Abstract
With the penetration of electric vehicles (EVs) growing considerably, it is important to understand the implications of different charging mechanisms in the grid operation and in the budget of users. In collaboration with an energy aggregator which has created a fully digital energy platform, we conduct a study analyzing data on EVs charging. Our study is based in Norway, the country with the largest plug-in car segment market share in the world. We first develop an optimization model to compute an ideal scheduling plan. Then, we compare the realized schedules against this ideal solution, distinguishing users 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 considerably better results and close to the idealistic optimal solution. Also, the smart-charging strategy usually shifts the charging schedules towards off-peak times, which helps the grid to be less congested.
Mario Guajardois Professor at the Department of Business and Management Science of NHH Norwegian School of Economics. He received his B.Sc. and M.Sc. from the Department of Industrial Engineering at the University of Chile, and Ph.D. from NHH. He is an active member of the Centre for Shipping and Logistics at NHH. His research interests include operations research, logistics, cooperative game theory, and sports analytics. Among his main recognitions, he has been finalist of the Franz Edelman Award and the Daniel H. Wagner Prize by INFORMS, and the EURO Excellence in Practice Award. He currently serves as Associate Editor in International Transactions in Operational Research and in The Journal of Quantitative Analysis in Sports.