Abstract
Vehicle-to-grid services make use of the aggregated capacity available from a fleet of vehicles to participate in energy markets, help integrate renewable energy in the grid and balance energy use. In this paper, the critical components of such a service are described in the context of a commercial service that is currently under development. Key among these components is the prediction of available capacity at a future time. In this paper, we extend a previous work that used a deep learning recurrent neural network for this task to include online machine learning, which enables the network to continually refine its predictions based on observed behaviour. The coronavirus pandemic that was declared in 2020 resulted in closures of the university and substantial changes to the behaviour of the university fleet. In this work, the impact of this change in vehicles usage was used to test the predictions of a network initially trained using vehicle trip data from 2019 with and without online machine learning. It is shown that prediction error is significantly reduced using online machine learning, and it is concluded that a similar capability will be of critical importance for a commercial service such as the one described in this paper.
Highlights
Effective management of electricity networks at a distribution level is increasingly important to prevent system issues due to an increase in distributed generation, for example from renewable energy systems, and demand driven in part by the upsurge in electric vehicles (EVs) [1,2]
Enhanced system management provides additional benefits such as the possibility of eligible assets to participate in energy markets, for example EVs through vehicle-to-grid (V2G) or smart charging [3,4,5,6]
V2G services enable electric vehicles to generate an income from participating in electricity trading during the prolonged periods they are not being used for their primary transportation purpose
Summary
Effective management of electricity networks at a distribution level is increasingly important to prevent system issues due to an increase in distributed generation, for example from renewable energy systems, and demand driven in part by the upsurge in electric vehicles (EVs) [1,2]. Enhanced system management provides additional benefits such as the possibility of eligible assets to participate in energy markets, for example EVs through vehicle-to-grid (V2G) or smart charging [3,4,5,6]. Octopus Energy has developed Powerloop, which provides participants with a bi-directional charger and a Nissan LEAF vehicle enabling them to receive financial rewards for making their vehicle available during times of peak demand [8]. Nuvve has developed a V2G platform that makes use of bi-directional chargers and a cloud-based control platform, to enable the use of V2G technology for commercial fleets [10]. EV8 Technologies are piloting and developing the EV8 Live Service, introduced in this paper, to enable V2G for consumers and fleets [11]
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