基于综合相关性指标与SA-BiGRU的综合能源系统多元负荷预测OA北大核心CSTPCD

Short-term load forecasting provides a guarantee for the safe and stable operation of IES,but the uncertainty of load fluctuations and the coupling of multiple energy sources increase the difficulty of prediction.To address this,this paper proposes a multi-dimensional load forecasting model for the integrated energy system based on the comprehensive correlation index and SA-BiGRU.Firstly,the comprehensive correlation index is used to calculate the correlation between meteorological factors and loads,and a multi-dimensional load coupling feature matrix is constructed to explore the cross-coupling relationship between energy sources,then the coupled load features are constructed as model inputs.At the same time,It divides the input into different load scenarios using adaptive k-means clustering,in order to reduce modeling complexity.And a self-attention mechanism is incorporated into the bidirectional GRU network to differentiate the importance of input features for enhanced distinction.Finally,compared with other forecasting models,the results show that the proposed method has higher accuracy and shorter forecasting time.