Fair charging strategies for EVs connected to a low-voltage distribution network

Mingming Liu; Paul McNamara; Seán McLoone

doi:10.1109/ISGTEurope.2013.6695268

Fair charging strategies for EVs connected to a low-voltage distribution network

Mingming Liu, Paul McNamara, Seán McLoone

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

12 Citations (Scopus)

Abstract

The development of smart grid technologies and appropriate charging strategies are key to accommodating large numbers of Electric Vehicles (EV) charging on the grid. In this paper a general framework is presented for formulating the EV charging optimization problem and three different charging strategies are investigated and compared from the perspective of charging fairness while taking into account power system constraints. Two strategies are based on distributed algorithms, namely, Additive Increase and Multiplicative Decrease (AIMD), and Distributed Price-Feedback (DPF), while the third is an ideal centralized solution used to benchmark performance. The algorithms are evaluated using a simulation of a typical residential low voltage distribution network with 50% EV penetration.

Original language	English
Title of host publication	2013 4th IEEE/PES Innovative Smart Grid Technologies Europe, ISGT Europe 2013
DOIs	https://doi.org/10.1109/ISGTEurope.2013.6695268
Publication status	Published - 01 Dec 2013
Event	2013 4th IEEE/PES Innovative Smart Grid Technologies Europe, ISGT Europe 2013 - Lyngby, Denmark Duration: 06 Oct 2013 → 09 Oct 2013

Conference

Conference	2013 4th IEEE/PES Innovative Smart Grid Technologies Europe, ISGT Europe 2013
Country/Territory	Denmark
City	Lyngby
Period	06/10/2013 → 09/10/2013

Keywords

demand side management
distributed algorithms
electric vehicle charging
smart grid

ASJC Scopus subject areas

Computer Science (miscellaneous)

UN SDGs

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

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10.1109/ISGTEurope.2013.6695268

Cite this

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title = "Fair charging strategies for EVs connected to a low-voltage distribution network",

abstract = "The development of smart grid technologies and appropriate charging strategies are key to accommodating large numbers of Electric Vehicles (EV) charging on the grid. In this paper a general framework is presented for formulating the EV charging optimization problem and three different charging strategies are investigated and compared from the perspective of charging fairness while taking into account power system constraints. Two strategies are based on distributed algorithms, namely, Additive Increase and Multiplicative Decrease (AIMD), and Distributed Price-Feedback (DPF), while the third is an ideal centralized solution used to benchmark performance. The algorithms are evaluated using a simulation of a typical residential low voltage distribution network with 50% EV penetration.",

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AU - McNamara, Paul

AU - McLoone, Seán

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N2 - The development of smart grid technologies and appropriate charging strategies are key to accommodating large numbers of Electric Vehicles (EV) charging on the grid. In this paper a general framework is presented for formulating the EV charging optimization problem and three different charging strategies are investigated and compared from the perspective of charging fairness while taking into account power system constraints. Two strategies are based on distributed algorithms, namely, Additive Increase and Multiplicative Decrease (AIMD), and Distributed Price-Feedback (DPF), while the third is an ideal centralized solution used to benchmark performance. The algorithms are evaluated using a simulation of a typical residential low voltage distribution network with 50% EV penetration.

AB - The development of smart grid technologies and appropriate charging strategies are key to accommodating large numbers of Electric Vehicles (EV) charging on the grid. In this paper a general framework is presented for formulating the EV charging optimization problem and three different charging strategies are investigated and compared from the perspective of charging fairness while taking into account power system constraints. Two strategies are based on distributed algorithms, namely, Additive Increase and Multiplicative Decrease (AIMD), and Distributed Price-Feedback (DPF), while the third is an ideal centralized solution used to benchmark performance. The algorithms are evaluated using a simulation of a typical residential low voltage distribution network with 50% EV penetration.

KW - demand side management

KW - distributed algorithms

KW - electric vehicle charging

KW - smart grid

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DO - 10.1109/ISGTEurope.2013.6695268

M3 - Conference contribution

AN - SCOPUS:84893562930

SN - 9781479929849

BT - 2013 4th IEEE/PES Innovative Smart Grid Technologies Europe, ISGT Europe 2013

T2 - 2013 4th IEEE/PES Innovative Smart Grid Technologies Europe, ISGT Europe 2013

Y2 - 6 October 2013 through 9 October 2013

ER -

Fair charging strategies for EVs connected to a low-voltage distribution network

Abstract

Conference

Keywords

ASJC Scopus subject areas

UN SDGs

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