Grid integration of electric vehicles for optimal marginal revenue of distribution system operator in spot market

Abstract

Electric vehicles (EVs) combined with low-carbon generator sets can significantly reduce CO2 emissions in the transportation sector. EVs can provide flexible auxiliary services for the grid through proper power dispatching, which benefits both EVs and the grid. This paper discusses the optimal charging and discharging plan for EVs for the purpose of a distribution system operator (DSO) while obtaining the optimal day-ahead bidding strategy for DSO in the spot market. Considering the different charging demands of EV users, two contract models of vehicle-to-grid (V2G) and smart charging services are introduced. Then, K-means clustering is adopted to manage the spatiotemporal uncertainties of EVs, in order to maximize the expected marginal revenue of DSO. Then the optimization model is proposed by considering the real conditions campus grid in Shenzhen and the electricity market in Guangdong province. The result shows that the DSO could obtain the marginal revenue not only by the optimal day-ahead bidding strategy but also by scheduling EVs’ charging and discharging. In addition, EV users could reduce the charging cost by charging their EVs during low electricity price periods and get extra revenue by exporting power to the utility grid during high price periods.