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All Journal International Transactions on Artificial Intelligence (ITALIC)
Hajra Rasmita Ngemba
Tadulako University
Computer Science & IT Control & Systems Engineering Library & Information Science

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Leveraging AI for Superior Efficiency in Energy Use and Development of Renewable Resources such as Solar Energy, Wind, and Bioenergy Umi Rusilowati; Hajra Rasmita Ngemba; Rio Wahyudin Anugrah; Anandha Fitriani; Eka Dian Astuti
International Transactions on Artificial Intelligence Vol. 2 No. 2 (2024): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v2i2.537

Abstract

Energy efficiency and the development of renewable resources are crucial issues in addressing the global energy crisis and climate change. This research explores the role of artificial intelligence (AI) in increasing energy efficiency and optimizing the development of renewable resources, such as solar energy, wind, and bioenergy. By using a mixed-methods approach that combines qualitative and quantitative methods, this research identifies concrete applications of AI in various renewable energy sectors. The results demonstrate that AI can significantly improve operational efficiency and reduce energy waste. Examples include optimizing solar panel placement, predictive maintenance of wind turbines, and optimizing fermentation processes in biogas production. The implementation of AI in renewable energy not only enhances efficiency but also reduces costs and supports sustainability. This research contributes to the field of energy efficiency and AI technologies by providing empirical evidence of the benefits of AI in the renewable energy sector. It is recommended that governments and the energy industry widely adopt AI, invest in technology and workforce training, and strengthen collaboration between the energy, technology, and academic sectors to develop innovative and applicable AI solutions. Further research should conduct broader and more comprehensive studies, including analysis of the long-term costs and benefits of AI implementation, as well as the integration of AI technology with existing energy management systems.
Co-Authors Anandha Fitriani Eka Dian Astuti Rio Wahyudin Anugrah Rusilowati, Umi