Power Demand-Supply Adjustment via Negawatt Trading Based on Regret Matching

Toru Namerikawa

doi:10.1109/CDC51059.2022.9993360

Power Demand-Supply Adjustment via Negawatt Trading Based on Regret Matching

Toru Namerikawa

Department of System Design Engineering

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

Abstract

This study deals with power demand-supply management based on negawatt trading. The aim of this study is to minimize the social cost of negawatt trading and maintain a demand-supply balance. Power consumers and independent system operators participate in the electricity market and each consumer acts based on regret matching, which is one of the learning algorithms. Furthermore, we consider strategy-proofness and individual rationality using VCG mechanism design. In this study, we propose a novel negawatt trading procedure based on regret matching and VCG mechanism design. Finally, the simulation results confirm the effectiveness of the proposed algorithm.

Original language	English
Title of host publication	2022 IEEE 61st Conference on Decision and Control, CDC 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4394-4399
Number of pages	6
ISBN (Electronic)	9781665467612
DOIs	https://doi.org/10.1109/CDC51059.2022.9993360
Publication status	Published - 2022
Event	61st IEEE Conference on Decision and Control, CDC 2022 - Cancun, Mexico Duration: 2022 Dec 6 → 2022 Dec 9

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Volume	2022-December
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	61st IEEE Conference on Decision and Control, CDC 2022
Country/Territory	Mexico
City	Cancun
Period	22/12/6 → 22/12/9

ASJC Scopus subject areas

Control and Systems Engineering
Modelling and Simulation
Control and Optimization

Access to Document

10.1109/CDC51059.2022.9993360

Cite this

Power Demand-Supply Adjustment via Negawatt Trading Based on Regret Matching. / Namerikawa, Toru.

2022 IEEE 61st Conference on Decision and Control, CDC 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 4394-4399 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2022-December).

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

Namerikawa, T 2022, Power Demand-Supply Adjustment via Negawatt Trading Based on Regret Matching. in 2022 IEEE 61st Conference on Decision and Control, CDC 2022. Proceedings of the IEEE Conference on Decision and Control, vol. 2022-December, Institute of Electrical and Electronics Engineers Inc., pp. 4394-4399, 61st IEEE Conference on Decision and Control, CDC 2022, Cancun, Mexico, 22/12/6. https://doi.org/10.1109/CDC51059.2022.9993360

@inproceedings{b887c6adf327493da14a646a9701c244,

title = "Power Demand-Supply Adjustment via Negawatt Trading Based on Regret Matching",

abstract = "This study deals with power demand-supply management based on negawatt trading. The aim of this study is to minimize the social cost of negawatt trading and maintain a demand-supply balance. Power consumers and independent system operators participate in the electricity market and each consumer acts based on regret matching, which is one of the learning algorithms. Furthermore, we consider strategy-proofness and individual rationality using VCG mechanism design. In this study, we propose a novel negawatt trading procedure based on regret matching and VCG mechanism design. Finally, the simulation results confirm the effectiveness of the proposed algorithm.",

author = "Toru Namerikawa",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 61st IEEE Conference on Decision and Control, CDC 2022 ; Conference date: 06-12-2022 Through 09-12-2022",

year = "2022",

doi = "10.1109/CDC51059.2022.9993360",

language = "English",

series = "Proceedings of the IEEE Conference on Decision and Control",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "4394--4399",

booktitle = "2022 IEEE 61st Conference on Decision and Control, CDC 2022",

}

TY - GEN

T1 - Power Demand-Supply Adjustment via Negawatt Trading Based on Regret Matching

AU - Namerikawa, Toru

PY - 2022

Y1 - 2022

N2 - This study deals with power demand-supply management based on negawatt trading. The aim of this study is to minimize the social cost of negawatt trading and maintain a demand-supply balance. Power consumers and independent system operators participate in the electricity market and each consumer acts based on regret matching, which is one of the learning algorithms. Furthermore, we consider strategy-proofness and individual rationality using VCG mechanism design. In this study, we propose a novel negawatt trading procedure based on regret matching and VCG mechanism design. Finally, the simulation results confirm the effectiveness of the proposed algorithm.

AB - This study deals with power demand-supply management based on negawatt trading. The aim of this study is to minimize the social cost of negawatt trading and maintain a demand-supply balance. Power consumers and independent system operators participate in the electricity market and each consumer acts based on regret matching, which is one of the learning algorithms. Furthermore, we consider strategy-proofness and individual rationality using VCG mechanism design. In this study, we propose a novel negawatt trading procedure based on regret matching and VCG mechanism design. Finally, the simulation results confirm the effectiveness of the proposed algorithm.

UR - http://www.scopus.com/inward/record.url?scp=85147041951&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85147041951&partnerID=8YFLogxK

U2 - 10.1109/CDC51059.2022.9993360

DO - 10.1109/CDC51059.2022.9993360

M3 - Conference contribution

AN - SCOPUS:85147041951

T3 - Proceedings of the IEEE Conference on Decision and Control

SP - 4394

EP - 4399

BT - 2022 IEEE 61st Conference on Decision and Control, CDC 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 61st IEEE Conference on Decision and Control, CDC 2022

Y2 - 6 December 2022 through 9 December 2022

ER -

Power Demand-Supply Adjustment via Negawatt Trading Based on Regret Matching

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this