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Applications of artificial intelligence methods in renewable energy systems

Cilt: 11 Sayı: 1 22 Aralık 2025
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Applications of artificial intelligence methods in renewable energy systems

Öz

In order to reduce environmental problems caused by fossil fuels and to build a sustainable future, radical transformations are required in energy systems. In this transition process, energy sources characterized by environmental sustainability and renewability play a critical role. Renewable energy systems such as solar, wind and hydroelectric power are strategically important for reducing carbon emissions and ensuring energy security. This study comprehensively examines current applications of artificial intelligence (AI) techniques in these energy systems. In particular, it analyzes the contributions of AI-based solutions in key areas such as production forecasting, predictive maintenance strategies, system performance optimization and smart grid integration. Numerous studies have shown that machine learning methods, deep learning approaches and optimization algorithms enable accurate predictions and effective decision-making to address challenges such as intermittency, variability and uncertainty inherent in renewable energy sources. Moreover, the advantages offered by these technologies in enhancing operational efficiency, minimizing energy losses and supporting long-term environmental sustainability are emphasized. The findings suggest that AI-driven systems will significantly contribute to the digital transformation of the energy sector and play a decisive role in shaping the sustainable, flexible and intelligent energy infrastructures of the future.

Anahtar Kelimeler

Kaynakça

  1. IEA. Global Electricity Generation by Renewable Energy Technology, 2023. [Online]. Available: https://www.iea.org/data-and-statistics/charts/global-electricity-generation-by-renewable-energy-technology-main-case-2023-and-2030 (Accessed: 25 June 2025)
  2. IRENA. Future of Solar Photovoltaic: Deployment, investment, technology, grid integration and socio-economic aspects, 2019. [Online]. Available: https://serendipv.eu/media/filer_public/86/a4/86a4e88a-61cc-4b2e-bc31-8d373805c229/irena_future_of_solar_pv_2019.pdf (Accessed: 25 June 2025)
  3. Sayed, E.T., Olabi, A.G., Alami, A.H.; Radwan, A., Mdallal, A., Rezk, A., Abdelkareem, M.A. Renewable Energy and Energy Storage Systems. Energies 2023, 16, 1415.
  4. Kiasari, M.; Ghaffari, M.; Aly, H.H. A Comprehensive Review of the Current Status of Smart Grid Technologies for Renewable Energies Integration and Future Trends: The Role of Machine Learning and Energy Storage Systems. Energies 2024, 17, 4128.
  5. Global Wind Energy Council (GWEC). GWEC Global Wind Report 2025, 2025. GWEC Publications, Lisbon, Portugal, 20.
  6. Blaabjerg, F. and Ma, K. 2017. Wind energy systems. IEEE Transactions on Industrial Electronics, 105(11), 2116–2131.
  7. Serrano-González, J. and Lacal-Arántegui, R. 2016. Technological evolution of onshore wind turbines: A market-based analysis. Wind Energy, 19(12), 2171–2187.
  8. Lu, M.-S., Chang, C.-L., Lee, W.-J., and Wang, L. 2009. Combining the wind power generation system with energy storage equipment. IEEE Transactions on Industry Applications, 45(2), 2019-2115.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Yenilenebilir Enerji Sistemleri

Bölüm

Derleme

Yayımlanma Tarihi

22 Aralık 2025

Gönderilme Tarihi

25 Haziran 2025

Kabul Tarihi

17 Aralık 2025

Yayımlandığı Sayı

Yıl 2025 Cilt: 11 Sayı: 1

Kaynak Göster

APA
Midilli, E. (2025). Applications of artificial intelligence methods in renewable energy systems. International Journal of Energy Applications and Technologies, 11(1), 86-99. https://doi.org/10.31593/ijeat.1727157
AMA
1.Midilli E. Applications of artificial intelligence methods in renewable energy systems. International Journal of Energy Applications and Technologies. 2025;11(1):86-99. doi:10.31593/ijeat.1727157
Chicago
Midilli, Ervanur. 2025. “Applications of artificial intelligence methods in renewable energy systems”. International Journal of Energy Applications and Technologies 11 (1): 86-99. https://doi.org/10.31593/ijeat.1727157.
EndNote
Midilli E (01 Aralık 2025) Applications of artificial intelligence methods in renewable energy systems. International Journal of Energy Applications and Technologies 11 1 86–99.
IEEE
[1]E. Midilli, “Applications of artificial intelligence methods in renewable energy systems”, International Journal of Energy Applications and Technologies, c. 11, sy 1, ss. 86–99, Ara. 2025, doi: 10.31593/ijeat.1727157.
ISNAD
Midilli, Ervanur. “Applications of artificial intelligence methods in renewable energy systems”. International Journal of Energy Applications and Technologies 11/1 (01 Aralık 2025): 86-99. https://doi.org/10.31593/ijeat.1727157.
JAMA
1.Midilli E. Applications of artificial intelligence methods in renewable energy systems. International Journal of Energy Applications and Technologies. 2025;11:86–99.
MLA
Midilli, Ervanur. “Applications of artificial intelligence methods in renewable energy systems”. International Journal of Energy Applications and Technologies, c. 11, sy 1, Aralık 2025, ss. 86-99, doi:10.31593/ijeat.1727157.
Vancouver
1.Ervanur Midilli. Applications of artificial intelligence methods in renewable energy systems. International Journal of Energy Applications and Technologies. 01 Aralık 2025;11(1):86-99. doi:10.31593/ijeat.1727157