湖北电力2025，Vol.49Issue(3)：92-100,9.DOI:10.3969/j.issn.1006-3986.2025.03.011
基于IWOA-iTransformer-QR的短期城市电力负荷区间预测模型
Short-Term Urban Power Load Interval Forecasting Model Based on IWOA-iTransformer-QR
张健伟 1胡夏波 1周稹坻 1鲁锦峰 1施汉武 1高啸 1罗承威1
作者信息
- 1. 华润电力(湖北)销售有限公司,湖北 武汉 430060
- 折叠
摘要
Abstract
With the connection of renewable energy and new-type loads,the uncertainty of power load forecasting has significantly increased.In view of this,an Improved whale optimization algorithm(IWOA)-based iTransformer quantile regression model(IWOA-iTransformer-QR)is proposed.This model uses IWOA to automatically optimize hyperparameters,and combines iTransformer and quantile regression to implement feature modeling and synchronous quantification of uncertainty.The results of the calculation examples show that this model significantly outperforms the Long Short-Term Memory(LSTM)network,Gated Recurrent Unit(GRU)and Transformer in short-term urban power load forecasting,with the root mean square difference(RMSE)decreased by more than 70%,and can provide a reliable prediction range.The study has proven that the proposed method has potential in improving prediction accuracy and credibility,thus providing support for the scheduling and operation of power systems.关键词
短期电力负荷预测/区间预测/iTransformer/分位数回归/改进鲸鱼优化算法Key words
short-term power load forecasting/interval prediction/iTransformer/quantile regression/improved whale optimization algorithm分类
信息技术与安全科学引用本文复制引用
张健伟,胡夏波,周稹坻,鲁锦峰,施汉武,高啸,罗承威..基于IWOA-iTransformer-QR的短期城市电力负荷区间预测模型[J].湖北电力,2025,49(3):92-100,9.
