电力需求侧管理2025，Vol.27Issue(3)：32-37,6.DOI:10.3969/j.issn.1009-1831.2025.03.005
基于BKM-VMD-TCN的日前负荷精准预测
Accurate day-ahead load forecasting method based on BKM-VMD-TCN
摘要
Abstract
Accurate day-ahead load forecasting is essential for optimizing distribution network planning.As the load data available to dis-tribution networks becomes increasingly multidimensional and extensive,efficiently leveraging this data for precise day-ahead load fore-casting has become a key research focus.To address this,an end-to-end approach that integrates data preprocessing,data decomposition,and data forecasting is proposed.In the data preprocessing stage,the bisecting K-means(BKM)clustering technique is used to reduce da-ta noise and categorize the data,while combining dynamic and static feature extraction to capture load characteristics.In the data decompo-sition stage,the variational mode decomposition(VMD)technique is applied to decompose the preprocessed data into frequency compo-nents with strong periodicity and randomness.Finally,in the data forecasting stage,a temporal convolutional network(TCN)is employed to predict each mode component,and the predictions are aggregated to produce the final day-ahead load forecast.Case studies demonstrate that the BKM-VMD-TCN method proposed achieves superior forecasting accuracy compared to three other load forecasting methods.关键词
电力负荷预测/二分K均值/时间卷积网络/变分模态分解Key words
power load forecasting/bisecting K-means/time convolutional network/variational modal decomposition分类
信息技术与安全科学引用本文复制引用
张立,林光亮,陈肯,苏畅,柳伟..基于BKM-VMD-TCN的日前负荷精准预测[J].电力需求侧管理,2025,27(3):32-37,6.基金项目
国网江苏省电力有限公司科技项目(J2023105) （J2023105）
