DocumentCode :
570441
Title :
Stochastic unit maintenance model of power prouducers considering market price uncertainty
Author :
Shao, Baozhu ; Wang, Zhiming ; Song, Dan ; Ge, Weichun ; Wang, Chenggang
Author_Institution :
Northeast Electr. Power Res. Inst. Co., Ltd., Shenyang, China
fYear :
2012
fDate :
21-24 May 2012
Firstpage :
1
Lastpage :
5
Abstract :
This paper presents a day-based stochastic unit maintenance schedule (UMS) model for power producers to optimize their payoffs, considering the uncertainty of market prices. In the proposed model, the producer´s benefits include the expected energy-selling profits in energy market and maintenance costs in each period. An effective Monte Carlo simulation based on latin hypercube sampling (LHS-MC) is adopted to evaluate the related risk associated with uncertain energy prices. Then, the proposed UMS issue can be solved via a combination of genetic algorithms and linear programmings. Finally, numerical examples on a four-unit producer are utilized to illustrate the usefulness of the presented scheme.
Keywords :
Monte Carlo methods; genetic algorithms; linear programming; power markets; stochastic processes; day-based stochastic unit maintenance schedule model; effective Monte Carlo simulation; energy market; energy-selling profits; genetic algorithms; latin hypercube sampling; linear programmings; maintenance costs; market price uncertainty; power producers; uncertain energy prices; Electricity; Genetic algorithms; Maintenance engineering; Power systems; Schedules; Stochastic processes; Uncertainty; LHS-MC; fluctuating market prices; power producers; risk; unit maintenance scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Smart Grid Technologies - Asia (ISGT Asia), 2012 IEEE
Conference_Location :
Tianjin
Print_ISBN :
978-1-4673-1221-9
Type :
conf
DOI :
10.1109/ISGT-Asia.2012.6303268
Filename :
6303268
Link To Document :
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