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Estimation of the Shapley value of a peer-to-peer energy sharing game using multi-step coalitional stratified sampling

Abstract:
One of the main objectives of a peer-to-peer energy market is to efficiently manage distributed energy resources while creating additional financial benefits for the participants. Cooperative game theory offers such a framework, and the Shapley value, a cooperative game payoff allocation based on the participants’ marginal contributions made to the local energy coalition, is shown to be fair and efficient. However, its high computational complexity limits the size of the game. In order to improve this peer-to-peer cooperative scheme’s scalability, this paper investigates and adapts a stratified sampling method for the Shapley value estimation. It then proposes a multi-step sampling strategy to further reduce the computation time by dividing the samples into incremental parts and terminating the sampling process once a certain level of estimation performance is achieved. Finally, selected case studies demonstrate the effectiveness of the proposed method, which is able to scale up the game from 20 players to 100 players.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/s12555-019-0535-1

Authors

More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
Hertford College
Role:
Author
ORCID:
0000-0003-2781-9588
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
Christ Church
Role:
Author
ORCID:
0000-0001-5378-1128


More from this funder
Funder identifier:
https://ror.org/001aqnf71
Grant:
EP/S031901/1
EP/S000887/1
EP/S000887/2
More from this funder
Funder identifier:
https://ror.org/0439y7842
Grant:
EP/N03466X/1
EP/S000887/2
EP/S000887/1


Publisher:
Springer
Journal:
International Journal of Control, Automation and Systems More from this journal
Volume:
19
Issue:
5
Pages:
1863-1872
Publication date:
2021-02-18
Acceptance date:
2020-08-25
DOI:
EISSN:
2005-4092
ISSN:
1598-6446


Language:
English
Keywords:
Pubs id:
1165801
Local pid:
pubs:1165801
Deposit date:
2025-12-19
ARK identifier:

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