DocumentCode :
3223633
Title :
Wind Farms Reactive Power Optimization Using Genetic/Tabu Hybrid Algorithm
Author :
Li Ling ; Zeng Xiang Jun ; Zhang Ping
Author_Institution :
Sch. of Electr. & Inf. Eng., Changsha Univ. of Sci. & Technol., Changsha
Volume :
1
fYear :
2008
fDate :
20-22 Oct. 2008
Firstpage :
1272
Lastpage :
1276
Abstract :
Considering the dynamic characteristic of wind farms, especially the wind turbines´ output fluctuate with wind speed, the optimal reactive power compensation problem for wind farms is formulated and solved by genetic/tabu search hybrid algorithm (GATS). A mathematical model of reactive power compensation, focused on voltage stability and power losses of wind farms, is developed, and the reactive power optimization scheme using GATS is also presented. Further, the optimization method is tested in a MATLAB based simulation model for an actual wind farm in Inner Mongolia. Test result indicated that the GATS has more powerful global searching ability and can converge more quickly than the genetic algorithm or tabu search respectively. With the computed result, the voltage of wind farms can be restricted within regular range, the power losses is also reduced greatly.
Keywords :
genetic algorithms; optimisation; reactive power control; search problems; voltage control; wind power plants; wind turbines; MATLAB based simulation model; genetic algorithm; genetic-tabu search hybrid algorithm; global search; optimal reactive power compensation problem; voltage stability; wind farms reactive power optimization; wind turbines; Genetics; Mathematical model; Optimization methods; Reactive power; Stability; Testing; Voltage; Wind farms; Wind speed; Wind turbines; Genetic/Tabu hybrid algorithm; Power flow calculation; Reactive power optimizing; Wind farms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3357-5
Type :
conf
DOI :
10.1109/ICICTA.2008.285
Filename :
4659698
Link To Document :
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