面向资源约束的电动公交车充电调度策略OACSTPCD

To reduce the operating cost of electric buses and formulate a reasonable charging schedul-ing scheme for electric buses under the mode of plug-in charging at bus terminals,a resource con-straint-oriented charging scheduling strategy(RCO-CSS)is proposed,which combines operational modeling and a solution algorithm.Considering the spatiotemporal characteristics and charging and discharging characteristics of electric buses,the standard model of the multi-skill resource-con-strained multi-project scheduling problem(MSRC-MPSP)operational programming philosophy is applied to implement the abstract modeling of the target problem for establishing a resource-con-strained charging scheduling model(RCCSM).The RCCSM takes the fleet size and the number of charging piles as resource parameters and aims to minimize the charging cost and average daily equipment purchase cost.A two-stage evolutionary imperialist competitive algorithm(TSE-ICA)is designed to solve the RCCSM to output the optimal charging schedule and corresponding vehicle scheduling plan.Four instances containing 5,10,20,and 36 lines are utilized to evaluate the perfor-mance and check the validity of RCO-CSS.In the numerical experiments,first,the Taguchi method is used to perform a sensitivity analysis of the resource parameters,and it is discovered that more abundant resources correspond to a lower daily charging cost output by the RCCSM but a higher dai-ly purchase cost of vehicles and charging equipment.Second,the experimental results are compared with the results of four advanced metaheuristic algorithms to verify the optimization performance of the TSE-ICA.Compared with the disordered charging scheduling strategy and the conventional or-dered scheduling strategy,it is proved that the RCO-CSS can better reduce the cost of electricity con-sumption,purchase cost of equipment,and battery charging and discharging times.The proposed RCO-CSS combining the MSRC-MPSP and TSE-ICA can allow bus operators to formulate feasible,agile,and efficient charging scheduling schemes and bus driving plans.