Optimal Control Of Electric Bus Battery Swapping And Charging Station

In the context of energy crisis and environmental pollution,the electric vehicle(EV)is raising worldwide concern due to its low carbon and energy saving properties.Electric bus as an application of EV in field of public transportation is more and more commonly seen in city.Large-scale application of electric buses is not only an opportunity but also a challenge to the bus service and the grid,a large number of battery swapping and charging station connected to grid will lead to increased operating cost and power quality deterioration.therefore,both building the model of battery swap demand and station charging load,and analyzing the optimal charging strategy based on station itself or connected to grid,is of great importance to reduced bus service operating costs and promoted reliability of power supply and the promotion of electric buses.With the influence factors of electric buses battery swap demand analyzed and the operation rules of bus service taken into consideration,the models of the buses battery swap demand and the station's charging load is built.Based on these two models,single-objective optimization models with a time-of-use(TOU)charging strategy and a load fluctuationoptimal charging strategy are studied respectively.A multi-objective optimization model with two objectives,charging costs and load fluctuation,is built,also considering constraints from charging conditions of the station.The improved single-objective and multi-objective particle swarm optimization are applied to solve the models,and a linear weighted sum method is applied to filter the final result out of the multi-objective model result archive.After that the influence of results from different strategies on the station's daily operation are studied.Then the influence of station with non-controlled charging on the grid is studied with three aspects including load curves,voltage deviation,and total losses.The single-objective optimization model with loss-optimal strategy is built.Besides,with both station and grid taken into consideration,a multi-objective optimization model with two objectives,total losses and charging costs,is built,also considering the constraints from both sides.These models are solved with particle swarm optimization and the influence of the results on the grid are analyzed.The study results show that the optimization of the charging behavior can effectively reduce the operating costs and its influence on the power grid,single-objective optimization can effectively reduce the target value,and the multi-objective optimization can satisfy several targets to a certain extent at the same time.The study provides a reference for charging control of battery swapping and charging station.