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The Shapley value for a fair division of group discounts for coordinating cooling loads

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posted on 2021-11-04, 14:09 authored by Sasan Maleki, Talal Rahwan, Siddhartha Ghosh, Areej Malibari, Daniyal Alghazzaw, Alex Rogers, Hamid Beigy, Nick JenningsNick Jennings
We consider a demand response program in which a block of apartments receive a discount from their electricity supplier if they ensure that their aggregate load from air conditioning does not exceed a predetermined threshold. The goal of the participants is to obtain the discount, while ensuring that their individual temperature preferences are also satisfied. As such, the apartments need to collectively optimise their use of air conditioning so as to satisfy these constraints and minimise their costs. Given an optimal cooling profile that secures the discount, the problem that the apartments face then is to divide the total discounted cost in a fair way. To achieve this, we take a coalitional game approach and propose the use of the Shapley value from cooperative game theory, which is the normative payoff division mechanism that offers a unique set of desirable fairness properties. However, applying the Shapley value in this setting presents a novel computational challenge. This is because its calculation requires, as input, the cost of every subset of apartments, which means solving an exponential number of collective optimisations, each of which is a computationally intensive problem. To address this, we propose solving the optimisation problem of each subset suboptimally, to allow for acceptable solutions that require less computation. We show that, due to the linearity property of the Shapley value, if suboptimal costs are used rather than optimal ones, the division of the discount will be fair in the following sense: each apartment is fairly "rewarded" for its contribution to the optimal cost and, at the same time, is fairly "penalised" for its contribution to the discrepancy between the suboptimal and the optimal costs. Importantly, this is achieved without requiring the optimal solutions.

Funding

National Elites Foundation of Iran

Intelligent Agents for Home Energy Management

Engineering and Physical Sciences Research Council

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HUMAN-AGENT COLLECTIVES: FROM FOUNDATIONS TO APPLICATIONS [ORCHID]

Engineering and Physical Sciences Research Council

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Deanship of Scientific Research at King Abdulaziz University (9-15-1432-HiCi)

History

Published in

PLoS ONE

Volume

15

Issue

1

Publisher

Public Library of Science

Version

  • VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This is an Open Access Article. It is published by Public Library of Science under the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Full details of this licence are available at: https://creativecommons.org/licenses/by/4.0/

Acceptance date

2019-12-11

Publication date

2020-01-10

Copyright date

2020

eISSN

1932-6203

Language

  • en

Article number

e0227049

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