DocumentCode :
3046587
Title :
Optimization of wind-PV hybrid power system based on interactive multi-objective optimization algorithm
Author :
Zhou, Tianpei ; Sun, Wei
Author_Institution :
Dept. of Mech. & Electr. Eng., Xuzhou Coll. of Ind. & Technol., Xuzhou, China
Volume :
2
fYear :
2012
fDate :
18-20 May 2012
Firstpage :
853
Lastpage :
856
Abstract :
The configuration optimization of wind-pv hybrid power system may consider as a problem of multi-object optimization problem, the optimization objective as minimizing system installation cost, subject to power reliability. It was a key how to reasonably settle the configuration to give full play to the superiority of hybrid power systems. Interactive multi-objective optimization algorithm based on preference was proposed in the calculation of the cost (objective) function minimization, the populations, composition of target weight value, was optimized by interactive genetic algorithm, the weighted single objective function was optimized by particle swarm optimization algorithm, which was applied to configuration optimization of wind-pv hybrid power systems. The result shows that the economic performance of the hybrid power system is superior to that of both the single photovoltaic power system and single wind power system under the prerequisite for satisfying the load demand.
Keywords :
genetic algorithms; hybrid power systems; particle swarm optimisation; photovoltaic power systems; power generation reliability; wind power plants; configuration optimization; installation cost; interactive genetic algorithm; interactive multiobjective optimization algorithm; load demand; objective function minimization; optimization objective; particle swarm optimization; power reliability; target weight value; weighted single objective function; wind photovoltaic hybrid power system; Batteries; Genetic algorithms; Hybrid power systems; Optimization; Particle swarm optimization; Photovoltaic systems; Wind power generation; Configuration optimization; Genetic algorithm; Multi-objective optimization algorithm; Particle swarm optimization algorithm; Wind-PV hybrid power system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Measurement, Information and Control (MIC), 2012 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4577-1601-0
Type :
conf
DOI :
10.1109/MIC.2012.6273421
Filename :
6273421
Link To Document :
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