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

Abstract:
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.