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http://dx.doi.org/10.5391/JKIIS.2009.19.6.766

Design of Neural Network based MPPT(Maximum Power Point Tracking) Algorithm for Efficient Energy Management in Urban Wind Turbine Generating System  

Kim, Seung-Young (군산대학교 전자정보공학부)
Kim, Sung-Ho (군산대학교 전자정보공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.19, no.6, 2009 , pp. 766-772 More about this Journal
Abstract
Generally, wind industry has been oriented to large power systems which require large windy areas and often need to overcome environment restrictions. However, small-scale wind turbines are closer to the consumers and have a large market potential, and much more efforts are required to become economically attractive. In this paper, a prototype of a small-scale urban wind generation system for battery charging application is described and a neural network based MPPT(Maximum Power Point Tracking) algorithm which can be effectively applied to urban wind turbine system is proposed. Through Matlab based simulation studies and actual implementation of the proposed algorithm, the feasibility of the proposed scheme is verified.
Keywords
Small-scale Urban Wind Turbine; Battery charging; Neural Network; MPPT(Maximum Power Point Tracking);
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