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An Artificial Intelligence Strategy for the Prediction of Wind Speed and Direction in Sarawak for Wind Energy Mapping

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Recent Advances in Mathematical Sciences

Abstract

Accurate and reliable wind speed and direction prediction is one of the necessary concepts in implementing a wind energy system. In this paper, meteorological and geographical variables were modeled via artificial neural networks (ANNs), taking terrain elevation and roughness class into account. The feedforward neural network (FFNN) with back propagation trained with Levenberg–Marquardt algorithm was utilized, with wind speed and direction as the target function in each model. The results obtained using the formulated topographical models showed a regression value R in the range of 0.8256–0.9883. The optimum network based on the lower mean square error and fast computation time was 9-152-1. Thus, the developed topographical feedforward neural network (T-FFNN) is efficient to predict the wind speed and direction properly.

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Acknowledgments

The authors duly thanked the support of Universiti Malaysia Sarawak (UNIMAS) who has supported the data used in the research.

Author information

Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Malaysia Sarawak (UNIMAS), Sarawak, Malaysia

    S. M. Lawan & W. A. W. Z. Abidin

  2. Department of Electrical Engineering, Kano University of Science and Technology, Wudil, Nigeria

    S. M. Lawan

  3. Faculty of Science, Department of Mathematical Science, Bayero University Kano (BUK), P.M.B 3011, Kano, Nigeria

    S. Lawan & A. M. Lawan

Authors
  1. S. M. Lawan
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  2. W. A. W. Z. Abidin
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  3. S. Lawan
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  4. A. M. Lawan
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Corresponding author

Correspondence to S. M. Lawan .

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Editors and Affiliations

  1. Department of Mathematics, University Putra Malaysia, Serdang, Malaysia

    Adem Kılıçman

  2. University of Victoria, Victoria, Canada

    Hari M. Srivastava

  3. Aligarh Muslim University, Aligarh, India

    M. Mursaleen

  4. Universiti Putra Malaysia, Serdang, Malaysia

    Zanariah Abdul Majid

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Lawan, S.M., Abidin, W.A.W.Z., Lawan, S., Lawan, A.M. (2016). An Artificial Intelligence Strategy for the Prediction of Wind Speed and Direction in Sarawak for Wind Energy Mapping. In: Kılıçman, A., Srivastava, H., Mursaleen, M., Abdul Majid, Z. (eds) Recent Advances in Mathematical Sciences. Springer, Singapore. https://doi.org/10.1007/978-981-10-0519-0_7

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