DocumentCode
2340714
Title
The application of combinatorial optimization by Genetic Algorithm and Neural Network
Author
Zhou, Shiqiong ; Kang, Longyun ; Guo, Guifang ; Zhang, Yanning ; Cao, Jianbo ; Cao, Binggang
Author_Institution
Sch. of Mech. Eng., Xi´´an Jiaotong Univ., Xi´´an
fYear
2008
fDate
3-5 June 2008
Firstpage
227
Lastpage
231
Abstract
A optimization model of sizing the storage section in a renewable power generation system was set up, and two methods were used to solve the model: genetic algorithm or combinatorial optimization by genetic algorithm and neural network. The system includes the photovoltaic arrays, the lead-acid battery and a flywheel. The optimal sizing can be considered as a constrained optimization problem: minimization the total capacity of energy storage system, subject to the main constraint of the loss of power supply probability (LPSP). Both of the two optimal algorithm got good results. We can see that, combinatorial optimization by genetic algorithm and neural network can lessen the calculation time, with the results change little.
Keywords
combinatorial mathematics; electric power generation; energy storage; flywheels; genetic algorithms; lead acid batteries; neural nets; renewable energy sources; solar cell arrays; combinatorial optimization; energy storage system capacity; flywheel; genetic algorithm; lead-acid battery; neural network; photovoltaic arrays; power supply probability loss; renewable power generation methods system; Batteries; Capacity planning; Constraint optimization; Flywheels; Genetic algorithms; Neural networks; Optimization methods; Photovoltaic systems; Power system modeling; Solar power generation;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics and Applications, 2008. ICIEA 2008. 3rd IEEE Conference on
Conference_Location
Singapore
Print_ISBN
978-1-4244-1717-9
Electronic_ISBN
978-1-4244-1718-6
Type
conf
DOI
10.1109/ICIEA.2008.4582512
Filename
4582512
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