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DESIGN AND DEVELOPMENT OF A 1/3 SCALE VERTICAL AXIS WIND TURBINE FOR ELECTRICAL POWER GENERATION (doi: 10.4090/juee.2007.v1n2.053060)
Abstract
This research describes the electrical power generation in Malaysia by the measurement of wind velocity acting on the wind turbine technology. The primary purpose of the measurement over the 1/3 scaled prototype vertical axis wind turbine for the wind velocity is to predict the performance of full scaled H-type vertical axis wind turbine. The electrical power produced by the wind turbine is influenced by its two major part, wind power and belt power transmission system. The blade and the drag area system are used to determine the powers of the wind that can be converted into electric power as well as the belt power transmission system. In this study both wind power and belt power transmission system has been considered. A set of blade and drag devices have been designed for the 1/3 scaled wind turbine at the Thermal Laboratory of Faculty of Engineering, Universiti Industri Selangor (UNISEL). Test has been carried out on the wind turbine with the different wind velocities of 5.89m/s, 6.08m/s and 7.02m/s. From the experiment, the wind power has been calculated as 132.19 W, 145.40 W and 223.80 W. The maximum wind power is considered in the present study.
... Many research works have been carried out by Walters et al. (1979), Musgrove (1987), Eriksson & Bernhoff (2005, and Greg et al. (2009) due to the demand for supply of electricity from wind turbines and different types of wind turbines have been developed and are available in the market for solving the wind power problems. Based on previous researches on wind turbine, a new design concept of " 1/3 scale H-type, vertical axis wind turbine " was proposed and a prototype has been developed (Hossain et al., 2007). It has the capability to self-start due to the wind flow and efficient performance of the VAWT that could lead to a change in the standard thinking of how wind energy is harnessed, and may spur future VAWT design and research. ...
... Power generation by wind velocity is a complex process with many interacting factors. For this reason, mathematical models have been developed to help to understand this phenomenon (Hossain et al., 2007). Much scientific knowledge has been accumulated on this subject, but not in a useful way for farm transportation decisions. ...
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.
... In addition, around twenty new wind farms have been planned for this region (Sarja & Halonen, 2012). Wind farms consist of many wind turbines set in areas favorable for wind power production (e.g. Hossain et al., 2007). The local media (e.g. ...
Raahe is a medium-sized Finnish town on the western coast of Northern Finland. It has declared itself to become the wind power capital of Finland. The aim of this paper is to find out what being a wind power capital can mean in practice and how it can advance the local industrial business. First, the theoretical framework of this systematic review study was formed by searching theoretical information about the forms of industrial clusters, and it was then examined what kinds of actors take part in these types of clusters. Finally, the actors of the case area were studied. The core companies of wind power clusters are the wind turbine manufacturers, component manufacturers, developers of the wind farms, wind power operators, and service and maintenance organizations. Understanding of the wind power cluster structure may help decision makers to develop the best possible conditions for the emergence of clusters. © 2013 Journal of Urban and Environmental Engineering (JUEE). All rights reserved.
Both air flow mechanics and control system of a wind turbine play an important role in its energy management system. Energy is considered as the essential part for the national development in the form of mechanical power or any other which has major contribution for improving the quality of life and enhancing the economic growth. Subsequently, power generation by wind velocity is a complex process with many interacting factors such as wind velocity, climate condition, natural disaster, control system, design structure, vane tip speed ratio, centrifugal force, rotor drag, turbulence flow, roughness and wind shear, etc. Various procedures have been reported in literature to achieve an optimal performance and system effectiveness. However, these control methods had depended only on exact mathematical modelling or on expert's knowledge that can’t be relied on solely in modelling such a complex management of air flow mechanics due to its unstable climate condition and so on. In the proposed study, an integrated control model using an adaptive neuro- fuzzy inference system for wind turbine power management strategy has been introduced. In this model, an artificial neural network is employed to develop the fuzzy expert system in order to achieve a more realistic evaluation of wind power extraction. Simulations and experiments have been carried out to investigate the effect of control strategy parameters of the wind turbine and its power extraction.
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