Dear Colleagues,

Economic development and the comfort-loving nature of human beings in recent years have resulted in increased energy demand. Since energy resources are scarce and should be preserved for future generations, optimizing energy systems is ideal. Still, due to the complexity of integrated energy systems, such a feat is by no means easy. Here is where computer-aided decision-making can be very game-changing in determining the optimum point for supply and demand. The concept of artificial intelligence (AI) and machine learning (ML) was born in the twentieth century to enable computers to simulate humans' learning and decision-making capabilities. Since then, data mining and artificial intelligence have become increasingly essential areas in many different research fields. Naturally, the energy section is one area where artificial intelligence and machine learning can be very beneficial.

With the increase of human society and its vital need for energy, energy systems play an important and decisive role in various sectors such as; residential, industry, and transportation. To accelerate the process and improve the methods of responding to this problem, the use of models and algorithms based on artificial intelligence has become common and mandatory.

In this Special Issue, the interaction between the energy-related areas with ML and how AI can be implemented in these areas will be investigated; identifying the existing network between authors and topics, journals and finally, determining the gaps in which ML should be implemented. Any research or review of AI, ML, and the most common energy-related terms to achieve this goal is welcomed.

This special issue focuses on the use and applications of algorithms and models of ML and DL on energy systems. Also, will be tried to cover more methods and models than previous articles and studies that have been done in this field. Potential topics include, but are not limited to:

·         The various applications of this science in relation to energy systems

·         The main applications and cases in which ML and DL have been used for energy systems

·         Describing ML and its algorithms, and also their application in the field of energy systems

·         Describing DL and its algorithms, and also their application in the field of energy systems

·         Dealing with the parameters and metrics used to evaluate the accuracy and error calculation of algorithms and models used for energy systems

·         Highlighting unexplored areas in the energy section from the ML viewpoint

·         Introducing new research aspects of machine learning in the energy field

·         Looking at the major applications of ML and DL in energy systems

·         Introducing performance evaluation metrics for the results predicted by the models for energy systems

We look forward to your contribution.