Study On Multi-objective Optimal Scheduling And Control Strategy For Energy Internet Based On Cost And Risk

This paper aims at Energy Internet system optimization scheduling problem and puts forward a multi-time scale optimal scheduling strategy based on the periodicity and volatility of loads.In this paper,elite strategy of genetic algorithm is used to solve optimization scheduling method in a long time and the improved particle swarm optimization algorithm is used to solve optimization scheduling method in a short time scale.The following work has been completed specifically:Firstly,this paper introduces the definition of Energy Internet,studies the background and significance of Energy Internet optimal scheduling,and internal and overseas research actuality.Then,active distribution networks model,natural gas networks model,electric load power model represented by electric vehicles are established.The models are simulated according to the actual situation of Energy Internet.After that,the optimal scheduling model of Energy Internet with the goal of lowest cost and lowest risk is presented.Taking the Energy Internet system including wind turbines,photovoltaic cells,miniature gas turbines and gas networks of Xinjiang Goldwind Sci & Tech Co.,Ltd.for example.Using the elite strategy of genetic algorithm and improved particle swarm optimization to simulate the simulate the different time scales of Energy Internet.Through simulation analysis,the correctness and superiority of the optimal scheduling method proposed in this paper are verified.Finally,taking MATLAB as the development platform to complete the simulation design.The experiment verifies the correctness and effectiveness of the optimization scheduling method proposed in this paper,and improves the economics of Energy Internet operation.