DocumentCode
586790
Title
Optimal dispatch of wind farm based on particle swarm optimization algorithm
Author
Xiaorong Zhu ; Wentong Zhang ; Yi Wang ; Haifeng Liang
Author_Institution
Dept. of Electr. Eng., North China Electr. Power Univ., Baoding, China
fYear
2012
fDate
Oct. 30 2012-Nov. 2 2012
Firstpage
1
Lastpage
5
Abstract
As installed capacity of wind power retains a significant proportion of generation in the power system, the dispatch of wind power brings some new problems to the system. It is an effective way to increase the capabilities of wind farms to regulate active power for grid optimal dispatch support. Particle swarm algorithm is an excellent optimization algorithm for its robustness and versatility, and it has been widely used in the field of power system optimization in recent years. In this paper, an active power dispatch model of wind turbine generators is presented, in which the optimization objective is to minimize the line loss of the wind farm, and the particle swarm optimization algorithm is applied to solve the optimization function. Testing results show that this calculation method could track the power dispatch upon operator´s request more accurately than the conventional distribution method, and the active power loss of wind farm can be reduced.
Keywords
AC generators; particle swarm optimisation; power generation dispatch; wind power plants; active power dispatch model; active power loss; grid optimal dispatch; particle swarm optimization algorithm; power system; power system optimization; wind farm optimal dispatch; wind turbine generators; Computer aided software engineering; Educational institutions; IP networks; Robustness; Turbines; active power loss; doubly fed induction generator (DFIG); optimal dispatch; particle swarm optimization (PSO); wind farm;
fLanguage
English
Publisher
ieee
Conference_Titel
Power System Technology (POWERCON), 2012 IEEE International Conference on
Conference_Location
Auckland
Print_ISBN
978-1-4673-2868-5
Type
conf
DOI
10.1109/PowerCon.2012.6401354
Filename
6401354
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