Research On Multi-objective Economic Scheduling Of Intelligent Community Including Electric Vehicles

With the accelerated development of urbanization in China in recent years,the number of residential communities has gradually increased,and some newly developed smart communities have installed a certain number of distributed power sources(such as photovoltaic and energy storage equipment).The intelligent community will become the main settlement after the gradual development of electric vehicle(EV),while the simultaneous aggregation charging of large-scale electric vehicles will affect the instability of the power grid.The development of distributed energy will be a new challenge to the stable economy of the community.Therefore,reasonable regulation of charging time for EV users and full use of scheduling flexibility of distributed devices and energy storage devices are crucial to improve scheduling economy of the system.The main research contents of this paper are as follows:(1)Firstly,the output characteristics of commonly used distributed power sources such as photovoltaic and energy storage devices in smart residential areas are analyzed,and the photovoltaic system model,energy storage device model and maintenance cost model are established respectively.Then,the disordered charging calculation model of EV in the community is established by studying the historical travel data of owners and the spatio-temporal characteristics of EV.Finally,Monte Carlo method is used to simulate and calculate the unordered charging load curve of EV.(2)The user-side orderly charging control strategy for electric vehicles based on dynamic electricity price is proposed in this paper.according to the original time-of-use electricity price principle of peak and valley periods,combined with the peak hour electricity price,the dynamic peak period and peak period price increase are introduced into the charging electricity price of the owners to formulate the dynamic electricity price charging strategy.At the same time,the minimum average charging cost of users is taken as the objective function to establish an orderly charging model of electric vehicles considering the capacity constraints of transformers.Then,levy flight strategy,adaptive adjustment strategy and weight ratio coefficient are used to improve ant-lion algorithm,which effectively improves the accuracy and optimization of the ant-lion algorithm.Finally,the improved ant-lion algorithm was used to solve the charging load of EV on the user side,and the effectiveness and superior performance of the improved algorithm were verified by simulation experiments.The optimization results also verified that the proposed strategy could further effectively reduce the impact of EV charging on the system.(3)The economic scheduling optimization strategy for intelligent community including electric vehicles is proposed in this paper,and builds a multi-objective optimization model that minimizes the economic operation cost and pollutant treatment cost of the community system.and studied the economic optimization scheduling of the residential system for user-side electric vehicles under the disordered charging mode,time-of-use electricity price orderly charging mode and dynamic electricity price orderly charging mode,as well as considering the charge and discharge optimization strategy of energy storage equipment,and uses the improved ant-lion algorithm to solve.Through the experimental simulation of the three operating modes,the results show that the system operation economy,security and environmental protection can be effectively improved by adopting dynamic electricity price strategy orderly charging and energy storage optimization strategy mode.