DocumentCode :
2469638
Title :
Research on the distributed bio-inspired optimization strategy generator of electricity power enterprises
Author :
Liu, Zhong-jing ; Huo, Xiao-jiang ; Huang, Xun-Cheng ; Chen, Xue-Guang
Author_Institution :
HuaZhong Univ. of Sci. & Technol., Wuhan, China
fYear :
2009
fDate :
16-19 Oct. 2009
Firstpage :
1
Lastpage :
4
Abstract :
At present, the energy-saving & environmental protection dispatching policy is proposed by our country for all power plants, while multiple energy-saving & environmental protection indexes bring a typical non-linear multiple-target decision-making problem, for which nothing can be done by the traditional control method. Therefore, the paper puts forward bionics optimization strategy generator to construct the power generation decision-making information network of power plant set and raises a kind of optimized bionics hardware module based on a hybrid algorithm of ant colony system - the design train of thought for strategy generator.
Keywords :
biocybernetics; decision making; distributed power generation; electricity supply industry; energy conservation; environmental factors; optimisation; power engineering computing; power generation dispatch; ant colony system; bionics optimization; distributed bio inspired optimization strategy generator; electricity power enterprise; energy saving; environmental protection; hybrid algorithm; nonlinear multiple target decision making problem; Ant colony optimization; Decision making; Design optimization; Dispatching; Distributed power generation; Hardware; Hybrid power systems; Power generation; Power generation dispatch; Protection; Ant colony algorithm; Ant colony algorithms Genetic algorithm (ACAGA); Bio-inspired hardware; Combinatorial Optimization; Genetic algorithm (GA); Power dispatching; Strategy generator;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bio-Inspired Computing, 2009. BIC-TA '09. Fourth International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-3866-2
Electronic_ISBN :
978-1-4244-3867-9
Type :
conf
DOI :
10.1109/BICTA.2009.5338088
Filename :
5338088
Link To Document :
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