Research On Optimized Charging Strategy Of Residential-Side Electric Vehicles Considering Uncertain Factors

With the supply crisis of petroleum resources and environmental pollution problems brought by the development of traditional fuel vehicles,electric vehicles are supported and promoted by governments with their advantages of low energy consumption and low pollution.However,due to the randomness and uncertainty of the charging behavior of electric vehicles in time and space,the disorderly charging of large-scale electric vehicles will cause a lot of adverse effects,such as increasing load,increasing difficulty in grid planning.In this paper,the optimized charging strategy of residential electric vehicles is studied.Considering the uncertainty of charging behavior of residential electric vehicles,the centralized day-ahead charging strategy with minimum peak-valley difference and the real-time charging strategy based on hierarchical multi-agent system are proposed.The main work of this paper includes:(1)By analyzing the charging characteristics of electric vehicles,the mathematical models for charging load of single electric vehicle and multiple electric vehicles under disorderly charging are established respectively,and the influence of disorderly charging of electric vehicles on power grid is analyzed.For large-scale electric vehicles,a centralized day-ahead charging strategy with minimum peak-valley difference is established,taking the charging time of electric vehicles as the optimization object,and the charging demand and adjustable time as constraints.The effectiveness of the proposed method is verified under different penetration rates of electric vehicles.(2)Aiming at households with photovoltaic and electric vehicle,taking into account the uncertainty of electric vehicle charging,the effects of different charging start time and different initial state of charge on photovoltaic consumption and household power peak are analyzed.Taking the residential area with photovoltaic and electric vehicles as the research object,a real-time optimized charging strategy for electric vehicles based on hierarchical multi-agent system is proposed.In the proposed hierarchical multi-agent system,by optimizing the charging power of electric vehicles,a two-stage optimization model under lower-level user agent is established based on the principle of maximizing the utilization of photovoltaic energy and minimizing the charging cost.Considering the operation status of the system,an optimization model for minimizing load fluctuation is established by the transformer agent.At the same time,an optimization model was established when the upper-level grid center agent issued the load intervention instruction.The orderly charging of electric vehicles is realized through a collaborative optimization mechanism among agents at each level.(3)In order to improve the accuracy of the optimization results,an event detection-based uncertainty correction method is proposed to deal with the uncertainties in the optimized charging model.Based on the travel characteristics of users in Ottawa,Canada,the corresponding simulation parameters are set to verify the effectiveness of the optimized charging strategy proposed in this paper.The comparison of the results under different scenarios shows that the optimized charging behavior of electric vehicle achieves better optimization results in improving the photovoltaic consumption ratio,reducing user costs and optimizing the operation status of power grid.