Research On The Optimization Strategy Of Energy Scheduling In A Community Considering The Orderly Charge And Discharge Of Electric Vehicles

In recent years,with the improvement of urbanization level in China,the electricity consumption of residents is increasing greatly.There are a variety of household appliances,and some newly built residential communities are equipped with a considerable number of distributed power sources(wind power generator,photovoltaic power generator and battery).Meanwhile,with the popularization of electric vehicles in recent years,the uncertainty of electricity consumption in residential communities has been increased.The research content of this paper is mainly divided into two aspects.On the one hand,it is the optimization strategy of electricity consumption for the load in the residential community(including electric vehicles),on the other hand,the optimization strategy of residential community energy scheduling is studied.Firstly,the household load in the community is classified according to the work characteristics,and the electricity consumption model of non-adjustable load,adjustable load,electric water heater,fixed-frequency air conditioner and variablefrequency air conditioner are established respectively.The electricity generation models of wind power generator,photovoltaic power generator and the model of battery charging and battery discharging are established,the model of maintenance cost of wind power generator and photovoltaic power generator are established,the model of battery maintenance cost and the model of battery loss cost are established.According to the one day trip model of electric vehicles provided by the U.S department of transportation,the one day trip data of electric vehicles in the community is obtained through the model simulation.The particle swarm optimization(PSO)algorithm is improved,and verify the effect of the improved particle swarm optimization algorithm.Secondly,Based on the study of the working characteristics of the temperature controlled load,the optimization strategy for the electricity consumption of the temperature controlled load is put forward.Based on the results of temperature control load optimization,the optimization strategy of adjustable load power consumption is proposed.The optimization strategy of adjustable load power consumption aims at the lowest power consumption cost,the smallest peak-valley difference of load curve and the best smoothness of load curve.According to the optimized results of temperature control load and adjustable load,electric vehicle power optimization strategy is given,electric vehicle power consumption optimization strategy can be divided into two modes: the grid can only charge the electric vehicles(G2V)and the electric vehicles can interact with the grid(V2G).The goal of electric vehicle electricity optimization in G2 V mode and V2 G mode during charging is the same as that of the adjustable load electricity optimization strategy,in V2 G mode,the optimal goal is to obtain the highest discharge yield.An example is given to verify the effectiveness of the proposed load power optimization strategy.Finally,based on the load curve of the residential community under the electric vehicle G2 V mode after using the power optimization strategy,the flow chart of the energy scheduling strategy of the community is given.Simulate and solve the energy scheduling strategy flow chart with 15 min and 30 min as the scheduling period respectively.The energy scheduling optimization model is given.The improved particle swarm optimization(PSO)algorithm is used to solve the problem with 15 min and 30 min as scheduling period respectively.Compare the power consumption,maintenance cost of distributed power generation devices,battery maintenance cost and loss cost when the two energy scheduling optimization strategies adopt different scheduling cycles,analyze the advantages and disadvantages of the two energy scheduling strategies and the impact of scheduling results when using different scheduling cycles.