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.
Highlights
Electric vehicles (EVs) are proliferating in major automobile markets around the world
We addressed the problem of estimating the maximum potential gains in terms of economics, the integration of renewable energy sources, and greenhousegas emission reductions for electrical-grid operators in shifting the time and location of charging EVs based on a real-world study
We present an analysis based on the actual driving and charging behavior of hundreds of EVs operating in the San Francisco Bay Area in California
Summary
Electric vehicles (EVs) are proliferating in major automobile markets around the world. Szinai et al [7] simulated the detailed travel and charging demand of EVs with an agent-based model called BEAM and a grid-operation model called PLEXOS and estimated the maximum benefit in reducing the cost and the renewable energy curtailment with EV-charging management. We identified and recommended an objective function to optimize EV-charging sessions so that the grid operation can improve holistically in terms of operation costs, greenhouse-gas emissions, and renewable energy integration These objective functions were developed based on measurable and immediately useful values to the grid operator.
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