DocumentCode
3311295
Title
The United Optimal Operation System of Cascade Hydropower Stations Based on Multi-Agent
Author
Zhao, TingHong ; Man, Zibin ; Qi, Xueyi
Author_Institution
Coll. of Fluid Power & Control Eng., Lanzhou Univ. of Technol., Lanzhou
Volume
6
fYear
2008
fDate
18-20 Oct. 2008
Firstpage
571
Lastpage
575
Abstract
With the opening of the electric market of side, the dispatcher scheme by the criteria of the largest power generation capacity has been unable to meet the requirements of cascade hydropower stations´ united optimal operation. Aiming at the characteristics of the current electric market of side implementing the price of electricity of time-sharing and surfing the Net at a competitive price. This paper, combining the theory of Multi-Agent with the united optimal operation, sets up the united optimal operation system of cascade hydropower stations based on Multi-Agent. And in the process of the calculation of united optimal operation, this paper establishes a kind of Master-slave Synchronization Parallel Genetic Algorithm based on Multi-Agent. The application of this system not only improve greatly the communication harmony among the cascade hydropower stations group, and improves speed and precision of the optimal operation calculation greatly, providing a good reference for the optimal operation of the Cascade Hydroelectric Power Stations under the environment of power market.
Keywords
genetic algorithms; hydroelectric power stations; multi-agent systems; power engineering computing; power generation economics; power markets; cascade hydropower stations; dispatcher scheme; electric market; electricity price; master-slave synchronization parallel genetic algorithm; multi-agent; power generation capacity; united optimal operation system; Control engineering; Educational institutions; Hydroelectric power generation; Intelligent agent; Master-slave; Multiagent systems; Power engineering computing; Power generation; Power generation dispatch; Time sharing computer systems; Cascade hydropower stations; Multi-Agent; United optimal operation; genetic algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location
Jinan
Print_ISBN
978-0-7695-3304-9
Type
conf
DOI
10.1109/ICNC.2008.722
Filename
4667901
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