Validating Algorithms for Flexible Load Control in a Smart Grid Laboratory Environment

Abstract

The increasing penetration of renewables in distribution networks calls for the development of new technologies allowing for secure and stable operation of the power grid. Smart DSM and sector coupling are options with growing potential to integrate flexibilities into the grid, supporting decarbonization, decentralization, and digitization. Advancing the available flexibility of smart demand side applications, the energy system will be enabled to operate in a more sustainable and reliable way. The German-Finnish R&D project FUSE (FUture Smart Energy) attempts to increase the resilience of distribution grids by developing and investigating methods based on Artificial Intelligence (AI) for integrated planning and operation of multi-energy applications, supply infrastructure and local network conditions. For performance testing and assessment, the applied methods are implemented in a Smart Grid laboratory integrating process and/or buffer storage flexibility. An optimization framework is established to find the optimum system design and operation of resources. With the developed methods soft-control signals are generated automatically for available resources, enabling dynamic and decentralized control of demand side applications, while preserving independence of stakeholders. First performance testing runs show promising results. Ongoing development activities include improvement of system forecasts and determination of dynamically changing flexibility levels of participating devices.