Intelligent Load Frequency Control Strategy for Multi-Microgrids with Vehicle-to-Grid Considering Charging Diversity and Extreme Weather

With the rapid electrification of urban transportation and increasing penetration of renewable energy, maintaining frequency stability in smart-city multi-microgrids (MMG) systems increasingly depends on coordinated vehicle-to-grid (V2G) flexibility. However, existing load frequency control strategies typically treat electric vehicles (EVs) as homogeneous resources and overlook the impacts of charging-infrastructure diversity, user mobility constraints, and extreme weather conditions on regulation availability. To address these challenges, this study proposes a weather-adaptive intelligent load frequency control strategy for smart-city MMG considering heterogeneous charging stations and energy requirements of EV users. Fast and slow charging infrastructures are modeled separately to reflect their distinct regulation characteristics, while time-varying charging and discharging margins are derived from travel demand, parking duration, and state-of-charge preferences and further adjusted under extreme weather scenarios. Based on these dynamic constraints, an enhanced multi-agent soft actor–critic (MA-SAC) controller coordinates micro gas turbines and charging stations for distributed frequency regulation. Simulations demonstrate MA-SAC outperforms PID, Fuzzy, and MA-DDPG methods, achieving a 98.51% frequency excellent rate normally and 91.47% during extreme weather. It reduces maximum deviations by up to 80% versus PID, while preserving user travel requirements. The proposed framework provides a practical pathway for integrating electrified mobility into resilient smart-city MMG frequency regulation.