• Jul 15, 2022 News!We are delighted to welcome Prof. Hao Luo to be the Editor-in-Chief!
  • Jul 15, 2022 News!We are delighted to welcome Prof. YOU Jia Jane to be the Associate Editor-in-Chief!
  • Jul 20, 2022 News!We are delighted to welcome Prof. Abdul Qayyum Khan to the Editorial Board!
General Information
    • Abbreviated Title: J. Adv. Artif. Intell.
    • E-ISSN: 2972-4503
    • Frequency: Biannually
    • DOI: 10.18178/JAAI
    • Editor-in-Chief: Prof. Dr.-Ing. Hao Luo
    • Executive Editor: Ms. Cherry L. Chen
    • E-mail: jaai@triples.sg
Editor-in-chief

Prof. Dr.-Ing. Hao Luo
Harbin Institute of Technology, Harbin, China
 
It is my honor to be the editor-in-chief of JAAI. The journal publishes good papers in the field of artificial intelligence. Hopefully, JAAI will become a recognized journal among the readers in the filed of artificial intelligence.

 
JAAI 2024 Vol.2(1): 1-26
DOI: 10.18178/JAAI.2024.2.1.1-26

Contribution of ChatGPT and Other Generative Artificial Intelligence (AI) in Renewable and Sustainable Energy

Nitin Liladhar Rane
Vivekanand Education Society's College of Architecture (VESCOA), Mumbai, India.
Email: nitinrane33@gmail.com (N.L.R.)
Manuscript submitted November 21, 2023; accepted November 28, 2023; published January 3, 2024
Abstract—In the dynamic field of renewable and sustainable energy, Artificial Intelligence (AI) integration has emerged as a crucial catalyst for enhancing efficiency, cost reduction, and addressing multifaceted challenges. This work delves into the performance and contributions of ChatGPT, a prominent representative of large AI language models, within the context of renewable and sustainable energy. The research endeavors to explore ChatGPT's efficacy and role across a diverse spectrum of renewable energy aspects, spanning solar energy, wind energy, biomass energy, hydropower, geothermal energy, energy storage, grid integration, energy efficiency, materials science, policy, economics, environmental impact, energy accessibility, and advanced biofuels. The investigation commences with solar energy, where ChatGPT showcases impressive capabilities in data analysis, modeling, and forecasting. It facilitates solar panel placement optimization, energy production prediction, and overall efficiency enhancement. Likewise, in the realm of wind energy, ChatGPT proves invaluable for tasks such as wind turbine control, maintenance scheduling, and wind speed prediction. In biomass energy, ChatGPT aids in feedstock selection, process optimization, and emissions reduction. In the hydropower sector, it supports reservoir management and river flow prediction, thereby optimizing energy output. Geothermal energy benefits from ChatGPT's geological analysis, reservoir modeling, and exploration strategies. Energy storage solutions are indispensable for grid stability, and ChatGPT contributes to the advancement of cutting-edge battery technologies, augmenting energy storage capacity and lifespan. Furthermore, ChatGPT's insights foster the evolution of smart grids, ensuring efficient energy distribution and effective demand management. Additionally, ChatGPT provides invaluable insights into policy and economics, offering recommendations for incentivizing the adoption of renewable energy sources while considering environmental impact and sustainability. It also contributes to the advancement of tidal and wave energy technologies, as well as the development of advanced biofuels. The outcomes of this research paper underscore the potential of AI and ChatGPT in shaping the future of renewable energy, expediting progress toward a sustainable energy ecosystem.

keywords—ChatGPT, artificial intelligence, generative AI, large language models, renewable energy, sustainable energy

Cite: Nitin Liladhar Rane, "Contribution of ChatGPT and Other Generative Artificial Intelligence (AI) in Renewable and Sustainable Energy," Journal of Advances in Artificial Intelligence vol. 2, no. 1, pp. 1-26, 2024.

Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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