system model demonstrate that the proposed method,utilizing electrical quantity information from only 8 measurement points,effectively locates disturbance positions and is applicable to various disturbance types with strong noise resistance.

关键词： Disturbance location compressed sensing group sparse representation entropy power method gomp algorithm

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