Coupling physical and machine learning models: case study of a single-family house

Abstract

Future intelligent and integrated energy systems must have a high degree of flexibility and efficiency to ensure reliable and sustainable operation. Along with the rapid expansion of renewable energy, this degree of flexibility and efficiency can be achieved by overcoming the clear separation between different sectors and by increasing connectivity and the associated data availability through the integration of sensors and edge/fog computing. All of these developments drive the transition from towards so-called Cyber-Physical Energy Systems . The Cyber technologies (sensors, edge/fog computing, IoT networks, etc.) are able to monitor the physical systems, to enable communication between different subsystems and to control them. The emergence of Cyber-Physical Systems poses new challenges for traditional modelling and simulation approaches.