DocumentCode :
2777168
Title :
Research on optimization for the open multi-sources oil-field power net output
Author :
Hong-bo, Bi ; Bing-kun, Gao ; Yu-bo, Zhang
Author_Institution :
Fac. of Electr. & Inf. Eng., Daqing Pet. Inst., Daqing, China
fYear :
2009
fDate :
17-19 June 2009
Firstpage :
1958
Lastpage :
1961
Abstract :
The oil-field power system and provincial power system belong to the different power system, which purchases the maximal economic benefit respectively. Therefore, under the security restraint, how to cooperate each source output to meet the need of economic operation of the oil-field power system adaptively becomes a very important problem. The mathematical model of oil-field power system output optimization is set up under the market condition, which takes the minimal power cost as the objective function, whose constraints include power supply balance, power station output, line security. At the same time, considering the influence on the actual power price of the net losses generated by the difference of the geographical different sources the modified power price is introduced. Furthermore, the improved genetic algorithm using the chaotic searching method is proposed and applied to the optimization for the oil-field power system. Results show that the improved algorithm can reduce the power costs of the oil-field power system.
Keywords :
genetic algorithms; industrial power systems; oil technology; power system economics; chaotic searching method; economic operation; genetic algorithm; market condition; mathematical model; oil-field power system; optimization; Constraint optimization; Cost function; Mathematical model; Power generation; Power generation economics; Power supplies; Power system economics; Power system modeling; Power system security; Power systems; Genetic Algorithm; Optimization; Output; Power Net;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
Type :
conf
DOI :
10.1109/CCDC.2009.5191631
Filename :
5191631
Link To Document :
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