Development Of Representative Driving Cycles And Optimal Charging Scheduling For Energy Storage Trams

Energy storage trams(ESTs)play an increasingly important role in the urban public transportation system in recent years due to the advantages of good appearance,environmental friendliness,good flexibility and high efficiency.Against this background,development of representative driving cycles can contribute to the evaluation of charging and discharging demand of trams and provide a criterion for the optimal sizing and safe operation of energy storage systems.What’s more,the study on coordinated charging strategy of ESTs helps to reduce the peak charging power of the line,which is significant for the economy and safety of the whole system.In this case,this paper mainly focuses on the synthesis of representative driving cycles and optimal charging scheduling of ESTs.First of all,this paper proposes station-based microtrip analysis method to develop driving cycles for ESTs.Because the tram load is large but not fixed,this paper considers kinematic and energy consumption characteristics of trams to obtain the representative speed profiles and power profiles.Firstly,error thresholds of kinematic characteristic parameters are defined for the preliminary screening of microtrips.Then square Euclidean distances are calculated by normalized energy consumption characteristic parameters to select the representative microtrip of each station.Finally,representative microtrips are spliced station by station and average dwell times are inserted to develop driving cycles for the whole line.Compared with traditional PCA-based microtrip analysis method,this improved method can not only mirror the kinematic and energy consumption characteristics of trams accurately,but also reduce the computation burden greatly.Subsequently,it is assumed that the ideal tram operation is aligned with representative driving cycles.Therefore,all the operation information of on-line trams has been determined.Because the charging time of ESTs at each station is much shorter than the corresponding dwell time,this paper builds a two-stage optimization model to realize the optimal charging scheduling of trams.In the first stage,the initial charging delay time at each station is optimized to minimize the maximum number of trams charging simultaneously.Then the coordinated charging strategy with the minimum sum of initial charging delay times is obtained among the optimal solutions of the first stage.A case study demonstrates that this method can reduce the maximum number of trams charging simultaneously,which proves the effectiveness of optimal charging scheduling in the ideal situation.Furthermore,since the dwell duration of ESTs at each station is stochastic,a dependent-chance programming model is established for the optimal charging scheduling of ESTs.This model takes the maximum number of trams charging simultaneously not greater than a certain threshold as an event.So the objective function is to maximize the probability of this event.Subsequently a simulation model is built based on the actual operation data of ESTs and then solved by LHS-MCS.The result shows the limitation of the proposed coordinated charging strategy in the actual situation.In other words,the goal of reducing the peak charging power of the whole line can only be fully realized by prolonging the dwell time of ESTs at certain stations.