考虑时空耦合的电动汽车接入配电网多维度承载力评估方法研究OA

To address the security challenges posed by the integration of Electric Vehicles(EVs)into distribution networks and the limitations of existing assessment methods in spatiotemporal dynamics and multi-constraint coordination,a multi-dimensional carrying capacity assessment method for EVs considering spatiotemporal coupling and operational constraints is proposed.The method constructs a spatiotemporal probabilistic model for EV charging demand based on trip chain-geographic information,using a bimodal Weibull mixture distribution and a hierarchical Poisson point process to achieve spatiotemporal coupling.An assessment framework integrating voltage security,line thermal stability,and protection coordination is established,employing an improved sequential Monte Carlo simulation for dynamic verification.A three-dimensional index system encompassing technical,economic,and resilience aspects is built,and the entropy-weight-TOPSIS algorithm is introduced to generate a comprehensive carrying capacity index.Simulations show that with unupdated protection settings,the comprehensive carrying capacity is 37.2%.After optimizing protection settings,the physical limits of grid equipment become the core limiting factor.Implementing an orderly charging strategy can increase the carrying capacity to 41.8%.The research provides a theoretical basis for the precise planning and operation of distribution networks with high-penetration EV integration.