Application of artificial intelligence (AI) in wind energy system with a case study

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Application of artificial intelligence (AI) in wind energy system with a case study

Fay ALZAHRANI, Feroz SHAIK, Nayeemuddin MOHAMMED, Nasser Abdullah Shinoon AL-NA’ABI

Abstract. Renewable energy is the fastest growing source of clean energy worldwide. The employment of wind energy is expected to increase dramatically over the next few years. There is a good source of wind power on the highways due to the movement of vehicles. A small windmill could utilize the wind power generated by passing vehicles and produce electricity that can power the lights on the highway. This paper presents the application of artificial intelligence to predict the current output from a small windmill placed on the highway. The results show a good concurrence between the experimental and predicted values.

Keywords
Wind Energy, Artificial Intelligence, Wind Turbine, Windmill, Genetic Algorithm, Wind Speed, Current Output

Published online 7/15/2024, 8 pages
Copyright © 2024 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA

Citation: Fay ALZAHRANI, Feroz SHAIK, Nayeemuddin MOHAMMED, Nasser Abdullah Shinoon AL-NA’ABI, Application of artificial intelligence (AI) in wind energy system with a case study, Materials Research Proceedings, Vol. 43, pp 96-103, 2024

DOI: https://doi.org/10.21741/9781644903216-13

The article was published as article 13 of the book Renewable Energy: Generation and Application

