Research On Energy Collaborative Optimization Of Energy Internet Based On Intelligent Algorithm

In order to cope with the energy crisis and environmental pollution,renewable energy has attracted widespread attention all over the world.Because renewable energy has the characteristics of distribution,intermittence and volatility,direct integration of renewable energy will have an impact on the existing energy network.Energy Internet,as an effective way of energy collaborative optimization,has attracted extensive research from scholars and industry all over the world once it was proposed.Park Energy Internet,as an application form of Energy Internet,the collaborative optimization of many kinds of energy,including distributed renewable energy,is one of the key research points of it.This paper focuses on the Park Energy Internet,takes energy collaborative optimization as the starting point,achieves research on the transition from a single park to multiple parks gradually and complete the in-depth analysis of the issues related to energy collaborative optimization in the Park Energy Internet.The main tasks completed in this article include the following:(1)An energy collaborative optimization method based on multi-dimensional models in a single park environment is proposed.Aiming at the problem of energy collaborative optimization in a single Park Energy Internet,from the point of view of cost,environment and robustness,a multi-objective optimization model is constructed,which includes cost model,environment model and robustness model.An improved multi-objective evolutionary algorithm is proposed.Based on the multiobjective optimization model in the single-park energy Internet,the introduction of a multi-objective evolutionary algorithm based on decomposition and the addition of a dynamic vector adjustment mechanism,which can effectively improve the search efficiency of the algorithm.The improved multi-objective optimization algorithm can provide multiple alternative solutions to the optimization problem in the Park Energy Internet.(2)An energy collaborative optimization method based on multi-agent games in a multiple park environment is proposed.Based on the single Park Energy Internet,further research on the collaborative energy optimization under the multi-Park Energy Internet,and the introduction of noncooperative game theory to analyze the competition and cooperation relationship between the various game agents to form the required game model.In view of the high complexity of the research objects in the multi-park environment,the reinforcement learning algorithm is introduced to solve the problem of the interest game of multi-agents,so as to ensure the entire system operates efficiently while maximizing the benefits of each agent.