Electric vehicle capacity forecasting model with application to load levelling


Autoria(s): Zhou, Bowen; Littler, Timothy; Foley, Aoife
Data(s)

01/07/2015

Resumo

There are many uncertainties in forecasting the charging and discharging capacity required by electric vehicles (EVs) often as a consequence of stochastic usage and intermittent travel. In terms of large-scale EV integration in future power networks this paper develops a capacity forecasting model which considers eight particular uncertainties in three categories. Using the model, a typical application of EVs to load levelling is presented and exemplified using a UK 2020 case study. The results presented in this paper demonstrate that the proposed model is accurate for charge and discharge prediction and a feasible basis for steady-state analysis required for large-scale EV integration.

Identificador

http://pure.qub.ac.uk/portal/en/publications/electric-vehicle-capacity-forecasting-model-with-application-to-load-levelling(f61ebc84-fe6c-422b-ab20-d047a7932218).html

Idioma(s)

eng

Direitos

info:eu-repo/semantics/restrictedAccess

Fonte

Zhou , B , Littler , T & Foley , A 2015 , ' Electric vehicle capacity forecasting model with application to load levelling ' Paper presented at IEEE Power & Energy Society General Meeting , Denver , United States , 27/07/2015 - 31/07/2015 , .

Palavras-Chave #electric vehicle (EV), capacity forecasting, uncertainty analysis, load levelling
Tipo

conferenceObject