This paper proposes a collaborative planning model for active distribution network(ADN)and electric vehicle(EV)charging stations that fully considers vehicle-to-grid(V2G)function and reactive power support of EVs in d...This paper proposes a collaborative planning model for active distribution network(ADN)and electric vehicle(EV)charging stations that fully considers vehicle-to-grid(V2G)function and reactive power support of EVs in different regions.This paper employs a sequential decomposition method based on physical characteristics of the problem,breaking down the holistic problem into two sub-problems for solution.Subproblem I optimizes the charging and discharging behavior of autopilot electric vehicles(AEVs)using a mixed-integer linear programming(MILP)model.Subproblem II uses a mixed-integer secondorder cone programming(MISOCP)model to plan ADN and retrofit or construct V2G charging stations(V2GCS),as well as multiple distributed generation resources(DGRs).The paper also analyzes the impact of bi-directional active-reactive power interaction of V2GCS on ADN planning.The presented model is tested in the 47-node ADN in Longgang District,Shenzhen,China,and the IEEE 33-node ADN,demonstrating that decomposition can significantly improve the speed of solving large-scale problems while maintaining accuracy with low AEV penetration.展开更多
基金supported in part by National Natural Science Foundation of China(No.52007123).
文摘This paper proposes a collaborative planning model for active distribution network(ADN)and electric vehicle(EV)charging stations that fully considers vehicle-to-grid(V2G)function and reactive power support of EVs in different regions.This paper employs a sequential decomposition method based on physical characteristics of the problem,breaking down the holistic problem into two sub-problems for solution.Subproblem I optimizes the charging and discharging behavior of autopilot electric vehicles(AEVs)using a mixed-integer linear programming(MILP)model.Subproblem II uses a mixed-integer secondorder cone programming(MISOCP)model to plan ADN and retrofit or construct V2G charging stations(V2GCS),as well as multiple distributed generation resources(DGRs).The paper also analyzes the impact of bi-directional active-reactive power interaction of V2GCS on ADN planning.The presented model is tested in the 47-node ADN in Longgang District,Shenzhen,China,and the IEEE 33-node ADN,demonstrating that decomposition can significantly improve the speed of solving large-scale problems while maintaining accuracy with low AEV penetration.
