Congestion Relief and Economic Optimization of Integrated Power Stations with Charging and Swapping Functions

To effectively address the challenges of imbalanced equipment utilization, frequent congestion, and poor economic benefits faced by charging and swapping stations (ICSSs), this paper innovatively proposes a comprehensive scheduling strategy that combines user behavior regulation and battery management. In terms of user regulation, an intention-reshaping model for changing user cognition is proposed to equalize the use of charging and swapping (CAS) equipment, easing ICSS congestion. Moreover, an off-station scheduling model for electric vehicles (EVs) is developed to enhance overall ICSS revenue. Within the battery management terms, the suggested inventory battery threshold adjustment method and charging strategy by charging time segmentation are employed to ensure consistent inventory battery supply and cost-effective battery charging. Finally, a two-stage scheduling strategy of in-station and off-station scheduling is suggested for the ICSS, and an improved northern goshawk optimization algorithm (INGO) is used to solve it. The results showed that this strategy reduced the overall congestion of ICSSs by 34% and increased the average annual net revenue by 64%. The goal of alleviating congestion and improving the economic efficiency of ICSSs has been achieved.