考虑电动汽车充电需求捕获的配电网光-充协同规划OA

Driven by the strategy of"carbon peaking and carbon neutrality"target,the power distribution networks(PDNs)are integrated with generous electric vehicles(EVs)and distributed photovoltaics(PVs).This integration presents significant challenges for the operation of distribution networks.Implementing collaborative planning for distributed PVs and charging stations,while leveraging the complementary roles of energy sources and loads,is crucial for enhancing the hosting capacity of the distribution network and improving charging convenience for users.However,the demand for EV charging is affected by traffic flow and various other factors,exhibiting heterogeneous characteristics in both spatial and temporal distribution.This variability significantly impacts the planning of charging stations.To address these challenges,we propose a collaborative planning approach for distributed PV and EV charging station that takes into account the capture of charging demand.First,we introduce a charging demand assessment method for charging stations based on the traffic equilibrium model,which quantifies the charging traffic flow at each station under different probabilistic scenarios.This method considers elements such as the uncertainty of user travel demand and is utilized to evaluate the benefits of user charging demand following the construction of charging stations.Building on this foundation,we develop a stochastic optimization-based collaborative planning model for PV-charging stations within distribution networks,accounting for the uncertainties associated with PV output and load variations.Finally,a modified IEEE 33-bus system with a 12-bus transportation network is used as a case study to illustrate the effectiveness of the proposed method.