Guest editorial: Applications of advanced machine learning and big data techniques in renewable energy-based power grids

In recent years, due to the grid modernizations, high penetration of renewable energies, and using smart sensors in the main structure of the power grids, a large amount of data has been generated that can potentially lead to the complexity of the net-work. This can be a significant issue especially in contingencies conditions, post-natural disasters operation, and cyber/physical attacks which require fast and reliable data processing to preserve grid reliability and resiliency. Furthermore, in the normal condition, the reliability of the power grids is very important,and it can be improved by using the large data of measurements during long-term operation. Therefore, to address these challenges, advanced machine learning-based techniques, as well as big data techniques can provide new solutions to energy systems operation and control.