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AgentSwitch: towards smart energy tariff selection

Authors:

Sarvapali D. Ramchurn,

Michael Osborne,

Trung D. Huynh,

Muddasser Alam,

Joel E. Fischer,

Steve RobertsAuthors Info & Claims

AAMAS '13: Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems

Pages 981 - 988

Published: 06 May 2013 Publication History

Abstract

In this paper, we present AgentSwitch, a prototype agent-based platform to solve the electricity tariff selection problem. Agent-Switch incorporates novel algorithms to make predictions of hourly energy usage as well as detect (and suggest to the user) deferrable loads that could be shifted to off-peak times to maximise savings. To take advantage of group discounts from energy retailers, we develop a new scalable collective energy purchasing mechanism, based on the Shapley value, that ensures individual members of a collective (interacting through AgentSwitch) fairly share the discounts. To demonstrate the effectiveness of our algorithms we empirically evaluate them individually on real-world data (with up to 3000 homes in the UK) and show that they outperform the state of the art in their domains. Finally, to ensure individual components are accountable in providing recommendations, we provide a novel provenance-tracking service to record of the flow of data in the system, and therefore provide users with a means of checking the provenance of suggestions from AgentSwitch and assess their reliability.

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Cited By

Alan ACostanza EFischer JRamchurn SRodden TJennings NBazzan AHuhns MLomuscio AScerri P(2014)A field study of human-agent interaction for electricity tariff switchingProceedings of the 2014 international conference on Autonomous agents and multi-agent systems10.5555/2615731.2617400(965-972)Online publication date: 5-May-2014
https://dl.acm.org/doi/10.5555/2615731.2617400
Ramchurn SOsborne MParson ORahwan TMaleki SReece SHuynh TAlam MFischer JRodden TMoreau LRoberts SGini MShehory OIto TJonker C(2013)AgentSwitchProceedings of the 2013 international conference on Autonomous agents and multi-agent systems10.5555/2484920.2485245(1401-1402)Online publication date: 6-May-2013
https://dl.acm.org/doi/10.5555/2484920.2485245

Index Terms

AgentSwitch: towards smart energy tariff selection
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Multi-agent systems

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Information & Contributors

Information

Published In

cover image ACM Other conferences

AAMAS '13: Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems

May 2013

1500 pages

ISBN:9781450319935

General Chairs:
Maria Gini
University of Minnesota, USA
,
Onn Shehory
IBM Haifa Research Lab, Israel
,
Program Chairs:
Takayuki Ito
Nagoya Institute of Technology, Japan
,
Catholijn Jonker
Delft Institute of Technology, The Netherlands

Sponsors

IFAAMAS

In-Cooperation

SIGAI: ACM Special Interest Group on Artificial Intelligence

Publisher

International Foundation for Autonomous Agents and Multiagent Systems

Richland, SC

Publication History

Published: 06 May 2013

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AAMAS '13

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AAMAS '13: International conference on Autonomous Agents and Multi-Agent Systems

May 6 - 10, 2013

MN, St. Paul, USA

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AAMAS '13 Paper Acceptance Rate 140 of 599 submissions, 23%;

Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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Cited By

Alan ACostanza EFischer JRamchurn SRodden TJennings NBazzan AHuhns MLomuscio AScerri P(2014)A field study of human-agent interaction for electricity tariff switchingProceedings of the 2014 international conference on Autonomous agents and multi-agent systems10.5555/2615731.2617400(965-972)Online publication date: 5-May-2014
https://dl.acm.org/doi/10.5555/2615731.2617400
Ramchurn SOsborne MParson ORahwan TMaleki SReece SHuynh TAlam MFischer JRodden TMoreau LRoberts SGini MShehory OIto TJonker C(2013)AgentSwitchProceedings of the 2013 international conference on Autonomous agents and multi-agent systems10.5555/2484920.2485245(1401-1402)Online publication date: 6-May-2013
https://dl.acm.org/doi/10.5555/2484920.2485245

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