Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/22936
Title: | Review of application of AI techniques to Solar Tower Systems | Authors: | Milidonis, Kypros Blanco, Manuel J. Grigoriev, Victor Panagiotou, Constantinos F. Bonanos, Aristides M. Constantinou, Marios Pye, John Asselineau, Charles Alexis |
Major Field of Science: | Natural Sciences | Field Category: | Computer and Information Sciences | Keywords: | Concentrating solar thermal;Solar towers;Central receiver systems;Artificial intelligence;Optimization;Metaheuristics;Artificial neural networks | Issue Date: | Aug-2021 | Source: | Solar Energy, 2021, vol. 224, pp. 500-515 | Volume: | 224 | Start page: | 500 | End page: | 515 | Journal: | Solar Energy | Abstract: | Artificial Intelligence (AI) is increasingly playing a significant role in the design and optimization of renewable energy systems. Many AI approaches and technologies are already widely deployed in the energy sector in applications such as generation forecasting, energy efficiency monitoring, energy storage, and overall design of energy systems. This paper provides a review of the applications of key AI techniques on the analysis, design, optimization, control, operation, and maintenance of Solar Tower systems, one of the most important types of Concentrating Solar Thermal (CST) systems. First, key AI techniques are briefly described and relevant examples of their application to CST systems in general are provided. Subsequently, a detailed review of how these AI techniques are being used to advance the state of the art of solar tower systems is presented. The review is structured around the different subsystems of a solar tower system. | URI: | https://hdl.handle.net/20.500.14279/22936 | ISSN: | 0038092X | DOI: | 10.1016/j.solener.2021.06.009 | Rights: | © Elsevier | Type: | Article | Affiliation : | The Cyprus Institute Australian National University Cyprus University of Technology |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
CORE Recommender
SCOPUSTM
Citations
20
checked on Mar 14, 2024
WEB OF SCIENCETM
Citations
17
Last Week
0
0
Last month
2
2
checked on Oct 29, 2023
Page view(s)
334
Last Week
1
1
Last month
9
9
checked on Nov 21, 2024
Google ScholarTM
Check
Altmetric
This item is licensed under a Creative Commons License