DocumentCode
572285
Title
Demand Response for Optimisation of Power Systems Demand Due to EV Charging Load
Author
Zhang, Peng ; Qian, Kejun ; Zhou, Chengke ; Stewart, Brian G. ; Hepburn, Donald M.
Author_Institution
Sch. of Eng. & Built Environ., Glasgow Caledonian Univ., Glasgow, UK
fYear
2012
fDate
27-29 March 2012
Firstpage
1
Lastpage
4
Abstract
This paper presents a novel demand response program for optimising power systems demand due to electric vehicle charging load. Based on a mathematical solution to the problem of power systems demand optimization, a demand response program which includes multiple tariffs for different groups of customers is proposed. This program takes into account consumer behaviour with and without external incentives (e.g. time-varying electricity prices). It also prices electricity over 24 hours according to the wholesale market energy price which reflects the generation marginal cost. A comparative study is carried out to evaluate the performance of the program. Three scenarios are considered, i.e. standard tariff, single-tariff and multi-tariff programs. The results show that the multi-tariff program could help utilities reduce daily cost by 1.5% and help customers save electricity bills by 7% compared to the standard tariff.
Keywords
battery powered vehicles; costing; mathematical analysis; performance evaluation; power markets; power system economics; pricing; tariffs; EV charging load; demand response program; electric vehicle charging load; electricity prices; generation marginal cost; mathematical solution; multitariff programs; performance evaluation; power system demand optimisation; single-tariff programs; wholesale market energy price; Batteries; Educational institutions; Electricity; Load management; Optimization; Power systems; Standards;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Engineering Conference (APPEEC), 2012 Asia-Pacific
Conference_Location
Shanghai
ISSN
2157-4839
Print_ISBN
978-1-4577-0545-8
Type
conf
DOI
10.1109/APPEEC.2012.6307523
Filename
6307523
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