An MPCC approach on a Stackelberg game in an electric power market: changing the leadership
Main Author: | |
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Publication Date: | 2009 |
Other Authors: | , |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | https://hdl.handle.net/1822/10848 |
Summary: | An electric power market is formulated as a Stackelberg game where two firms, A and B, produce energy. Two distinct situations, according to the firm who plays the leader role, are analysed. In the first one, the firmA is the leader and the firm B is the follower, and in the second situation the players reverse their roles. In order to select the optimal strategy, the leader uses as knowledge his own perception of the market and anticipates the reactions of the other followers. The main goal of this paper is to understand the behaviour of the various agents that compose the electric power network, such as transmissions capacity, quantities of power generated and demanded, when the leadership changes. The problem is formulated as a mathematical program with complementarity constraints (MPCC) and reformulated into a nonlinear program (NLP), allowing the use of robust NLP solvers. Computational results using Lancelot, Loqo and Snopt solvers are performed. The numerical experiments show that the firm profit is conditioned by the available information. |
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An MPCC approach on a Stackelberg game in an electric power market: changing the leadershipElectric powerStackelberg gameLeadershipMPCCNLP solverScience & TechnologyAn electric power market is formulated as a Stackelberg game where two firms, A and B, produce energy. Two distinct situations, according to the firm who plays the leader role, are analysed. In the first one, the firmA is the leader and the firm B is the follower, and in the second situation the players reverse their roles. In order to select the optimal strategy, the leader uses as knowledge his own perception of the market and anticipates the reactions of the other followers. The main goal of this paper is to understand the behaviour of the various agents that compose the electric power network, such as transmissions capacity, quantities of power generated and demanded, when the leadership changes. The problem is formulated as a mathematical program with complementarity constraints (MPCC) and reformulated into a nonlinear program (NLP), allowing the use of robust NLP solvers. Computational results using Lancelot, Loqo and Snopt solvers are performed. The numerical experiments show that the firm profit is conditioned by the available information.Taylor and FrancisUniversidade do MinhoRodrigues, Helena SofiaMonteiro, M. Teresa T.Vaz, A. Ismael F.20092009-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/10848eng"International Journal of Computer Mathematics." ISSN 0020-7160. 86:10-11(2009) 1921-1931.0020-71601029-026510.1080/00207160902906471info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T07:17:59Zoai:repositorium.sdum.uminho.pt:1822/10848Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:22:13.893417Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
An MPCC approach on a Stackelberg game in an electric power market: changing the leadership |
title |
An MPCC approach on a Stackelberg game in an electric power market: changing the leadership |
spellingShingle |
An MPCC approach on a Stackelberg game in an electric power market: changing the leadership Rodrigues, Helena Sofia Electric power Stackelberg game Leadership MPCC NLP solver Science & Technology |
title_short |
An MPCC approach on a Stackelberg game in an electric power market: changing the leadership |
title_full |
An MPCC approach on a Stackelberg game in an electric power market: changing the leadership |
title_fullStr |
An MPCC approach on a Stackelberg game in an electric power market: changing the leadership |
title_full_unstemmed |
An MPCC approach on a Stackelberg game in an electric power market: changing the leadership |
title_sort |
An MPCC approach on a Stackelberg game in an electric power market: changing the leadership |
author |
Rodrigues, Helena Sofia |
author_facet |
Rodrigues, Helena Sofia Monteiro, M. Teresa T. Vaz, A. Ismael F. |
author_role |
author |
author2 |
Monteiro, M. Teresa T. Vaz, A. Ismael F. |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Rodrigues, Helena Sofia Monteiro, M. Teresa T. Vaz, A. Ismael F. |
dc.subject.por.fl_str_mv |
Electric power Stackelberg game Leadership MPCC NLP solver Science & Technology |
topic |
Electric power Stackelberg game Leadership MPCC NLP solver Science & Technology |
description |
An electric power market is formulated as a Stackelberg game where two firms, A and B, produce energy. Two distinct situations, according to the firm who plays the leader role, are analysed. In the first one, the firmA is the leader and the firm B is the follower, and in the second situation the players reverse their roles. In order to select the optimal strategy, the leader uses as knowledge his own perception of the market and anticipates the reactions of the other followers. The main goal of this paper is to understand the behaviour of the various agents that compose the electric power network, such as transmissions capacity, quantities of power generated and demanded, when the leadership changes. The problem is formulated as a mathematical program with complementarity constraints (MPCC) and reformulated into a nonlinear program (NLP), allowing the use of robust NLP solvers. Computational results using Lancelot, Loqo and Snopt solvers are performed. The numerical experiments show that the firm profit is conditioned by the available information. |
publishDate |
2009 |
dc.date.none.fl_str_mv |
2009 2009-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/1822/10848 |
url |
https://hdl.handle.net/1822/10848 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
"International Journal of Computer Mathematics." ISSN 0020-7160. 86:10-11(2009) 1921-1931. 0020-7160 1029-0265 10.1080/00207160902906471 |
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info:eu-repo/semantics/openAccess |
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openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Taylor and Francis |
publisher.none.fl_str_mv |
Taylor and Francis |
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