Agent-coordinated virtual power plants of electric vehicles

Research output: Chapter/Conference proceedingConference proceedingAcademicpeer-review

3 Citations (Scopus)

Abstract

Challenges with energy provision due to intermittent renewable energy sources can be addressed with information systems in smart energy markets. One specific solution is virtual power plants (VPP) of electric vehicles (EV). The operation of the VPP is agent controlled, so that cars are charged when market prices on the wholesale market signal excess capacity and turn into a power plant when market prices signal a need for additional energy supply. We show that due to a low utilization of EVs, its storage in idle status can be used by owners of large EV fleets to trade energy on the electricity wholesale market. We scrutinize and evaluate a trading strategy under different scenarios of battery cost developments for large EV fleets owners in the simulation platform Power TAC against the triple bottom line (people, planet, profit). Findings indicate that people pay lower electricity prices under widespread adoption of VPPs of EVs. In addition to that results show a decrease in CO2 emissions for the planet. Finally profits for fleet owners of EV parks are boosted, which decreases with growing market adoption.

Original languageEnglish
Title of host publication13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1547-1548
Number of pages2
Volume2
ISBN (Electronic)9781634391313
Publication statusPublished - 2014
Event13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014 - Paris, France
Duration: 5 May 20149 May 2014

Conference

Conference13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
Country/TerritoryFrance
CityParis
Period5/05/149/05/14

Bibliographical note

Publisher Copyright:
Copyright © 2014, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.

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