Economic and Environmental Benefits for Electricity Grids from Spatiotemporal Optimization of Electric Vehicle Charging

Abstract

This article addresses the problem of estimating the potential economic and environmental gains for utility grids of shifting the electric-vehicle (EV) charging time and location. The current literature on shifting EV charging loads has been limited by real-world data availability and has typically therefore relied on simulated studies. Collaborating with a large automobile company and a major utility grid operator in California, this research used actual EV operational data and grid-operation data including locational marginal prices, marginal-grid-emission-rate data, and renewable-energy-generation ratio information. With assumptions about the future potential availability of EV charging stations, this research estimated the maximum potential gains in the economic and environmental performance of the electrical-grid operation by optimizing the time and location of EV charging. For the problem of rescheduling the charging sessions, the optimization models and objective functions were specifically designed based on the information available to the energy system operators that influence their economic and environmental performance like grid congestion, emissions, and renewable energy. The results present the maximum potential in reducing the operational costs and the marginal emissions and increasing the renewable energy use in the utility grid by rescheduling the EV charging load with respect to its time and location. The analysis showed that the objective functions of minimizing the marginal cost or the marginal emission rate performed the best overall.