Back to Search
Start Over
Review of application of AI techniques to Solar Tower Systems
- Source :
- Solar Energy. 224:500-515
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
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.
- Subjects :
- Optimization
Artificial intelligence
Computer and Information Sciences
Computer science
020209 energy
Metaheuristics
02 engineering and technology
7. Clean energy
GeneralLiterature_MISCELLANEOUS
Energy storage
Solar tower
0202 electrical engineering, electronic engineering, information engineering
General Materials Science
Central receiver systems
Solar towers
Artificial neural networks
Renewable Energy, Sustainability and the Environment
Concentrating solar thermal
021001 nanoscience & nanotechnology
Energy sector
Renewable energy system
Systems engineering
Key (cryptography)
State (computer science)
Natural Sciences
0210 nano-technology
Energy (signal processing)
Efficient energy use
Subjects
Details
- ISSN :
- 0038092X
- Volume :
- 224
- Database :
- OpenAIRE
- Journal :
- Solar Energy
- Accession number :
- edsair.doi.dedup.....16763dbb0a7c38f4deaaa96915ccac99
- Full Text :
- https://doi.org/10.1016/j.solener.2021.06.009