全球能源互联网2024，Vol.7Issue(4)：406-420,15.DOI:10.19705/j.cnki.issn2096-5125.2024.04.006
基于Spearman相关性阈值寻优和VMD-LSTM的用户级综合能源系统超短期负荷预测
Ultra Short-term Load Forecasting of User Level Integrated Energy System Based on Spearman Threshold Optimization and Variational Mode Decomposition and Long Short-term Memory
摘要
Abstract
The integrated energy system(IES)faces great difficulties because of the strong complexity of the multivariate load series of IES at the user level,which is readily influenced by external factors.For that reason,this paper proposes a load forecasting way based on Spearman correlation threshold optimization,which integrates with variational mode decomposition(VMD)and long short-term memory network(LSTM).To start with,the Spearman rank(SR)correlation coefficient is used to quantitatively calculate the correlation between multiple loads and between loads and other climate factors,and the optimal correlation threshold is determined through cyclic optimization.Then,the VMD algorithm is used to decompose the load characteristic series screened based on the optimal threshold into simpler,more stable the regular intrinsic mode function(IMF)components are input into the LSTM model together with the optimal meteorological characteristics for load forecasting.The effectiveness of the proposed method is verified by the actual data of a user level IES,and the result was indicative of that the way can validly improve the accuracy of the multivariate load forecasting of IES.关键词
负荷预测/综合能源系统/相关性分析/阈值寻优/变分模态分解Key words
load forecasting/integrated energy system(IES)/correlation analysis/threshold optimization/variational mode decomposition(VMD)分类
能源与动力引用本文复制引用
李鹏,罗湘淳,孟庆伟,朱明晓,陈继明..基于Spearman相关性阈值寻优和VMD-LSTM的用户级综合能源系统超短期负荷预测[J].全球能源互联网,2024,7(4):406-420,15.基金项目
山东省自然科学基金(ZR2021ME027). Natural Science Foundation of Shandong Province(ZR2021ME027). （ZR2021ME027）
