Smart home charging of electric vehicles using a digital platform

Abstract

As the penetration of electric vehicles (EVs) grows, it is important to understand the implications of home charging technologies for grid operations and for the budget of users. We conduct an empirical study analyzing data on 438 EVs over a period of 3,687 consecutive hours, collected by an energy aggregator which operates a digital platform. We first develop an optimization model to compute an optimal schedule of charging for all EVs in the dataset at minimum cost. Then, we compare the realizations against this optimal solution, distinguishing householders who use a smart charging functionality of the digital platform from those who do not use it. Our findings indicate that the smart charging behaviour conduces to better results, and close to the optimal solution. The non-users tend to start charging as soon as they plug-in their EVs, often at peak consumption times. In contrast, the smart charging strategy usually shifts the charging schedules towards times where the consumption is cheaper and the grid is less congested, facilitating a higher load factor and lower power losses. These results highlight the positive role of energy aggregators and digital platforms in coordinating users to lower the cost and enhance efficiency of energy consumption.