Research on Multi-objective Optimal Scheduling of Large-scale Electric Vehicles Connected to Active Distribution Network

Aiming at the problems of increased active network loss and dispatch cost caused by short-term line congestion when large-scale unordered electric vehicles are connected to the active distribution network, this study proposes an orderly electric vehicle load connected to the active distribution network considering the incentive response of electricity price. Multi-objective day-ahead optimization scheduling strategy for power grid. The introduction of electricity price incentive response promotes the orderly change of the disordered tram load. The optimal power flow model of active distribution network is introduced with mixed integer second-order cone-convex programming. And many constraints such as electric vehicle charging demand, equipment adjustment frequency and distribution network power quality are comprehensively considered, and important equipment of the extended active distribution network is modeled. Based on the EV order mode, the YALMIP+CPLEX plug-in in the MATLAB2018B environment is used for dual-objective solution in the extended IEEE33 node active distribution network. The results show that the introduction of electricity price incentive response to transform the disordered electric vehicle load into order can further optimize the stability goals of energy conservation and environmental protection such as active power grid loss, curtailment of wind and light, carbon emissions, and load fluctuations.