DocumentCode :
508364
Title :
On Purchasing Portfolio for Distribution Companies with Options and Interruptible Load Based on Improved Genetic Algorithm
Author :
Wang, Ruiqing ; Zheng, Xia
Author_Institution :
Sch. of Comput. & Inf. Eng., Anyang Normal Univ., Anyang, China
Volume :
4
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
355
Lastpage :
359
Abstract :
Distribution companies (Discos) are faced with the trade-off between benefit and risk when they purchase electric power energy from several sub-markets under electricity market environment. With conditional value at risk (CVaR) as a measuring index for market risk, a purchasing portfolio model for Discos among the wholesale, forward, options and interruptible load (IL) markets, is presented, in which the objective function is to minimize the portfolio loss. 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 and the IL compensation price have explicitly effect on the portfolio allocation.
Keywords :
distribution networks; genetic algorithms; load (electric); power markets; purchasing; Discos; conditional value at risk; distribution companies; electric power energy; electricity market; improved genetic algorithm; interruptible load; purchasing portfolio; Costs; Distributed computing; Electricity supply industry; Forward contracts; Genetic algorithms; Genetic engineering; Portfolios; Power engineering computing; Power markets; Power system modeling; genetic algorithm; interruptible load; option contract; purchasing portfolio;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
Type :
conf
DOI :
10.1109/ICNC.2009.87
Filename :
5366943
Link To Document :
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