Study On Energy Management Strategy Of Urban Rail Vehicle Photovoltaic/energy Storage System

With the continuous development of photovoltaic power generation technology and the accelerated construction of rail transit network in major cities,the application of photovoltaic cells in urban rail trains and short-distance intercity trains will be one of the development directions of new energy in rail transit in the future.At present,the research on on-board photovoltaic power generation technology of urban rail transit is still less,and the commercial urban rail train carrying photovoltaic cells is still in the exploratory stage.The on-board photovoltaic of urban rail train faces three problems:first,it is difficult to track maximum power due to the rapid change of illumination during the rapid running of urban rail train;Second,under the environmental conditions of urban rail train running lines,the global optimization speed of photovoltaic cells is slow under the dynamic local shadow of rapid change.Third,photovoltaic power generation fluctuates greatly,so when photovoltaic and hybrid energy storage devices coordinate their output,the management strategy of optical energy storage applicable to urban rail trains is needed.Therefore,this paper takes the efficient utilization of photovoltaic cells on urban rail trains as the goal to study the above three issues.Firstly,an improved variable step size perturbation method for power prediction is proposed for problem 1.On the one hand,in order to reduce the power shock loss,a three-point sampling function model is established based on Newton interpolation method to reduce the deviation between the predicted power value and the actual power value.On the other hand,the dynamic factor of illumination intensity change is included in the process of determining the variable step size.By introducing the correction coefficient of illumination intensity change,a method of determining the variable step size is proposed.Finally,a simulation was built to track the maximum power point.The results show that the improved power prediction variable step size perturbation method can improve the misjudgment and failure problems while tracking the maximum power point more smoothly.Secondly,an improved bat algorithm is proposed to solve the second problem.In order to further improve the tracking speed of the bat algorithm,a corresponding solution is proposed for the three problems of optimal bat number,optimal duty cycle initialization,pulse intensity coefficient and frequency coefficient:The optimal number of bats was obtained by the local convergence probability,the optimal duty cycle was initialized by the expected duty cycle of the multi-peak PV power-voltage curve,and the global and local search abilities of the algorithm were enhanced by the dynamic parameters.Simulation results show that the improved bat algorithm is superior to bat algorithm and particle swarm optimization algorithm in global MPPT tracking time.Finally,aiming at problem 3,a hybrid energy storage control strategy for urban rail train is proposed.The battery maintains the energy supply and demand balance on the bus,and the ultracapacitor provides the high-frequency component of fluctuating power.This paper proposes an energy management method for hybrid energy storage system based on primary power distribution and real-time SOC of supercapacitor to adjust the time constant of low-pass filtering.At the same time,the rules of over charge and over discharge protection and maximum power limit between the battery and the ultracapacitor are proposed.The simulation results show that this method can improve the power fluctuation suppression effect of the hybrid energy storage system and reduce The Times of charge and discharge of the system.