Abstract
The Vehicle-To-Grid (V2G) concept is a key feature towards the integration of electric vehicles into smart grids. Through V2G sessions, plug-in electric vehicles (PEVs) can sell their surplus energy to the grid. However, profiting from V2G sessions is not trivial for singletons. Thereby, the formation of coalitions among PEVs has been proposed to tackle this issue. In this paper, we rely on domain knowledge in order to propose a novel modelling for such problem. Specifically, we investigate how the similarity among the PEVs' energy profiles can be used to improve the formation of coalitions. The energy profile of a PEV estimates how long such PEV will be available for the V2G session. Based on this, we aim at maximising the coalitions' duration. We empirically show that our approach is both efficient (it outperforms state-of-the-art algorithms in terms of runtime) and effective (solutions were 96.5% of optimum, on average).
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