Estimating plug-in electric vehicle demand flexibility through an agent-based simulation model

Abstract

In the future context of smart grids, plug-in electric vehicles (PEVs) can be seen not only as a new spatial and temporal distributed load, but also as an electricity storage system. In this sense, the storage capacity can be aggregated and made an active participant in the power market to provide ancillary services. The estimation of this capacity over time and space is challenging as it depends on many factors such as vehicle owner driving profiles, charging behavior, and charging infrastructure features, etc. In this paper the demand flexibility potential of a PEV fleet is estimated using an agent-based modelling approach in which different scenarios of participation in flexible charging mechanisms are evaluated. The case study depicted in this work is based on current technology and demographic data from an urban area in London (UK).