The Machine Learning for Sustainable Power Systems (ML4SPS) workshop aims to bring together researchers in the fields of machine learning and energy systems.

Energy systems around the world are facing the challenge of integrating massive amounts of new renewable energy production. Unlike traditional energy production methods, new renewables are highly variable, decentralized and only partially predictable. At the same time, new consumption patterns and additional uses of electricity are emerging, such as self-consumption, heat pumps or electric vehicles. These new consumers increase the complexity of the grids in terms of monitoring and control, but also allow for new flexibility in the future. The use of machine learning methods can help to exploit these new flexibilities to overcome the increasing complexity of modern energy systems. To this end, machine learning can take advantage of technological advances such as smart meters and novel communication devices.

Consequently, ML4SPS aims to bring together researchers and practitioners to share their knowledge and experience in the field of renewable energy systems, grid management and machine learning. The workshop itself will be organised by experts in the field of renewable energy systems and machine learning who will share their knowledge and experience with the participants. The workshop will be interactive and will include the presentation of the submitted papers, a poster session and two keynote speakers from the field of machine learning in energy systems.