电测与仪表2026，Vol.63Issue(4)：82-88,7.DOI:10.19753/j.issn1001-1390.2026.04.009
基于改进卷积神经网络的配电网线损率估计方法研究
Research on distribution network line loss rate estimation method based on improved convolutional neural network
摘要
Abstract
The proposal of the dual carbon target has made reducing losses and energy conservation a key focus of modern power grid construction.A distribution network line loss estimation method combining convolutional neural networks and improved particle swarm optimization algorithm is proposed to address the problems of low estimation accuracy and poor operational efficiency in existing methods.By improving the particle swarm optimization algo-rithm to balance individual and global optimal,the optimal weights and thresholds of the network are obtained,which improves the convergence speed and estimation accuracy of convolutional neural network.The feasibility of the proposed line loss rate estimation method is verified through simulation.The results indicate that,compared with conventional methods,the proposed method has higher estimation accuracy and faster operational efficiency,which can provide certain assistance for achieving the dual carbon target.关键词
配电网/线损率/估计方法/卷积神经网络/粒子群算法Key words
distribution network/line loss rate/estimation method/convolution neural network/particle swarm op-timization algorithm分类
信息技术与安全科学引用本文复制引用
谢乔富,尹学祥,许思伟..基于改进卷积神经网络的配电网线损率估计方法研究[J].电测与仪表,2026,63(4):82-88,7.基金项目
国家重点研发计划项目(2022YFB2703500) （2022YFB2703500）
中国南方电网有限责任公司重点科技项目(YNKJXM20220010) （YNKJXM20220010）
中国南方电网有限责任公司重点科技项目(YNKJXM20222387) （YNKJXM20222387）
