DocumentCode :
2771317
Title :
UK electricity market modeling using combined Conjectural Variation equilibrium method and hierarchical optimization algorithm
Author :
Alikhanzadeh, AmirHessam ; Irving, Malcolm ; Taylor, Gareth A.
fYear :
2012
fDate :
4-7 Sept. 2012
Firstpage :
1
Lastpage :
5
Abstract :
Various methods such as equilibrium models are introduced to manage the risks of participating in the electricity market. Especially in those electricity markets with specific structures, such as BETTA (British Electricity Transmission and Trading Agreement), based on bilateral trading, the usage of this modeling becomes more significant. This paper proposes a novel Conjectural Variation (CV) equilibrium model for bilateral electricity markets, such as BETTA, to reduce the market participants´ exposure to risk. Through an iterative coordination algorithm, consisting of a conjectural variations equilibrium model of an oligopolistic set of generators with a corresponding oligopsonistic equilibrium model of a set of supply companies, the `match´ of both quantity and price between these two models can be obtained. This match can be found by a hierarchical optimization approach, using the Matlab Direct-Search optimization method.
Keywords :
iterative methods; power markets; search problems; BETTA; British electricity transmission and trading agreement; CV equilibrium model; Matlab direct-search optimization method; UK electricity market modeling; bilateral trading; combined conjectural variation equilibrium method; generators; hierarchical optimization algorithm; iterative coordination algorithm; oligopsonistic equilibrium model; Biological system modeling; Companies; Electricity; Electricity supply industry; Generators; Optimization; Power systems; BETTA; bilateral electricity market; conjectural variations equilibrium model; hierarchical optimization method; pattern-search algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Universities Power Engineering Conference (UPEC), 2012 47th International
Conference_Location :
London
Print_ISBN :
978-1-4673-2854-8
Electronic_ISBN :
978-1-4673-2855-5
Type :
conf
DOI :
10.1109/UPEC.2012.6398424
Filename :
6398424
Link To Document :
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