A Neural Approach for Optimum Matching of Wind Turbines to The Potential Wind Site to obtain Higher Plant Factor

Pramod Raikar*, Shekhappa G. Ankaliki **
* PG Scholar, Department of Electrical & Electronics, SDMCET, Dharwad, India.
** Professor, Department of Electrical & Electronics, SDMCET, Dharwad,India.
Periodicity:April - June'2014
DOI : https://doi.org/10.26634/jee.7.4.2868

Abstract

A development of the techniques for accurately assessing the wind power potential of site is gaining increased significance. This is because of the fact that the planning and establishment of a wind energy system depends upon various factors. Once the details of wind resource is known for potential wind power site, efficient design of a wind energy system demands optimum matching of wind turbines to the potential wind site to obtain higher plant factor. The model which is designed is useful for planning of the wind power stations as it can be applied for accurate assessment of wind power potential at a site. The Weibull model is the most used one and provides good results. However, the accurate determination of the wind speed distribution law constitutes a major problem. Multi Layer Perceptron type Artificial Neural Networks (ANN) are used here for the approximation of the wind speed distribution law. In this paper, site energy characteristic is determined by means of the neural approach and compared with those obtained by the classical method. Distribution law is achieved by the neural model which provides assessments closer to the discrete distribution than the Weibull model.

Keywords

Multi-Layer Perception, Artificial Neural Networks (ANN), Distribution Law and Weibull Model.

How to Cite this Article?

Raikar, P. and Ankaliki, S. G. (2014). A Neural Approach for Optimum Matching of Wind Turbines to the Potential Wind Site to obtain Higher Plant Factor. i-manager’s Journal on Electrical Engineering , 7(4), 9-16. https://doi.org/10.26634/jee.7.4.2868

References

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