ICEERE2022

Renewable energy systems have newly gained popularity due to climate protection and sustainability issues. However, the intermittency caused by renewable energy sources disrupts the balance of the energy system and can put considerable strain on electrical systems. Such systems should be carefully protected, optimized and controlled to keep them safe and stable. Machine learning methods were widely applied to solve complex problems in many sectors, and recently in renewable power generation systems.
This session aims to present the most recent research, new concepts and latest results on the application of machine learning methods to address problems in renewable energy systems (solar energy, wind energy, biomass, and other).
This session aims to present the most recent research, new concepts and latest results on the application of machine learning methods to address problems in renewable energy systems (solar energy, wind energy, biomass, and other). Topics of interest for the special issue include, but are not limited to, the following:

• Machine for renewable energy systems (solar energy, wind energy, biomass, and other);
• Machine learning and Deep Learning methods for solar radiation forecasting;
• Machine learning for Energy consumption prediction in Green Buildings using Machine Learning;
• Intelligent Condition Monitoring for Solar and Wind Energy Systems;
• Artificial Intelligence Methods for Hybrid Energy System;
• Real-time Decision Making for Renewable System;
• Supervised Machine Learning for Wind Energy Systems.