Review of application of AI techniques to Solar Tower Systems - Milidonis, Kypros; Blanco, Manuel J.; Grigoriev, Victor; Panagiotou, Constantinos F.; Bonanos, Aristides M.; Constantinou, Marios; Pye, John; Asselineau, Charles Alexis (My University, 2021)
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.
Keywords: Concentrating solar thermal; Solar towers; Central receiver systems; Artificial intelligence; Optimization; Metaheuristics; Artificial neural networks