基于机会约束规划的含电动汽车市域铁路牵引供电系统优化运行OA北大核心CSTPCD

The urban railway system provides convenient access to urban and suburban areas.The stations along the railway lines offer parking facilities for electric vehicles(EVs)with park-and-ride scheme and serve as a convenient interface for EVs to connect with the railway traction power system.To improve the utilization rate of regenerative braking energy in trains and reduce the operating cost of urban railways,this study proposes an optimal operation model for co-phase traction power substations in conjunction with EVs in urban rail.The primary objective of this model is to minimize the daily electricity cost of the traction substation(TS)by optimizing the charging and discharging strategy of EVs and ultracapacitors,as well as the power regulation strategy of the TS.To address the uncertainties associated with EV arrival time,departure time,and initial charge state,chance-constrained programming ensures that the EV charging scheme meets the driving requirements at a higher confidence level using probabilistic constraints than the predetermined confidence level of traditional deterministic constraints.The model is formulated as a mixed integer linear programming model by converting chance constraints into deterministic constraints using sample average approximation,and the model is subsequently solved using the CPLEX solver.Simulation analysis shows that the proposed model can effectively reduce the daily electricity cost of the TS by 20.37%,which reflects the feasibility of EVs in participating in the load regulation of the traction power supply system,thereby effectively improving the operating economy of the system.