Model and Analysis of Wind Speed Profile using Artificial Neural Network - Feasibility Study in Peninsular Malaysia

Authors

  • Muhammad Nizam Kamarudin Faculty of Electrical Engineering Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka,
  • Abdul Rashid Husain Faculty of Electrical Engineering, Universiti Teknologi Malaysia, UTM Skudai, 81310 Johor
  • Mohamad Noh Ahmad Faculty of Electrical Engineering, Universiti Teknologi Malaysia, UTM Skudai, 81310 Johor
  • Zaharuddin Mohamed Faculty of Electrical Engineering, Universiti Teknologi Malaysia, UTM Skudai, 81310 Johor

DOI:

https://doi.org/10.11113/jt.v74.3566

Keywords:

Wind speed, artificial neural network, wind turbine

Abstract

Accurate modeling of wind speed profile is crucial as the wind speed dynamics are non-deterministic, having chaotic behavior and highly nonlinear in nature. Therefore, obtaining mathematical model of such wind speed profile is rather difficult and vague. In this brief manuscript, the wind speed distribution in Peninsular Malaysia is modeled via the real-time wind data obtained from the Malaysian Meteorological Services (MMS). Artificial neural network (ANN) has been exploited to train the data such that the exact model of wind speed can be identified. The induced wind speed model worthwhile for control engineers to develop control apparatus for wind turbine systems at the selected area of studies. With the wind speed distribution profile, turbine output power can be analyzed and were discussed thoroughly.

References

A. S. Al-Mashakbeh. 2011. Feasibility Study of Using Wind Turbines with Diesel Generators Operating at One of the Rural Sides in Jordan. Journal of Theoretical and Applied Information Technology. 30(2): 109–114.

K. Sopian, M. Y. Othman and A. Wirsat. 1995. The Wind Energy Potential of Malaysia. Renewable Energy. 6(8): 1005–1016.

M. R. S. Siti, M. Norizah and M. Syafrudin. 2011. The Evaluation of Wind Energy Potential in Peninsular Malaysia. International Journal of Chemical and Environmental Engineering. 2(4): 284–291.

Y. D. Song, B. Dhinakaran, and X. Y. Bao. 2000. Variable Speed Control of Wind Turbines using Nonlinear and Adaptive Algorithm. Journal of Wind Engineering and Industrial Aerodynamics. 85: 293–308.

B. Boukhezzar, L. Lupu, H. Siguerdidjane and M. Hand. 2007. Multivariable Control Strategy for Variable Speed Variable Pitch Wind Turbine. Renewable Energy. 32(8): 1273–1287.

U. Ozbay, E. Zergeroglu and S. Sivrioglu. 2008. Adaptive Backstepping Control of Variable Speed Wind Turbines. International Journal of Control. 81(6): 910–919.

B. Beltran, T. Ahmed-Ali and M. E. H. Benbouzid. 2009. High Order Sliding Mode Control of Variable Speed Wind Turbines. IEEE Transactions on Industrial Electronics. 56: 3314–3321.

B. Boukhezzar and H. Siguerdidjane. 2011. Nonlinear Control of a Variable-Speed Wind Turbine Using a Two-Mass Model. IEEE Transaction on Energy Conversion. 26(1): 149–162.

V. Thapar, G. Agnihotri and V. K. Sethi. 2011. Critical Analysis of Methods for Mathematical Modelling of Wind Turbine. Renewable Energy. 36(11): 3166–3177.

M. N. Kamarudin, A. R. Husain and M. N. Ahmad. 2014. Variable Speed Wind Turbine with External Stiffness and Rotor Deviation Observer. Applied Mechanics and Materials. 661: 154–159.

F. A. Inthamoussou, F. D. Bianchi, H. D. Battista and R. J. Mantz. 2014. LPV Wind Turbine Control with Anti-windup Features Covering the Complete Wind Speed Range. IEEE Transaction on Energy Conversion. 29: 259–266.

A. W. Manyonge, R. M. Ochieng, F. N. Onyango and J. M. Shichikha. 2012. Modelling of Wind Turbine in a Wind Energy Conversion System: Power Coefficient Analysis. Applied Mathematical Sciences. 6(91): 4527–4536.

P. M. Anderson and A. Bose. 1983. Stability Simulation of Wind Turbine Systems. IEEE Transaction on Power Apparatus and Systems. PAS-102(12): 3791–3795.

O. Belghazi and M. Cherkaoui. 2012. Pitch Angle Control for Variable Speed Wind Turbines using Genetic Algorithm Controller. Journal of Theoretical and Applied Information Technology. 39(1): 6–10.

Enercon Ltd. http://www.enercon.de/en-en/20.htm.

Wind Energy Solution Ltd.http://www.windenergysolutions.nl/

J. L. Dominguez-Garcia, O. Gomis-Bellmunt, L. Trilla-Romero and A. Junyent-Ferre. 2012. Indirect Vector Control of a Squirrel Cage Induction Generator Wind Turbine. Computers and Mathematics with Applications. 64: 102–114.

M. N. Kamarudin and S. M. Rozali. 2008. Simulink Implementation Of Digital Cascade Control DC Motor Model - A Didactic Approach. 2nd IEEE International Conference on Power and Energy. 1043 – 1048.

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Published

2015-04-13

Issue

Section

Science and Engineering

How to Cite

Model and Analysis of Wind Speed Profile using Artificial Neural Network - Feasibility Study in Peninsular Malaysia. (2015). Jurnal Teknologi (Sciences & Engineering), 74(1). https://doi.org/10.11113/jt.v74.3566