This Special Issue covers selected topics on the combination of machine learning with research on sustainable energy. Energy systems are transforming worldwide to mitigate carbon emissions and global warming. Machine learning, which is an ideal companion to renewable energy, can facilitate the process of energy sector transformation. Because the major sources of renewable energy, wind and solar, are in their very nature, variable, it is a challenging task for a modern society to depend on these sources. Therefore, there is a growing need for novel concepts enabling their efficient and reliable integration into energy systems. Machine learning can help in various ways by providing accurate predictions of future generation and demand, using optimal control to increase the utilization of renewable energy sources, or monitoring the state of the system. We invite all colleagues to submit an original manuscript with novel research results on this general topic, including, but not limited to, applications of machine learning related to energy system analysis; renewable energy and renewable energy systems; the energy transition; weather data modeling; forecasting of relevant quantities, such as generation, demand, or electricity prices; demand-side management; peer-to-peer energy trading; use of big data in energy research; and other issues relevant to sustainable energy.
Keywords: sustainable energy; machine learning; energy system analysis; future energy scenario; large-scale optimisation; energy informatics; energy transition; environmental sustainability; smart energy markets; artificial intelligence; big data.