Smart charging for electric vehicles to minimise charging cost

Wang, Yue, Infield, David and Gill, Simon (2017) Smart charging for electric vehicles to minimise charging cost. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 231 (6). pp. 526-534. ISSN 0957-6509

[img]
Preview
Text
Wang_Infield_Gill_JPE_2017_Smart_charging_for_electric_vehicles.pdf - Accepted Version

Download (843kB) | Preview
Official URL: https://doi.org/10.1177/0957650916688409

Abstract

This paper assumes a smart grid framework where the driving patterns for electric vehicles are known, time variations in electricity prices are communicated to householders, and data on voltage variation throughout the distribution system are available. Based on this information, an aggregator with access to this data can be employed to minimise electric vehicles charging costs to the owner whilst maintaining acceptable distribution system voltages. In this study, electric vehicle charging is assumed to take place only in the home. A single-phase Low Voltage (LV) distribution network is investigated where the local electric vehicles penetration level is assumed to be 100%. Electric vehicle use patterns have been extracted from the UK Time of Use Survey data with a 10-min resolution and the domestic base load is generated from an existing public domain model. Apart from the so-called real time price signal, which is derived from the electricity system wholesale price, the cost of battery degradation is also considered in the optimal scheduling of electric vehicles charging. A simple and effective heuristic method is proposed to minimise the electric vehicles’ charging cost whilst satisfying the requirement of state of charge for the electric vehicles’ battery. A simulation in OpenDSS over a period of 24 h has been implemented, taking care of the network constraints for voltage level at the customer connection points. The optimisation results are compared with those obtained using dynamic optimal power flow.

Item Type: Article
Uncontrolled Keywords: Electric vehicles, real time price signal, cost minimisation, dynamic optimal power flow
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Becky Skoyles
Date Deposited: 06 Oct 2017 09:17
Last Modified: 06 Oct 2017 09:36
URI: http://nrl.northumbria.ac.uk/id/eprint/32272

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics


Policies: NRL Policies | NRL University Deposit Policy | NRL Deposit Licence