Short-term prediction method of multiple power load under integrated energy access
The changes between multiple power loads affect the normal operation and coordinated management of the integrated energy system.Therefore,a short-term prediction method for multiple power loads under comprehensive energy access is proposed.Using Copula theory,analyze the nonlinear characteristics between multiple power loads and influencing factors,and form a multivari-ate time series.Input it into the least squares support vector machine model to complete short-term prediction of multivariate power loads.Using the fruit fly optimization algorithm to optimize the prediction model,obtain the best prediction results,and achieve short-term prediction of multiple power loads.The experimental results show that when the penalty coefficient is 0.4 and the search dis-tance is 5,the optimal short-term prediction of multiple power loads can be achieved,with a mean square error of 0.6％-2.5％.This indicates that the proposed method has good prediction performance and provides support for the operation and management of the comprehensive energy system.
integrated energy accessmultiple power loadsshort term forecastcoupling characteristicstime seriesnonlinear
万方数据
维普
