Analyzing EV User Behavior in Aggregator Smart Charging with ESS and Real-Time Pricing

Amidst increasing global electricity consumption, governments prioritize energy efficiency and electric vehicle (EV) integration into energy markets. This study examines EV aggregator strategies employing smart charging methods, adjusting charging rates based on user preferences. Through simulations in Quito's distribution system, it analyzes actions' effects on aggregator costs and technical conditions, with a focus on demand response (DR) strategies, particularly in residential areas. Exploring EVs' potential as energy storage via vehicle-to-home (V2H) and vehicle-to-grid (V2G) options, the study introduces a collaborative evaluation of dynamic pricing and peak power limiting-based DR strategies, integrating bi-directional EV and energy storage system (ESS) use. It also proposes a novel mixed-integer linear programming (MILP) model for home energy management (HEM), incorporating distributed renewable energy, V2H/V2G capabilities, two-way ESS energy trading, and diverse DR strategies. This comprehensive approach assesses the impact of EV owner preferences and ESS availability on reducing total electricity costs through case studies.