电力需求侧管理2025，Vol.27Issue(2)：55-61,7.DOI:10.3969/j.issn.1009-1831.2025.02.009
基于负荷分解与辨识的短期电力负荷预测
Short-term power load forecasting based on load decomposition and identification
摘要
Abstract
In order to further reduce the forecasting error of electric load data,a short-term power load forecasting method based on load de-composition and identification is proposed.First,for the electric power load data of each industry,the polynomial fitting error of tempera-ture-sensitive load to the temperature series is taken as the objective function,and the load decomposition is transformed into a mathemati-cal optimization problem,and the total load of each industry is decomposed into the weekly load based on load identification component and the temperature-sensitive load component.Second,the short-term load prediction is performed for the temperature-sensitive load compo-nent based on the long short-term memory network.Finally,the temperature-sensitive load prediction results are superimposed with the weekly load based on load identification component to obtain the complete load forecast results.The results show that the short-term load forecasting method based on load decomposition and identification proposed can effectively reduce the short-term load forecasting error.关键词
负荷预测/负荷分解/负荷辨识/长短时记忆网络Key words
load forecasting/load decomposition/load identification/LSTM network分类
动力与电气工程引用本文复制引用
朱俊澎,李子钰,李虎军,邓振立,袁越..基于负荷分解与辨识的短期电力负荷预测[J].电力需求侧管理,2025,27(2):55-61,7.基金项目
江苏省自然科学基金资助项目(BK20221165) （BK20221165）
