电力系统保护与控制2025，Vol.53Issue(13)：82-92,11.DOI:10.19783/j.cnki.pspc.241291
基于分行业用电特性与多因素影响的区域级短期用电负荷曲线预测
Regional short-term electricity load curve forecasting based on industry electricity consumption characteristics and multi-factor effects
摘要
Abstract
Aiming at the problem of low accuracy of regional level total electricity load curve forecasting under the"dual carbon"goals,a forecasting framework that incorporates industry-specific electricity consumption characteristics and multi-factor influences is proposed.First,industry load curve clustering analysis and the construction of comprehensive electricity consumption evaluation indicators are used to qualitatively and quantitatively analyze the electricity consumption characteristics of different industries,demonstrating the necessity of refined,industry-level load profiling.Furthermore,the impact of various external factors,such as seasonal temperatures and day types,on industry-specific electricity usage patterns is quantified using nonlinear correlation coefficients and violin plot visualizations,laying a data foundation for fine-grained forecasting.Finally,a hybrid forecasting model is constructed by extracting electricity usage features via convolutional neural network(CNN),integrating them with the bi-directional long short-term memory(BiLSTM)network and the attention mechanism.This ensemble model is used to predict load curves for each industry,and an indirect forecasting approach is applied to reconstruct the total electricity load curve of the entire society.Using load data from eleven industries and residential electricity users in a region of East China,ten groups of comparative experiments are conducted.Results show that the proposed forecasting framework significantly reduces the prediction errors compared to traditional methods.关键词
行业用电特性/综合用电评价指标/小提琴图/负荷曲线预测Key words
industry electricity consumption characteristics/comprehensive electricity consumption evaluation index/violin diagram/load curve forecasting引用本文复制引用
郭耀扬,张利,郝颖,赵波,周颖,马笑天,李闯..基于分行业用电特性与多因素影响的区域级短期用电负荷曲线预测[J].电力系统保护与控制,2025,53(13):82-92,11.基金项目
This work is supported by the Science and Technology Project of the Headquarters of State Grid Corporation of China(No.5108-202218280A-2-379-XG). 国家电网公司总部科技项目资助(5108-202218280A-2-379-XG) （No.5108-202218280A-2-379-XG）
