计量学报2024，Vol.45Issue(2)：253-260,8.DOI:10.3969/j.issn.1000-1158.2024.02.16
基于BA-MKELM的微电网故障识别与定位
Microgrid Fault Identification and Location Based on BA-MKELM
摘要
Abstract
A microgrid fault identification and location method based on Bayesian algorithm optimizing multi-kernel extreme learning machine is proposed.Aiming at the problem of insufficient regression ability caused by the random selection of input parameters and hidden layer nodes of extreme learning machine,the kernel function is introduced,and the polynomial and the Gaussian radial basis kernel function are combined to form a multi-kernel extreme learning machine to establish a fault identification and location model.The Bayesian algorithm is used to optimize the relevant parameters of the multi-kernel extreme learning machine to further improve the approximation ability of the model.In order to verify the fault identification and location performance of the proposed model,extreme learning machine and multi-kernel extreme learning machine are selected to establish fault diagnosis models respectively for comparative analysis.Experimental results show that the proposed method can identify and locate any type of faults in the microgrid with high performance,and has higher recognition and location accuracy.关键词
电学计量/微电网线路/故障识别和定位/贝叶斯算法/多核极限学习机/小波包分解Key words
electrical measurement/microgrid line/fault identification and location/bayesian algorithm/multi-kernel extreme learning machine/wavelet packet decomposition分类
通用工业技术引用本文复制引用
吴忠强,卢雪琴..基于BA-MKELM的微电网故障识别与定位[J].计量学报,2024,45(2):253-260,8.基金项目
河北省自然科学基金(F2020203014) （F2020203014）
