Spatial Arbitrage through Bidirectional Electric Vehicle Charging

Energy arbitrage is typically a temporal process - buying energy when prices are low, and selling when prices are high. However, the spatial variation in electricity prices could generate additional revenue streams if energy were transported to locations with deficits in cheap energy, providing valuable grid services such as congestion relief. In this paper, we develop de-terministic and single-stage stochastic optimization frameworks which maximize revenue by optimizing the charging, discharging, and travel of an electric vehicle under spatial and temporal price uncertainty. The model is also capable of incorporating uncertain traffic data. The results show the potential of bidirectional electric vehicle charging as a mobile grid asset; however, only substantial revenue is realized when prices between areas vary significantly and can be forecast with high probability.