DocumentCode :
593357
Title :
Particle swarm optimization-based maximum power point tracking algorithm for wind energy conversion system
Author :
Abdullah, Mohd Ariff ; Yatim, A.H.M. ; Tan, Chee Wei ; Samosir, A.S.
Author_Institution :
Dept. of Energy Conversion, Univ. Teknol. Malaysia (UTM), Skudai, Malaysia
fYear :
2012
fDate :
2-5 Dec. 2012
Firstpage :
65
Lastpage :
70
Abstract :
Due to the nature of unpredicted wind speed, determining the optimal generator speed to extract the maximum available wind power at any wind speed is essential. Therefore, it is significant to include an intelligent controller that can track the maximum peak regardless of wind speed. This paper describes the design and development of particle swarm optimization (PSO)-based maximum power point tracking (MPPT) algorithm to variable-speed fixed-pitch wind turbines. Other than the electrical power subjected to maximization, the proposed algorithm does not need any additional sensor. In addition, the MPPT algorithm does not require any prior knowledge of the wind energy system. Unlike the conventional search optimization method, PSO-based MPPT algorithm produces almost negligible oscillations at the maximum power once the true peak is located. In short, the proposed MPPT is simple, flexible, accurate and efficient in maximum wind power tracking. In this work, MATLAB/Simulink simulation package is used to simulate the performance of the proposed MPPT algorithm.
Keywords :
AC generators; maximum power point trackers; particle swarm optimisation; wind power plants; wind turbines; MPPT algorithm; Matlab-Simulink simulation package; PSO; intelligent controller; maximum power point tracking algorithm; optimal generator speed; particle swarm optimization; search optimization method; unpredicted wind speed; variable-speed fixed-pitch wind turbines; wind energy conversion system; wind energy system; Algorithm design and analysis; Conferences; Generators; Maximum power point tracking; Wind energy; Wind speed; Wind turbines; hill-climb searching (HCS); maximum power point tracking (MPPT); particle swarm optimization (PSO); wind energy system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy (PECon), 2012 IEEE International Conference on
Conference_Location :
Kota Kinabalu
Print_ISBN :
978-1-4673-5017-4
Type :
conf
DOI :
10.1109/PECon.2012.6450296
Filename :
6450296
Link To Document :
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