Real-Time Flexibility Allocation among Distributed Energy Resources: A Digital Twin-Driven Dynamic Optimization Approach

The transition towards decentralized energy systems, driven by the integration of distributed energy resources (DERs), presents significant challenges for grid flexibility and operational planning. In this paper, a novel digital twin-driven optimization methodology is introduced for real-time flexibility provision in decentralized energy cells. By using dynamic simulation models, the proposed approach disaggregates centralized load requests into component-specific signals tailored to Electric Heat Pumps (EHPs) and Battery Electric Storage Systems (BESSs). A two-stage framework
is proposed: a preparation phase, where dynamic system behaviors are analyzed and linearized to create simplified gray-box models for optimization, and a provision phase, where optimized control signals are generated to meet realtime flexibility demands. A case study demonstrates the effectiveness of the methodology, highlighting the capability to manage diverse DERs under varying conditions. The results underscore the potential of digital twin-driven frameworks to enhance grid stability and support the evolving needs of decentralized energy systems.

DDC Class

600: Technology

Options

Real-Time Flexibility Allocation among Distributed Energy Resources: A Digital Twin-Driven Dynamic Optimization Approach