Decentralized Approach to Detect and Eliminate Flapping Phenomena due to Flexible Resources

TL;DR

This paper introduces a decentralized method for power systems to autonomously detect and mitigate flapping caused by discrete devices, improving stability through local autocorrelation analysis and device-specific mitigation.

Contribution

It proposes a novel decentralized autocorrelation-based detection and mitigation approach for flapping phenomena in power systems involving flexible resources.

Findings

Robust detection of sustained oscillations versus damping.

Devices can independently identify and respond to problematic oscillations.

Method effective for both discrete and continuous operation devices.

Abstract

This paper presents a decentralized methodology for detecting and mitigating flapping phenomena in power systems, primarily caused by the operation of discrete devices. The proposed approach applies moving-window autocorrelation to local measurements, enabling each device to autonomously identify sustained oscillations. Upon detection, a probabilistic, device-specific mitigation strategy is executed. Flexible demand resources (DFRs), under-load tap changers (ULTCs), and automatic voltage regulators (AVRs) are utilised to illustrate the performance of the proposed approach to both discrete and continuous-operation devices. Results show that the proposed method is robust and properly distinguishes damped oscillations from persistent flapping, allowing devices to independently recognize problematic operating scenarios and implement corrective actions accordingly.