Back to Search Start Over

A data-driven online approach for detection and localization of forced oscillation in wind turbine integrated power system.

Authors :
Abhinav, Kumar
Rai, Piyush
Prakash, Abhineet
Parida, S.K.
Source :
Electric Power Systems Research. Aug2024, Vol. 233, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

This article introduces an innovative approach for online detection and localization of forced oscillation (FO) in power systems with significant integration of wind turbine generation (WTG). The synergistic combination of Multichannel Prony analysis with Periodogram and dissipating energy flow (DEF) approach is proposed in this paper to overcome the challenges inherent in detecting FO amidst the complexities introduced by WTG integration. An adaptive version of multichannel Prony analysis is proposed in this paper that dynamically estimates Prony's system order via the recursive process. It estimates the frequency and damping ratio of all oscillatory modes, which is used to identify low damping modes that are potentially attributed to FO. Leveraging this information, the proposed method enhances both FO detection and source localization capabilities. The proposed method is verified on measurements taken from IEEE benchmark 4-machine, 11-bus system and 10-machine, 39-bus system with high wind energy penetration. Comprehensive testing demonstrates the proposed approach's effectiveness across various FO scenarios, including governor valve malfunction, exciter malfunction, and cyclic loads. Furthermore, the methodology is evaluated under resonant conditions and scenarios involving the simultaneous identification of multiple disturbances. • Detection & source location in WTG integrated power system. • MDMMO for dynamic estimation of Prony model order. • OFDM using Periodogram technique. • OFSLM using dissipating energy flow method. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03787796
Volume :
233
Database :
Academic Search Index
Journal :
Electric Power Systems Research
Publication Type :
Academic Journal
Accession number :
177880142
Full Text :
https://doi.org/10.1016/j.epsr.2024.110512