DocumentCode
3077258
Title
Optimal Purchasing Portfolio for Power Supplier with Options and Interruptible Load Based on Conditional Value-at-Risk
Author
Wang, Ruiqing ; Xiao, Xinfeng ; Dong, Weijun
Author_Institution
Sch. of Comput. & Inf. Eng., Anyang Normal Univ., Anyang, China
Volume
1
fYear
2009
fDate
10-11 July 2009
Firstpage
514
Lastpage
517
Abstract
Power suppliers are faced with the trade-off between benefit and risk when they purchase energy from several sub-markets under electricity market environments. With conditional value-at-risk (CVaR) as a measuring index for market risk, a purchasing model for power suppliers among the wholesale, forward, options and interruptible load (IL) markets, is proposed, in which the objective function is to maximize the portfolio expected revenues. The model can be solved by an improved genetic algorithm, and the impacts of options and IL on purchasing portfolio are analyzed. The results of numerical examples show that options and IL can effectively lower portfolio loss, and the strike price of options, the IL compensation price and the risk evaded mentalities of suppliers have substantially effect on the portfolio allocation. As a consistency risk measurement tool, CVaR can be better applied in risk management of electricity markets.
Keywords
genetic algorithms; investment; power markets; purchasing; risk management; conditional value-at-risk; electricity market; genetic algorithm; interruptible load markets; market risk measurement index; optimal purchasing portfolio; portfolio allocation; portfolio expected revenues; portfolio loss; power supplier; risk management; Costs; Decision making; Electricity supply industry; Forward contracts; Genetic algorithms; Portfolios; Power engineering and energy; Power generation; Power supplies; Risk management; conditional value-at-risk; genetic algorithm; interruptible load; options; purchasing portfolio;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Engineering, 2009. ICIE '09. WASE International Conference on
Conference_Location
Taiyuan, Shanxi
Print_ISBN
978-0-7695-3679-8
Type
conf
DOI
10.1109/ICIE.2009.50
Filename
5211470
Link To Document