兵工自动化2025，Vol.44Issue(3)：25-28,4.DOI:10.7690/bgzdh.2025.03.006
一种电力用户用电特征数据挖掘方法
Power Consumption Characteristic Data Mining Method for Power User
李雄 1吴方权 1汤成佳1
作者信息
- 1. 贵州电网有限责任公司信息中心,贵阳 550003
- 折叠
摘要
Abstract
In order to solve the problem of lack of analysis and prediction of user's response behavior under different environments and incentive signals in the current power demand response analysis,a data mining method based on power user's power consumption behavior is proposed.Construct and analyze the incentive-based demand response architecture,establish a user response flexibility model based on the existing abstract formula of user response cost,and propose a double-layer longshort-term memory network to identify user response behavior model;The proposed model is compared with random forest(RF),support vector machines(SVM),recurrent neural network(RNN)and long short-term memory(LSTM).The results show that the proposed model has excellent performance,the accuracy rate is 94.83%,the F1 score is 95.45%,and the quality factor is 39.42%,which can provide a reference for the development of safe operation and management of electric power.关键词
电力系统/需求响应/深度学习/长短时记忆/行为识别Key words
power system/demand response/deep learning/long short-term memory/behavior recognition引用本文复制引用
李雄,吴方权,汤成佳..一种电力用户用电特征数据挖掘方法[J].兵工自动化,2025,44(3):25-28,4.
