Comprehensive Modeling of Electric Vehicles in California Demand Response Markets
For grid operators and EV fleet managers, it provides a practical framework to maximize revenue under heterogeneous market rules, though the approach is incremental.
This paper models electric vehicles (EVs) in California demand response markets using real-world data and mixed-integer programming, achieving up to 30% cost savings for fleet operators by optimizing V1G participation.
Electric vehicle (EV) is a significant type of distributed energy resources (DERs), that provide flexibilities to grid operators to achieve a myriad of objectives. This paper presents a comprehensive modeling framework of EVs under multiple real-world demand response (DR) markets in California and provides combined strategies to maximize the revenues via unidirectional EV-Grid integrations (V1G). EV itinerary and usage information from a commercial demonstration site is utilized to model the EV flexibilities, based on which, we modeled the heterogeneous market rules using mixed-integer programming approaches. The system cost-saving performance is analyzed with respect to fleet properties and market constraints, including flexibility, participation threshold, and baseline calculaton, etc.