Research On Optimization Strategy Of Household Electricity Based On Demand Response

In recent years,with the development of smart grid technology,as the home energy system of smart grid extension in user side management has become a hot industry,but most of the research results is how to achieve household electricity information collection and power control,and the research results of the optimal control strategy of user experience based on the needs of family comfort in response to the electric load is very small.Therefore,this topic analyzes and studies the optimal demand control strategy based on user comfort experience under the smart grid,and the main research contents are as follows:Firstly,it makes an introduction on demand response,smart grid and household smart power,through consulting the relevant literature at home and abroad.Pointing to the existing problems on the household smart power,it leads to the specific research content of this paper.Secondly,through the analysis of the TOU,RTP,CPP electricity price,the advantages and disadvantages of various electrovalence are given.It is convenient for control strategies to foster strengths and circumvent weaknesses.Then it saves electricity costs to the limit.Moreover,it is as a reference to the control strategies in this paper to analyze some of the existing demand responses.Secondly,the demand response is summarized,introduces the overall control strategy of household electricity demand response based on the overall control strategy consists of four parts,namely: electricity saving control strategy,power control strategy,energy-saving incentive response control strategy and constraints,introduced in detail the contents of each control strategy.Through the research of household electric power control strategy based on demand response,users can save electricity and save user's comfort experience to the greatest extent.Finally,the basic particle swarm optimization(PSO)algorithm and the weight improved particle swarm optimization(PSO)algorithm are introduced in detail.In view of the slow convergence speed of particle swarm optimization in later stage,an immune particle swarm optimization algorithm combining immune algorithm and particle swarm optimization is proposed,which is used to solve the demand response based household electric strategy optimization algorithm,and the corresponding algorithm flow chart is listed.Finally,the simulation platform of MATLAB,combined with immune particle swarm optimization algorithm,the user through the MATLAB simulation of electricity control strategy and the multi-objective optimization function is established,the simulation results show that the control strategy of household electricity demand response based on the optimized target,economic target user comfort and the comprehensive economic index and comfort based on improved optimization.