
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
Next-Generation CSP: The Synergy of Nanofluids and Industry 4.0 for Sustainable Solar Energy Management
doi: 10.3390/en18082083
handle: 11584/443013
The growing demand for efficient and sustainable energy solutions underscores the importance of advancing solar energy technologies, particularly Concentrated Solar Power (CSP) systems. This review presents a structured evaluation of two key innovation domains in CSP: the application of nanofluids and the adoption of Industry 4.0 technologies. The first part analyzes experimental and simulation-based studies on nanofluid-enhanced CSP systems, covering four major collector types—parabolic trough, solar power tower, solar dish, and Fresnel reflectors. Nanofluids have been shown to significantly enhance thermal efficiency, with hybrid formulations offering the greatest improvements. The second part examines the role of Industry 4.0 technologies—including artificial intelligence (AI), machine learning (ML), and digital twins (DT)—in improving CSP system monitoring, performance prediction, and operational reliability. Although a few recent studies explore the combined use of nanofluids and Industry 4.0 tools in CSP systems, most research addresses these areas independently. This review identifies this lack of integration as a gap in the current literature. By presenting separate yet complementary analyses, the study offers a comprehensive overview of emerging pathways for CSP optimization. Key research challenges and future directions are highlighted, particularly in nanofluid stability, system cost-efficiency, and digital implementation at scale.
- University of Cagliari Italy
Technology, nanofluids, machine learning, digital twin, T, Industry 4.0, artificial intelligence, nanofluids; concentrated solar power; Industry 4.0; artificial intelligence; digital twin; machine learning, concentrated solar power
Technology, nanofluids, machine learning, digital twin, T, Industry 4.0, artificial intelligence, nanofluids; concentrated solar power; Industry 4.0; artificial intelligence; digital twin; machine learning, concentrated solar power
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).1 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
