基于IGDT-RO的电动汽车充换电站优化调度策略OA

[Objective]To address the critical challenges of unreasonable battery management and heightened vulnerability to various sources of uncertainty interference that emerge during the process of deep integration between urban electric vehicle battery charging and swapping stations and renewable energy sources,this study is dedicated to significantly improving both the operational economy and robustness of battery charging and swapping station systems within the context of high-proportion renewable energy penetration and complex grid interactions.[Methods]To achieve this goal,an innovative and comprehensive optimal scheduling strategy for battery charging and swapping stations is proposed,based on the synergistic combination of information gap decision theory and robust optimization(IGDT-RO).First,a detailed optimal scheduling model is constructed that integrally encompasses multiple key components:the external power grid,photovoltaic generation units,gas turbines,battery energy storage systems,and diverse charging and swapping facilities.Second,a sophisticated energy management strategy is designed,which is founded on refined battery state-of-charge(SOC)interval management and a well-defined charging/discharging prioritization mechanism,thereby enabling the dynamic maintenance of an adequate inventory of fully charged batteries to meet fluctuating demand.Furthermore,a hybrid uncertainty handling method is innovatively developed:robust optimization is specifically adopted to effectively mitigate the inherent fluctuations in photovoltaic power output,while the information gap decision theory(IGDT)risk-averse model is skillfully integrated to manage the uncertainties associated with load demand.This combined approach fundamentally eliminates the dependency on pre-defined probability distributions or extensive scenario generation,thereby substantially reducing the computational complexity and burden of the scheduling model.[Results]A comprehensive case study,based on a typical industrial park in east China,is meticulously conducted for simulation analysis and validation.By constructing and analyzing multiple simulation scenarios that reflect different decision-maker risk attitudes,the corresponding optimal scheduling schemes for the electric vehicle battery charging and swapping station are derived.The simulation results unequivocally and comprehensively verify the reliability and practical effectiveness of the proposed IGDT-RO-based scheduling model in real-world operational environments,demonstrating its capability to yield both feasible and economically advantageous scheduling outcomes.[Conclusion]The proposed IGDT-RO-based optimal scheduling strategy for battery charging and swapping stations provides a robust and effective solution to the critical challenges of unreasonable battery management and the detrimental impacts of uncertainty interference that arise from the deep integration of renewable energy.It offers robust theoretical and technical support for formulating both economically viable and operationally feasible scheduling schemes for such stations.Consequently,this strategy can significantly enhance the operational economy and bolster the robustness of these station systems,thereby facilitating their reliable and efficient operation within the context of high penetration of renewable energy and supporting the broader goals of sustainable urban energy development.