We got the power: Predicting available capacity for vehicle-to-grid services using a deep recurrent neural network

Shipman, Rob; Roberts, Rebecca; Waldron, Julie; Naylor, Sophie; Pinchin, James; Rodrigues, Lucelia; Gillott, Mark

doi:10.1016/j.energy.2021.119813

All Outputs (4)

Cost, context, or convenience? Exploring the social acceptance of demand response in the United Kingdom (2021)
Journal Article

The energy sector, and buildings in particular, are one of the main contributors to climate change. Demand-Side Management (DSM) has the potential to realise energy savings on the demand as well as the supply side. However, the domestic sector still... Read More about Cost, context, or convenience? Exploring the social acceptance of demand response in the United Kingdom.

Online machine learning of available capacity for vehicle-to-grid services during the coronavirus pandemic (2021)
Journal Article

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 ser... Read More about Online machine learning of available capacity for vehicle-to-grid services during the coronavirus pandemic.

Assessing the impact of lockdown due to COVID-19 on the electricity consumption of a housing development in the UK (2021)
Book Chapter

In March 2020, the United Kingdom (UK) government ruled that householders must stay home as a response to the COVID-19 outbreak to help flatten the curve of the epidemic and reduce the exponential growth of the virus. Commercial activities, workplace... Read More about Assessing the impact of lockdown due to COVID-19 on the electricity consumption of a housing development in the UK.

We got the power: Predicting available capacity for vehicle-to-grid services using a deep recurrent neural network (2021)
Journal Article

© 2021 Elsevier Ltd Vehicle-to-grid (V2G) services utilise a population of electric vehicle batteries to provide the aggregated capacity required to participate in power and energy markets. Such participation relies on the prediction of available cap... Read More about We got the power: Predicting available capacity for vehicle-to-grid services using a deep recurrent neural network.