Integrated modeling and forecasting of EVs charging profiles based on real data

In the context of energy transition and decarbonization of the economy, several governments will ban the sale of new combustion vehicles by 2050. Thus, growing penetration of electric vehicles (EVs) in distribution networks (DN) is predicted. Impact analyses must be performed to determine if mitigation means are needed to accommodate a large quantity of EVs in the DN. Furthermore, the habits of the local population resulting in different EVs charging patterns needs to be realistically considered. This article presents a multi-charging algorithm for individual residential EVs, developed from the observed charging behaviours of 500 residential EVs in the Hydro-Québec service region. By analysing these charging patterns, probability functions were derived to model daily charging profiles. These profiles can be used to assess the impact of EVs charging on both individual customers and the DN from a quasi-static time-series perspective. An impact evaluation study is also included.