Electric vehicle capacity forecasting model with application to load levelling

Bowen Zhou; Timothy Littler; Aoife Foley

doi:10.1109/PESGM.2015.7285829

Electric vehicle capacity forecasting model with application to load levelling

Bowen Zhou, Timothy Littler, Aoife Foley

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Citations (Scopus)

110 Downloads (Pure)

Abstract

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.

Original language	English
Title of host publication	2015 IEEE Power & Energy Society General Meeting: Proceedings
DOIs	https://doi.org/10.1109/PESGM.2015.7285829
Publication status	Published - 05 Oct 2015
Event	IEEE Power & Energy Society General Meeting - Colorado, Denver, United States Duration: 27 Jul 2015 → 31 Jul 2015 http://www.pes-gm.org/2015/

Publication series

Name	2015 IEEE Power & Energy Society General Meeting: Proceedings
Publisher	IEEE
ISSN (Print)	1932-5517

Conference

Conference	IEEE Power & Energy Society General Meeting
Country	United States
City	Denver
Period	27/07/2015 → 31/07/2015
Internet address	http://www.pes-gm.org/2015/

Keywords

electric vehicle (EV), capacity forecasting, uncertainty analysis, load levelling

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10.1109/PESGM.2015.7285829Licence: Unspecified

Electric Vehicle Capacity Forecasting Model with Application to Load Levelling
© 2015 IEEE. This work is made available online in accordance with the publisher’s policies. Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 373 KB

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title = "Electric vehicle capacity forecasting model with application to load levelling",

abstract = "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.",

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AU - Zhou, Bowen

AU - Littler, Timothy

AU - Foley, Aoife

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N2 - 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.

AB - 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.

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U2 - 10.1109/PESGM.2015.7285829

DO - 10.1109/PESGM.2015.7285829

M3 - Conference contribution

T3 - 2015 IEEE Power & Energy Society General Meeting: Proceedings

BT - 2015 IEEE Power & Energy Society General Meeting: Proceedings

T2 - IEEE Power & Energy Society General Meeting

Y2 - 27 July 2015 through 31 July 2015

ER -

Electric vehicle capacity forecasting model with application to load levelling

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Keywords

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