Charging behavior guidance strategy for electric vehicle users considering grid demand

With the rapid development of electric vehicles (EVs), uncontrolled EV charging in renewable-dominated power systems may exacerbate peak-valley load differences, posing significant threats to grid stability. Leveraging EVs' mobile energy storage potential through tariff-based coordinated charging offers a dual solution: mitigating grid impacts from random EV charging while compensating for renewable generation fluctuations. This study conducts a comprehensive analysis of user charging demands and behavioral patterns. We enhance traditional Monte Carlo sampling methods to generate more realistic research samples and propose a user charging behavior transition mechanism. Building upon this foundation, a two-layer particle swarm optimization (PSO) algorithm is developed to balance grid operational requirements with the economic interests of charging aggregators and end-users. Ultimately, an optimal vehicle-grid interaction pricing strategy is formulated, demonstrating effective coordination between demand-side management and supply-side variability in high-renewable power systems