Energy consumption optimisation through machine learning: a strategic approach to sustainable procurement in smart grids and buildings: a bibliometric analysis

Saravanan Thirunavukkarasu, K. Kavitha, T. Sandeep, P. Shalini Reddy, R. Madhavi and L. Dillipriya

International Journal of Procurement Management, 2026, vol. 26, issue 2, 129-159

Abstract: This paper addresses whether machine learning, optimising energy intake in smart grids and smart buildings, improves efficiency, stability, and sustainability of energy use. A bibliometric analysis was performed to identify the principal contributors, thematic patterns, and research gaps within the domain. Techniques of artificial neural networks and reinforcement learning support real-time decisions by integrating renewable sources in maintaining a stable energy supply. Our results underscore the disruptive potential of ML in reducing wasted energy, shifting the shape of demand, and achieving more effective, cost-effective, resilient grids for energy. It unravels the immense promise that ML holds in transforming energy-efficient solutions worldwide.

Keywords: energy optimisation; machine learning; smart grids; smart buildings; energy efficiency; sustainability; renewable energy integration; demand response; artificial intelligence; predictive energy management; bibliometric analysis; real-time decision making. (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.inderscience.com/link.php?id=154962 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpman:v:26:y:2026:i:2:p:129-159

Access Statistics for this article

More articles in International Journal of Procurement Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().