Regional Multi-energy System Modeling And Simulation And Its Short-term Load Forecasting Method

In a single energy system,the independent operation of the energy terminals makes the utilization of different energy sources not effectively coordinated,which leads to the overall energy utilization efficiency is not high.At the same time,the traditional way of fossil energy generation will cause certain damage to the environment,so it is necessary to reduce the use of fossil energy and increase the exploitation and use of renewable energy.In contrast,in a multi-energy system,the energy efficiency can be improved through multi-energy cooperation,coupling and complementation,and the environmental problems can be alleviated by connecting renewable energy to reduce the use of fossil energy.In order to implement the coordinated utilization of multiple energy sources and accurate comprehensive demand response,accurate prediction of energy load is necessary.The spatial-temporal coupling of multi-energy flow and information flow in multi-energy system is a key problem that restricts the accuracy of energy load prediction..In order to realize accurate prediction of energy load in multi-energy system,this paper conducts photovoltaic micro-grid simulation based on Open DSS and gas turbine modeling based on Simulink.Through platform combination of Open DSS and Simulink,the modeling of multi-energy system is realized,and the accurate prediction of energy load is studied.The efficient fusion of multi-source features is crucial to the accuracy of the prediction model,so the feature extraction and fusion of multi-source data are used as input of the model to predict the energy load.In order to improve the prediction accuracy of the model,the stack integration method is adopted.Finally,an algorithm for load prediction of regional multi-energy system based on multi-source information fusion method and integrated learning is proposed.In the comparison experiment of prediction accuracy based on simulation data,all the comparison performances show that the model proposed in this paper is higher than other classical prediction algorithms in prediction accuracy,and does not produce the case that the prediction accuracy of similar classical algorithms is lower than other algorithms in a certain test data,namely,the generalization is better.It provides a method to predict the energy load of regional multi-energy system.