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

References
[1] Y. Eroğlu and S. U. Seçkiner, “Wind farm layout optimization using particle filtering approach,” Renewable Energy, vol. 58, pp. 95–107, Oct. 2013. https://doi.org/10.1016/j.renene.2013.02.019
[2] National Renewable Energy Laboratory (NREL), Golden, CO., “Small Wind Electric Systems: An Ohio Consumer’s Guide,” DOE/GO-102005-2077, 15016004, Mar. 2005. https://doi.org/10.2172/15016004
[3] T. J. Wenning and J. K. Kissock, “Methodolgy for Preliminary Assessment of Regional Wind Energy Potential,” in ASME 2009 3rd International Conference on Energy Sustainability, Volume 2, San Francisco, California, USA: ASMEDC, Jan. 2009, pp. 1031–1040. https://doi.org/10.1115/ES2009-90469
[4] A. Harrouz, I. Colak, and K. Kayisli, “Control of a small wind turbine system application,” in 2016 IEEE International Conference on Renewable Energy Research and Applications (ICRERA), Birmingham, United Kingdom: IEEE, Nov. 2016, pp. 1128–1133. https://doi.org/10.1109/ICRERA.2016.7884509
[5] R. Ahshan, A. Al-Badi, N. Hosseinzadeh, and M. Shafiq, “Small Wind Turbine Systems for Application in Oman,” in 2018 5th International Conference on Electric Power and Energy Conversion Systems (EPECS), Kitakyushu, Japan: IEEE, Apr. 2018, pp. 1–6. https://doi.org/10.1109/EPECS.2018.8443520
[6] P. Rogowski, M. Rogowska, T. Smaz, and F. Grapow, “Small Wind Turbine Off-Grid Power Generation Optimization,” in 2021 IEEE 4th International Conference on Renewable Energy and Power Engineering (REPE), Beijing, China: IEEE, Oct. 2021, pp. 355–359. https://doi.org/10.1109/REPE52765.2021.9617019
[7] A. M. Eltamaly, “Design and implementation of wind energy system in Saudi Arabia,” Renewable Energy, vol. 60, pp. 42–52, Dec. 2013. https://doi.org/10.1016/j.renene.2013.04.006
[8] M. Zemamou, M. Aggour, and A. Toumi, “Review of savonius wind turbine design and performance,” Energy Procedia, vol. 141, pp. 383–388, Dec. 2017. https://doi.org/10.1016/j.egypro.2017.11.047
[9] S. Vahdatpour, S. Behzadfar, L. Siampour, E. Veisi, and M. Jahangiri, “Evaluation of Off-grid Hybrid Renewable Systems in the Four Climate Regions of Iran,” JREE, vol. 4, no. 1, Feb. 2017. https://doi.org/10.30501/jree.2017.70107
[10] M. Abdelateef Mostafa, E. A. El-Hay, and M. M. ELkholy, “Recent Trends in Wind Energy Conversion System with Grid Integration Based on Soft Computing Methods: Comprehensive Review, Comparisons and Insights,” Arch Computat Methods Eng, vol. 30, no. 3, pp. 1439–1478, Apr. 2023. https://doi.org/10.1007/s11831-022-09842-4
[11] V. Yaramasu, B. Wu, P. C. Sen, S. Kouro, and M. Narimani, “High-power wind energy conversion systems: State-of-the-art and emerging technologies,” Proc. IEEE, vol. 103, no. 5, pp. 740–788, May 2015. https://doi.org/10.1109/JPROC.2014.2378692
[12] N. O. Farrar, M. H. Ali, and D. Dasgupta, “Artificial Intelligence and Machine Learning in Grid Connected Wind Turbine Control Systems: A Comprehensive Review,” Energies, vol. 16, no. 3, p. 1530, Feb. 2023. https://doi.org/10.3390/en16031530
[13] F. Elyasichamazkoti and A. Khajehpoor, “Application of machine learning for wind energy from design to energy-Water nexus: A Survey,” Energy Nexus, vol. 2, p. 100011, Dec. 2021. https://doi.org/10.1016/j.nexus.2021.100011
[14] J. T. Dellosa and E. C. Palconit, “Artificial Intelligence (AI) in Renewable Energy Systems: A Condensed Review of its Applications and Techniques,” in 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), Bari, Italy: IEEE, Sep. 2021, pp. 1–6. https://doi.org/10.1109/EEEIC/ICPSEurope51590.2021.9584587
[15] E. Zhao, S. Sun, and S. Wang, “New developments in wind energy forecasting with artificial intelligence and big data: a scientometric insight,” Data Science and Management, vol. 5, no. 2, pp. 84–95, Jun. 2022. https://doi.org/10.1016/j.dsm.2022.05.002
[16] N. Mohammed, P. Palaniandy, and F. Shaik, “Pollutants removal from saline water by solar photocatalysis: a review of experimental and theoretical approaches,” International Journal of Environmental Analytical Chemistry, vol. 103, no. 16, pp. 4155–4175, Dec. 2023. https://doi.org/10.1080/03067319.2021.1924160
[17] N. Mohammed, A. Asiz, M. A. Khasawneh, H. Mewada, and T. Sultana, “Machine learning and RSM-CCD analysis of green concrete made from waste water plastic bottle caps: Towards performance and optimization,” Mechanics of Advanced Materials and Structures, pp. 1–9, Aug. 2023. https://doi.org/10.1080/15376494.2023.2238220
[18] N. Mohammed, P. Palaniandy, F. Shaik, and H. Mewada, “Experimental and computational analysis for optimization of seawater biodegradability using photo catalysis,” IIUMEJ, vol. 24, no. 2, pp. 11–33, Jul. 2023. https://doi.org/10.31436/IIUMEJ.v24i2.2650
[19] N. Mohammed, P. Palaniandy, F. Shaik, H. Mewada, and D. Balakrishnan, “Comparative studies of RSM Box-Behnken and ANN-Anfis fuzzy statistical analysis for seawater biodegradability using TiO2 photocatalyst,” Chemosphere, vol. 314, p. 137665, Feb. 2023. https://doi.org/10.1016/j.chemosphere.2022.137665
[20] N. Mohammed, P. Palaniandy, F. Shaik, B. Deepanraj, and H. Mewada, “Statistical analysis by using soft computing methods for seawater biodegradability using ZnO photocatalyst,” Environmental Research, vol. 227, p. 115696, Jun. 2023. https://doi.org/10.1016/j.envres.2023.115696
[21] N. Mohammed, P. Palaniandy, F. Shaik, and H. Mewada, “Statistical Modelling of Solar Photocatalytic Biodegradability of Seawater Using Combined Photocatalysts,” J. Inst. Eng. India Ser. E, Sep. 2023. https://doi.org/10.1007/s40034-023-00274-8

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