基于多能耦合机理的综合能源系统多元负荷协同预测模型

Multi-load Cooperative Prediction Model of Integrated Energy System Based on Multi-energy Coupling Mechanism

综合能源系统是提高能源利用效率,降低用能成本的重要技术手段,精准负荷预测是综合能源系统优化调度的关键基础和重要前提。随着各类能源耦合设备的应用和提升和电能替代政策的推广,能源之间的关联关系日益增强。然而,现有的负荷预测方法多为对负荷的单独预测,未能将耦合性和互补性结合起来构建预测模型。基于此,首先结合Copula理论分析了综合能源系统中冷、热、电负荷之间的耦合特性;其次,利用樽海鞘群优化算法(SSA)对最小二乘支持向量机(LSSVM)中的关键参数进行求解,建立SSA-LSSVM多元负荷预测模型;最后,通过对比不同场景下的预测效果,证实了所建模型能有效提升预测精度,具有良好的应用效果。研究成果考虑了多能源之间的耦合特性,可为综合能源系统的负荷预测提供技术支撑,从而为系统调度优化提供基础。

Integrated energy system(IES)is an important technical means to improve energy utilization efficiency and reduce energy cost.Accurate load forecasting is the key foundation and important prerequisite for optimal scheduling of integrated energy system.With the application and promotion of all kinds of energy coupling equipment and the promotion of electric energy substitution policy,the relationship between energy is increasing.However,most of the existing load forecasting methods are single load forecasting,which fails to combine the coupling and complementarity to build a forecasting model.Based on this,we first analyzed the coupling characteristics of cold,heat and electrical loads in the integrated energy system with Copula theory.Secondly,we used the Salp Swarm Algorithm(SSA)to solve the key parameters of the Least Squares Support Vector Machine(LSSVM),and established the SSA-LSSVM multiple load forecasting model.Finally,we compared the prediction effect at different scenarios to prove that the model can effectively improve the prediction accuracy and has good application effect.Considering the coupling characteristics of multiple energy sources,the research can provide technical support for load forecasting of IES and provide the basis for system scheduling optimization.