Coordination of Damping Controllers: A Data-Informed Approach for Adaptability

This work proposes a data-informed approach for an adaptable coordination of damping controllers. The novel concept of coordination is based on minimizing the Total Action, a single metric that measures the system's dynamic response post-disturbance. This is a performance measure based on the p...

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Bibliographic Details
Published in:arXiv.org 2023-12
Main Authors: Zelaya-Arrazabal, Francisco, Pulgar-Painemal, Hector, Liu, Jingzi, Li, Fangxing, Silva-Saravia, Horacio
Format: Article
Language:English
Subjects:
Controllers
Coordination
Damping
Dynamic response
Learning theory
Synchronous machines
Systems stability
Time lag
Online Access:Get full text
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Summary:This work proposes a data-informed approach for an adaptable coordination of damping controllers. The novel concept of coordination is based on minimizing the Total Action, a single metric that measures the system's dynamic response post-disturbance. This is a performance measure based on the physics of the power system, which encapsulates the oscillation energy related to synchronous generators. Deep learning theory is used to propose a Total Action function approximator, which captures the relationship between the system wide-area measurements, the status of damping controllers, and the conditions of the disturbance. By commissioning the switching status (on/off) of damping controllers in real-time, the oscillation energy is reduced, enhancing the power system stability. The concept is tested in the Western North America Power System (wNAPS) and compared with a model-based approach for the coordination of damping controllers. The data-informed coordination outperforms the model-based approach, demonstrating exceptional adaptability and performance to handle multi-modal events. The proposed scheme shows outstanding reductions in low-frequency oscillations even under various operating conditions, fault locations, and time delay considerations.
ISSN:2331-8422