现代科学仪器2024，Vol.41Issue(4)：190-195,6.
基于经验模态分解与偏差校正的配电网短期负荷预测方法
Short term load forecast method of distribution network based on empirical mode decomposition and deviation correction
肖明伟 1舒晓欣 1汪涵 1陈彦斌 1刘于良1
作者信息
- 1. 国网安徽电力有限公司芜湖供电公司,芜湖 241027
- 折叠
摘要
Abstract
Under the influence of uncertain factors such as temperature,rest days and even emergencies,the accuracy of distribution network short-term load forecast is not high.Aiming at the above problems,a distribution network short-term load forecast method based on empirical mode decomposition and deviation correction is proposed.Preprocessing the load data of distribution network,including missing data compensation,abnormal value processing and normalization;Using empirical mode decomposition,the preprocessed distribution network load time series is decomposed into several independent Intrinsic Mode Function components.Taking these components as inputs,the short-term load value of distribution network is analyzed by deep confidence network.The fuzzy control method is introduced to take the two common uncertain factors of temperature change and rest day into account,optimize the basic short-term load forecast results calculated by the depth confidence network,and realize the deviation correction.The results show that the accuracy of distribution network short-term load forecast is improved by the research.关键词
经验模态分解/偏差校正/配电网短期负荷/深度置信网络Key words
empirical mode decomposition/deviation correction/short term load of distribution network/deep confidence network分类
信息技术与安全科学引用本文复制引用
肖明伟,舒晓欣,汪涵,陈彦斌,刘于良..基于经验模态分解与偏差校正的配电网短期负荷预测方法[J].现代科学仪器,2024,41(4):190-195,6.
