Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/10848

TitleAn MPCC approach on a Stackelberg game in an electric power market: changing the leadership
Author(s)Rodrigues, Helena Sofia
Monteiro, M. Teresa T.
Vaz, A. Ismael F.
KeywordsElectric power
Stackelberg game
Leadership
MPCC
NLP solver
Issue date2009
PublisherTaylor & Francis
JournalInternational Journal of Computer Mathematics
Citation"International Journal of Computer Mathematics." ISSN 0020-7160. 86:10-11(2009) 1921-1931.
Abstract(s)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.
TypeArticle
URIhttp://hdl.handle.net/1822/10848
DOI10.1080/00207160902906471
ISSN0020-7160 (print)
1029-0265 (online)
Peer-Reviewedyes
AccessOpen access
Appears in Collections:LES/ALG - Artigos em revistas científicas internacionais com arbitragem

Files in This Item:
File Description SizeFormat 
An MPCC approach on a Stackelberg game in an electric power market.pdfDocumento principal1,57 MBAdobe PDFView/Open

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID