Abstract
Linked to the 3D challenges of the energy transition (decarbonisation, decentralization and digitization) are the integrated planning and operation of distribution networks and supply infrastructure. Increasing shares of renewable energies are forcing the use of new flexibilities for maintaining the resilience and stability of the power grid. Important components of such flexibility options are the use of multi-commodity systems (sector coupling) and Smart DSM. Activating the flexibility of smart demand side applications is key for a sustainable, reliable energy system. In FUSE (FUture Smart Energy), a German-Finnish R&D project, AI-based DSM methods are developed to increase the resilience of distribution grids, considering multi-energy applications and local network conditions. The methods are evaluated in a Smart Grid laboratory, principles are integrated into an optimization framework for planning system design and operation. The project is ongoing, hence results are subject to update. The DSM methods are based on automated generation of soft-control signals enabling dynamic, decentralized control of consumers based on energy availability. Consumers include either buffer storage or process flexibility, or both, with the latter being transformed into the former. First results of the controller testing in the power hardware/software Smart Grid laboratory are promising, with further investigation needed.
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