@article{(Open Science Index):https://publications.waset.org/pdf/12033,
	  title     = {Optimization Method Based MPPT for Wind Power Generators},
	  author    = {Chun-Yao Lee  and  Yi-Xing Shen  and  Jung-Cheng Cheng  and  Chih-Wen Chang and  Yi-Yin Li},
	  country	= {},
	  institution	= {},
	  abstract     = {This paper proposes the method combining artificial neural network with particle swarm optimization (PSO) to implement the maximum power point tracking (MPPT) by controlling the rotor speed of the wind generator. With the measurements of wind speed, rotor speed of wind generator and output power, the artificial neural network can be trained and the wind speed can be estimated. The proposed control system in this paper provides a manner for searching the maximum output power of wind generator even under the conditions of varying wind speed and load impedance.
	    journal   = {International Journal of Electrical and Computer Engineering},
	  volume    = {3},
	  number    = {12},
	  year      = {2009},
	  pages     = {2277 - 2280},
	  ee        = {https://publications.waset.org/pdf/12033},
	  url   	= {https://publications.waset.org/vol/36},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 36, 2009},