IIUM Repository (IREP)

Prediction of power generation of small scale vertical axis wind turbine using fuzzy logic

Hossain, Altab and Rahman, Mohammed Ataur and Rahman, Md. Mozasser and Hasan, SK. and Hossen, Md. Jakir (2009) Prediction of power generation of small scale vertical axis wind turbine using fuzzy logic. Journal of Urban and Emvironmental Engineering, 3 (2). pp. 43-51. ISSN 1982-3932

[img] PDF (Prediction of power generation of small scale vertical axis wind turbine using fuzzy logic) - Published Version
Restricted to Repository staff only until March 2012.

Download (394kB)

Abstract

Renewable energy from the wind turbine has been focused for the alternative source of power generation due to the following advances of the of the wind turbine. Firstly, the wind turbine is highly efficient and eco-friendly. Secondly, the turbine has the ability to response for the changeable power generation based on the wind velocity and structural framework. However, the competitive efficiency of the wind turbine is necessary to successfully alternate the conventional power sources. The most relevant factor which affects the overall efficiency of the wind turbine is the wind velocity and the relative turbine dimensions. Artificial intelligence systems are widely used technology that can learn from examples and are able to deal with non-linear problems. Compared with traditional approach, fuzzy logic approach is more efficient for the representation, manipulation and utilization. Therefore, the primary purpose of this work was to investigate the relationship between wind turbine power generation and wind velocity, and to illustrate how fuzzy expert system might play an important role in prediction of wind turbine power generation. The main purpose of the measurement over the small scaled prototype vertical axis wind turbine for the wind velocity is to predict the performance of full scaled H-type vertical axis wind turbine. Prediction of power generation at the different wind velocities has been tested at the Thermal Laboratory of Faculty of Engineering, Universiti Industri Selangor (UNISEL) and results concerning the daily prediction have been obtained.

Item Type: Article (Journal)
Additional Information: 5264/1459
Uncontrolled Keywords: Wind turbine, power generation, wind velocity, fuzzy logic
Subjects: T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL500 Aeronautics
Kulliyyahs/Centres/Divisions/Institutes: Kulliyyah of Engineering
Kulliyyah of Engineering > Department of Mechanical Engineering
Depositing User: Dr Ataur Rahman
Date Deposited: 12 Sep 2011 12:28
Last Modified: 12 Sep 2011 12:28
URI: http://irep.iium.edu.my/id/eprint/1459

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year