Research On Optimal Dispatch Model Of Household Energy Hub Based On PSO Algorithm

The energy crisis and environmental pollution problems have attracted more and more attention.Developing the energy Internet is an important way to solve energy problems.As an important part of the energy Internet,energy hubs have important significance and role in the development of the energy Internet.The use of energy hubs to model multi-energy systems can fully consider the mutual aid and complementarity of various forms of energy,and achieve coordinated optimization of various forms of energy.With the popularization of energy sources such as energy storage,distributed new energy and cogeneration,and the widespread use of smart homes,home energy hubs are also beginning to be used by ordinary home users.However,the current modeling and optimization methods for home energy hubs are not comprehensive enough.Based on this,this paper studies it from the following aspects.This paper first introduces the research and development status of energy hubs,and analyzes its basic concepts and mathematical descriptions in detail.Then the detailed description and framework of the home energy hub were carried out,and the family energy hub model was further promoted and revised taking into account the access of elements such as energy storage,distributed new energy and cogeneration.A household energy hub model consisting of household cogeneration,electric vehicles,photovoltaic systems and energy storage systems was proposed.This paper proposes a home energy hub optimization scheduling model with the goal of minimizing energy payment costs.By controlling the energy consumption of household loads,scheduling the charging and discharging of electric vehicles and energy storage systems,managing the direct use of photovoltaic output,storage and whether to sell to the grid to determine the optimal operating mode of the energy hub.The optimal scheduling model is solved by adaptive particle swarm optimization algorithm based on relative progress.The algorithm reduces the blindness of the basic particle swarm optimization algorithm to some extent,and improves the search efficiency and convergence speed.The simulation example demonstrates the rationality of the proposed optimal scheduling model and compares it with the basic particle swarm optimization algorithm.The effectiveness of the adaptive particle swarm optimization algorithm based on relative progress is verified.At present,the user's comfort requirements for power consumption are getting higher and higher.This paper constructs a multi-objective home energy hub optimization scheduling model,which comprehensively considers the energy cost and user comfort of the home energy hub.The proposed model is solved by a multi-objective particle swarm optimization algorithm based on Pareton Nash equilibrium game.The simulation example demonstrates the rationality of the multi-target home energy hub optimization model and verifies the effectiveness of the multi-objective particle swarm optimization algorithm based on the Pareto Nash equilibrium game.