Electric Vehicles

The increasing number of electric vehicles (EVs) on the road brings both opportunities and challenges to the power system. For the EV charging stations (EVCSs), it is often difficult to conduct effective operations due to the incomplete information in EVs’ departure times and the opacity of their preference information. To tackle this challenge, we seek to design the optimal deadline differentiated dynamic price menu that offers multiple choice-pairs of deadlines and charging prices. We prove that such price menus can incentivize EVs to truthfully reveal their departure time. We then...

Energy demand and supply vary from area to area, where an unbalanced load may occur and endanger the system security constraints and cause significant differences in the locational marginal price (LMP) in the power system. With the increasing proportion of local renewable energy (RE) sources in microgrids that are connected to the power grid and the growing number of electric vehicle (EV) charging loads, the imbalance will be further magnified. In this article, we first model the EV charging network as a cyber–physical system (CPS) that is coupled with both the transportation networks and...

Interest in residential batteries to supply photovoltaic (PV) electricity on demand is increasing, however they are not profitable yet. Combining applications has been suggested as a way to increase their attractiveness, but the extent to which this can be achieved, as well as how the different value propositions may affect the optimal battery technology, remain unclear. In this study, we develop an open-source optimization framework to determine the best-suited battery technology depending on the size and the applications combined, including PV self-consumption, demand load-shifting,...

Demand charge often constitutes a significant portion of electricity costs for commercial electric vehicle (EV) charging station operators. This paper explores control methods to reduce peak power consumption at workplace EV charging stations in a joint price and power optimization framework. We optimize a menu of price options to incentivize users to select controllable charging service. Using this framework, we propose a model predictive control approach to reduce both demand charge and overall operator costs. Through a Monte Carlo simulation, we find that our algorithm outperforms a...