Two Stage Operation Optimization Of Integrated Energy System Considering Fluctuation Of Source And Load

The integrated energy system integrates various types of energy supply equipment,energy conversion equipment and energy storage equipment,which can realize the coupling and complementation of various energy sources and coordinated optimization of energy,which provides a new technical means for alleviating the energy crisis.In the integrated energy system,renewable energy equipment is often involved,because these equipment are greatly affected by environmental factors,it will produce strong intermittent volatility.In addition,the diversification of users and the change of energy consumption habits will make the cooling,heating and power load fluctuate.Therefore,considering the source load fluctuation in the operation optimization of integrated energy system is helpful to ensure the safe and stable operation of the system.This paper takes the integrated energy system as the research object,and studies the operation optimization of the integrated energy system from the day ahead stage and the real-time stage on the basis of considering the source load fluctuationFirstly,in order to explore the coupling and coordination relationship between various energy sources and the operation characteristics of various equipment in the integrated energy system,this paper constructs the basic framework of the integrated energy system structure,and analyzes the modeling of the basic energy supply equipment and energy storage equipment in the integrated energy system;secondly,based on the random forest theory,this paper adds the weighted grey relational projection method Based on the improved random forest combination model,this model can predict the output of renewable energy equipment and the demand of cooling,heating and power load of users from a long time scale on the basis of screening similar daily sample set,so as to simplify the calculation of the prediction model and improve the prediction accuracy of the model.The prediction results of this model are designed to provide reference for the future operation of integrated energy system Secondly,this paper constructs the day ahead operation optimization model and solution method of the integrated energy system,taking the minimum daily operation cost and carbon dioxide emission as the dual objectives,considering the constraints of cooling and heating power balance,equipment operation and network transmission,genetic algorithm is used to solve the model,and the Pareto solution set is obtained and then the TOPSIS method is adopted First,based on the actual output of renewable energy equipment and the real-time load of cooling,heating and power of users on that day,the model predicts the load of wind and solar power equipment and users on a short time scale of 15 minutes,and then optimizes the output plan based on the actual output of renewable energy equipment and the real-time load of cooling,heating and power of users Taking the minimum deviation as the objective,the actual output of each equipment in the integrated energy system is adjusted in real time,so as to obtain the real-time rolling operation optimization results of the integrated energy system.Finally,taking the comprehensive energy system of a park in Nanjing as an example,this paper applies the proposed day ahead phase operation optimization model and real-time phase operation optimization model of the comprehensive energy system,and compares and analyzes the output day ahead optimization scheme and real-time optimization scheme.The results show that the model can get the optimal operation plan considering the daily operation cost and carbon dioxide emission.The real-time phase optimization model can get the optimal operation scheme with the minimum deviation from the daily optimization results,effectively reduce the real-time fluctuation of the output of renewable energy equipment such as light wind power and the demand of users on the demand of comprehensive energy system.The impact of balance,environmental protec tion and economy.