Manuscript Topics

Artificial intelligence (AI) has received significant attention in recent years from research communities and the energy industry. Among the most diffuse AI methods used in the field of renewable energy systems, storage systems and high-efficient technologies for building air conditioning, artificial neural networks (ANNs) and other types of learning techniques find application in all fields since they represent mathematical models of AI capable of learning and solving complex problems very accurately. They are based on mechanisms similar to learning and are made up of a network of artificial neurons that simulate the behaviour of biological neurons.

The Special Issue aims to collect research that combines artificial intelligence algorithms and renewable energy system models to create useful, reliable, accurate and quick tools for decision-making and real-time processes to make decisions regarding the management of energy flows in the network and for the prediction of the renewable energy produced in any period in alternative to the classical simulation methodologies available in the literature.

The analysis expected in this special issue aims to propose user-friendly tools with the advantages of the reduction of input data required and no need of required high expertise to use transient simulation software that in many cases requires an expensive license to be used.

In particular, the research papers related to AI techniques should aim but not be limited to:

• photovoltaic, wind, geothermal, heat pumps and building performance evaluation;
• optimization and simulation of renewable and building systems;
• thermal and electrical storage systems analysis;
• technical, economic and environmental tool development;
• reviews on the topic.

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