Coordinated Fast Frequency Regulation in Dynamic Virtual Power Plants via Disturbance Estimation
Saif Ahmad, Seifeddine Ben Elghali, Hafiz Ahmed

TL;DR
This paper presents a decentralized control method for dynamic virtual power plants that combines disturbance estimation and distributed coordination to improve fast frequency regulation in renewable-heavy grids.
Contribution
It introduces a layered control architecture that enables fast local corrections and coordinated imbalance compensation among DVPP nodes, enhancing scalability and efficiency.
Findings
Validated on a 4-bus system with high renewable penetration
Demonstrated improved frequency regulation performance
Showed effective coordination between DVPP nodes
Abstract
In the context of dynamic virtual power plants (DVPPs), the integration of frequency containment reserve (FCR) and fast frequency control (FFC) enabled via local compensation of power imbalance represents a significant advancement in decentralized frequency regulation. However, they still have to cope with the limited power and energy capacities associated with commonly available storage solutions. This work combines a disturbance estimation based decentralized local control with distributed imbalance compensation in the event of local shortfall. The layered architecture facilitates fast local corrections in power setpoints while enabling coordination between neighbouring DVPP nodes to leverage the aggregated capacity, ensuring scalable and efficient operation suitable for renewable-heavy future grids. The proposed approach is validated on an illustrative 4-bus system with a high…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMicrogrid Control and Optimization · Power System Optimization and Stability · Smart Grid Energy Management
