热力发电2024，Vol.53Issue(12)：21-28,8.DOI:10.19666/j.rlfd.202404084
基于变分模态分解的综合能源系统短期电负荷预测
Short-term electrical load forecasting for integrated energy system based on variational mode decomposition
摘要
Abstract
Aiming at the characteristics of complex and variable load and strong coupling of integrated energy system,a combined forecasting model based on variational mode decomposition(VMD),Prophet model,long-and short-term memory network(LSTM)and autoregressive integrated moving average(ARIMA)model is proposed for short-term electrical load prediction.Firstly,the electric load eigen mode functions with different center frequencies and relatively stable ones are obtained by VMD.Then,after calculating the value of zero cross rate,the modal components of each group are superimposed respectively to form the high-frequency and low-frequency timing components,and the Prophet model is used to extract the high-frequency components for timing features.Finally,the ARIMA prediction model is used to predict the low frequency component,and the LSTM neural network model is applied to predict the high frequency component.The final predicted electric load is obtained by superimposing the respective prediction results.The proposed method is applied to the actual integrated energy system,and the example analysis shows that the combined forecasting method presented above has good forecasting performance for the integrated energy system.关键词
综合能源系统/负荷预测/变分模态分解/LSTM神经网络/Prophet模型Key words
integrated energy system/load forecasting/variational mode decomposition/LSTM neural network/Prophet model引用本文复制引用
苏子越,柴琳,谢亮,肖凡..基于变分模态分解的综合能源系统短期电负荷预测[J].热力发电,2024,53(12):21-28,8.基金项目
国家自然科学基金项目(51877161)National Natural Science Foundation of China(51877161) （51877161）
