Data-driven Forced Oscillation Localization using Inferred Impulse Responses

Fuente: arXiv
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Main Authors: Liu, Shaohui, Zhu, Hao, Kekatos, Vassilis
Format: Preprint
Published: 2023
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author Liu, Shaohui
Zhu, Hao
Kekatos, Vassilis
author_facet Liu, Shaohui
Zhu, Hao
Kekatos, Vassilis
contents Poorly damped oscillations pose threats to the stability and reliability of interconnected power systems. In this work, we propose a comprehensive data-driven framework for inferring the sources of forced oscillation (FO) using solely synchrophasor measurements. During normal grid operations, fast-rate ambient data are collected to recover the impulse responses in the small-signal regime, without requiring the system model. When FO events occur, the source is estimated based on the frequency domain analysis by fitting the least-squares (LS) error for the FO data using the impulse responses recovered previously. Although the proposed framework is purely data-driven, the result has been established theoretically via model-based analysis of linearized dynamics under a few realistic assumptions. Numerical validations demonstrate its applicability to realistic power systems including nonlinear, higher-order dynamics with control effects using the IEEE 68-bus system, and the 240-bus system from the IEEE-NASPI FO source location contest. The generalizability of the proposed methodology has been validated using different types of measurements and partial sensor coverage conditions.
format Preprint
id arxiv_https___arxiv_org_abs_2310_01656
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Data-driven Forced Oscillation Localization using Inferred Impulse Responses
Liu, Shaohui
Zhu, Hao
Kekatos, Vassilis
Systems and Control
Signal Processing
Poorly damped oscillations pose threats to the stability and reliability of interconnected power systems. In this work, we propose a comprehensive data-driven framework for inferring the sources of forced oscillation (FO) using solely synchrophasor measurements. During normal grid operations, fast-rate ambient data are collected to recover the impulse responses in the small-signal regime, without requiring the system model. When FO events occur, the source is estimated based on the frequency domain analysis by fitting the least-squares (LS) error for the FO data using the impulse responses recovered previously. Although the proposed framework is purely data-driven, the result has been established theoretically via model-based analysis of linearized dynamics under a few realistic assumptions. Numerical validations demonstrate its applicability to realistic power systems including nonlinear, higher-order dynamics with control effects using the IEEE 68-bus system, and the 240-bus system from the IEEE-NASPI FO source location contest. The generalizability of the proposed methodology has been validated using different types of measurements and partial sensor coverage conditions.
title Data-driven Forced Oscillation Localization using Inferred Impulse Responses
topic Systems and Control
Signal Processing
url https://arxiv.org/abs/2310.01656