Understanding electric vehicle charging behaviours

The UK Government has announced its intention to ban the sales of internal combustion cars and vans from 2035. Ofgem's Decarbonisation Action Plan states that GB electricity network operators should have a network that can power 10 million electric vehicles by 2030. It is widely recognized and acknowledged that stress on current electricity networks can be alleviated with smart technologies, which enable smart demand management using advanced predictive analytics, such as accurate forecasting algorithms, and prescriptive analytics, such as advanced load balancing and optimization algorithms. To successfully utilize analytical models for charging electric vehicles at scale it is essential for these models to inherently capture vehicle users' interaction with charging infrastructure, both personal and public. Hence the need for understanding charging behaviours and the factors that influence these behaviours. The aim of this project is to utilize public and home charging data to develop a finer understanding of charging behaviours and influencing factors, and explore algorithmic frameworks that embed these behaviours in realizing large scale smart charging solutions.