Demand response for optimisation of power systems demand due to EV charging load

Peng Zhang; Kejun Qian; Chengke Zhou; Brian Stewart; Donald Hepburn

doi:10.1109/APPEEC.2012.6307523

Demand response for optimisation of power systems demand due to EV charging load

Peng Zhang, Kejun Qian, Chengke Zhou, Brian Stewart, Donald Hepburn

Mechanical Engineering

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

14 Citations (Scopus)

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.

Original language	English
Title of host publication	Asia-Pacific Power and Energy Engineering Conference (APPEEC)
Publisher	IEEE
Number of pages	4
ISBN (Print)	9781457705458
DOIs	https://doi.org/10.1109/APPEEC.2012.6307523
Publication status	Published - Sept 2012

Keywords

power systems
demand optimization
consumer behaviour
pricing

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Documents and Links

10.1109/APPEEC.2012.6307523

http://www.appeecconf.org/2012/

Cite this

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title = "Demand response for optimisation of power systems demand due to EV charging load",

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.",

keywords = "power systems, demand optimization, consumer behaviour, pricing",

author = "Peng Zhang and Kejun Qian and Chengke Zhou and Brian Stewart and Donald Hepburn",

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language = "English",

isbn = "9781457705458",

booktitle = "Asia-Pacific Power and Energy Engineering Conference (APPEEC)",

publisher = "IEEE",

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T1 - Demand response for optimisation of power systems demand due to EV charging load

AU - Zhang, Peng

AU - Qian, Kejun

AU - Zhou, Chengke

AU - Stewart, Brian

AU - Hepburn, Donald

PY - 2012/9

Y1 - 2012/9

N2 - 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.

AB - 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.

KW - power systems

KW - demand optimization

KW - consumer behaviour

KW - pricing

U2 - 10.1109/APPEEC.2012.6307523

DO - 10.1109/APPEEC.2012.6307523

M3 - Conference contribution

SN - 9781457705458

BT - Asia-Pacific Power and Energy Engineering Conference (APPEEC)

PB - IEEE

ER -

Demand response for optimisation of power systems demand due to EV charging load

Abstract

Keywords

UN SDGs

Documents and Links

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Cite this