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Navigating the Nexus of Artificial Intelligence and Renewable Energy for the Advancement of Sustainable Development Goals

Author

Listed:
  • Raghu Raman

    (Amrita School of Business, Amrita Vishwa Vidyapeetham, Amritapuri 690525, Kollam, India)

  • Sangeetha Gunasekar

    (Amrita School of Business, Amrita Vishwa Vidyapeetham, Coimbatore 641112, Tamil Nadu, India)

  • Deepa Kaliyaperumal

    (Department of Electrical and Electronics Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Bengaluru 560035, Karnataka, India)

  • Prema Nedungadi

    (Amrita School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri 690525, Kollam, India)

Abstract

The integration of artificial intelligence (AI) into renewable energy and sustainability represents a transformative approach toward achieving sustainable development goals (SDGs), especially SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 13 (Climate Action). This study utilized the PRISMA framework to conduct a systematic review, focusing on the role of AI in renewable energy and sustainable development. This research utilized Scopus’s curated AI research area, which employs text mining to refine AI concepts into unique keywords. Further refinement via the All Science Journals Classification system and SDG-mapping filters narrowed the focus to publications relevant to renewable energy and SDGs. By employing the BERTopic modeling approach, our study identifies major topics, such as enhancing wind speed forecasts, performance analysis of fuel cells, energy management in elective vehicles, solar irradiance prediction, optimizing biofuel production, and improving energy efficiency in buildings. AI-driven models offer promising solutions to address the dynamic challenges of sustainable energy. Insights from academia-industry collaborations indicate that such partnerships significantly accelerate sustainable-energy transitions, with a focus on AI-driven energy storage, grid management, and renewable-energy forecasting. A global consensus on the critical role of investing in technology-driven solutions for energy sustainability was underscored by the relationship between funding data and global R&D spending patterns. This study serves as a resource for practitioners to harness AI technologies for renewable energy, where for example, AI’s accurate wind speed predictions can increase wind farm efficiency, highlighting the necessity of innovation and collaboration for sustainable development.

Suggested Citation

  • Raghu Raman & Sangeetha Gunasekar & Deepa Kaliyaperumal & Prema Nedungadi, 2024. "Navigating the Nexus of Artificial Intelligence and Renewable Energy for the Advancement of Sustainable Development Goals," Sustainability, MDPI, vol. 16(21), pages 1-25, October.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:21:p:9144-:d:1503782
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    2. Hafize Nurgul Durmus Senyapar & Ramazan Bayindir, 2025. "The Energy Hunger Paradox of Artificial Intelligence: End of Clean Energy or Magic Wand for Sustainability?," Sustainability, MDPI, vol. 17(7), pages 1-32, March.
    3. Shuang Peng & Qiao Lin & Yangfen Chen, 2025. "Strengthening Food Security Within the Sustainable Development Goals Framework: A Study Based on Bibliometric Analysis and BERTopic Mining," Sustainable Development, John Wiley & Sons, Ltd., vol. 33(6), pages 8431-8448, December.
    4. Di Chiacchio, Laura & Al-Khateeb, Haider & Butt, Usman & Yussof, Salman, 2026. "AI legitimacy in energy: A model to improve corporate narratives on sustainability and responsibility," Technological Forecasting and Social Change, Elsevier, vol. 222(C).
    5. Rizwana Yasmeen & Rui Tao, 2026. "Leveraging energy-sector artificial intelligence to enhance energy security and achieve sustainable development goals," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 13(1), pages 1-23, December.
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