The introduction of Phasor Measurement Units (PUMs) represented a major technical breakthrough, as they enabled measuring phasor, frequency and rate of change of frequency (ROCOF) in remote nodes, refereed to a synchronized timescale. This allows taking frequent snapshots of the monitored network, and following possible oscillations. Power grids are now experiencing deep changes, leading to faster dynamics. Moreover, PMUs were originally intended to be installed in transmission systems, but in recent years the extension of synchronized measurements to distribution grids is under study. In this context, phasor, frequency and ROCOF have to be measured under more challenging conditions. This triggered the research for high performance estimation algorithms; many of them can be found in the scientific literature, based on multifold approaches. This thesis explores the application of an advanced PMU measurement algorithm, called Compressed Sensing Weighted Total Frequency Modulation (CS-WTFM) method and its three-phase extension, CS-3WTFM. The primary objective is to assess the advantages of the three-phase approach over the single-phase approach under various static and dynamic test conditions for syncrophasor, frequency and ROCOF estimation. Additionally, other considerations are discussed to demonstrate potential improvements in the performance of the CS-3WTFM method. The results demonstrate that the CS-3WTFM method consistently outperforms the CSWTFM method across key performance parameters, such as Total Vector Error (TVE), Frequency Error (FE), and Rate of Change of Frequency Error (RFE). The three-phase approach shows significant improvements in accuracy and robustness, particularly in challenging conditions where the single-phase approach struggles. The study also highlights the sensitivity of both methods to the coherence of the dictionary and the impact of different weighting functions on overall performance. This work not only confirms the superiority of the CS-3WTFM method for power system applications but also opens up avenues for future research, including real-time implementation, extension to even more challenging scenarios, and the development of adaptive weighting techniques.
L’introduzione delle Phasor Measurement Units (PMUs) ha rappresentato un importante progresso tecnico, poiché peremettono di misurare fasori, frequenza e rapidità della variazione della frequenza (rate of change of frequency,ROCOF) in nodi geograficamente distanti, riferiti a una scala temporale condivisa e sincronizzata. Questo consente di ricostruire l’evluzione nel tempo dello stato della rete, e di inseguire possibili fenomeni oscillatori. Le reti elettriche stanno attraversando profondi cambiamenti, che determinano un comportamento caratterizzato da dinamiche più rapide. Inoltre, le PMUs erano originariamente destinate ad essere installate nei sistemi di trasmissione, ma negli ultimi anni è allo studio l’applicazione delle misure sincronizzate alle reti di distribuzione. In questo contesto, fasori, frequenza e ROCOF devono essere misurati in condizioni più impegnative. Ciò ha stimolato la ricerca di algoritmi di stima ad alte prestazioni, molti dei quali si trovano nella letteratura scientifica, basati su molteplici approcci. Questa tesi esplora l’applicazione di un algoritmo avanzato per PMU, chiamato Compressive Sensing Weighted Taylor-Fourier Multifrequency (CS-WTFM) e della sua estensione al caso trifase, CS-3WTFM. L’obiettivo principale è valutare i vantaggi ottenuti grazie all’adozione dell’approccio trifase (CS-3WTFM) rispetto alla versione monofase (CS-WTFM) in varie condizioni di test, sia statiche sia dinamiche, nella stima di fasore, frequenza e ROCOF. Inoltre, si discuteranno come è possibile ulteriormente migliorare le prestazioni ottenute con il metodo CS-3WTFM. I risultati dimostrano che le prestazioni ottenute mediante il metodo CS-3WTFM (valutate in termini di Total Vector Error, TVE, di Frequency Error, FE e di ROCOF Error, RFE) sono sempre superiori. L’approccio trifase mostra miglioramenti significativi in termini di accuratezza e robustezza della stima, in particolare nelle condizioni più difficili. Lo studio evidenzia anche la sensibilità di entrambi i metodi alla coerenza del dizionario e l’impatto delle diverse funzioni di ponderazione sulle prestazioni complessive. Questo lavoro non solo conferma la superiorità del metodo CS-3WTFM per le applicazioni nei sistemi elettrici, ma apre anche nuove strade per future ricerche, tra cui l’implementazione in tempo reale, l’estensione a scenari ancora più impegnativi e lo sviluppo di tecniche di ponderazione adattive.
Three-phase compressive sensing Taylor-Fourier approach for syncrophasor estimation
PLATA PINZON, JAIRO ANDRES
2023/2024
Abstract
The introduction of Phasor Measurement Units (PUMs) represented a major technical breakthrough, as they enabled measuring phasor, frequency and rate of change of frequency (ROCOF) in remote nodes, refereed to a synchronized timescale. This allows taking frequent snapshots of the monitored network, and following possible oscillations. Power grids are now experiencing deep changes, leading to faster dynamics. Moreover, PMUs were originally intended to be installed in transmission systems, but in recent years the extension of synchronized measurements to distribution grids is under study. In this context, phasor, frequency and ROCOF have to be measured under more challenging conditions. This triggered the research for high performance estimation algorithms; many of them can be found in the scientific literature, based on multifold approaches. This thesis explores the application of an advanced PMU measurement algorithm, called Compressed Sensing Weighted Total Frequency Modulation (CS-WTFM) method and its three-phase extension, CS-3WTFM. The primary objective is to assess the advantages of the three-phase approach over the single-phase approach under various static and dynamic test conditions for syncrophasor, frequency and ROCOF estimation. Additionally, other considerations are discussed to demonstrate potential improvements in the performance of the CS-3WTFM method. The results demonstrate that the CS-3WTFM method consistently outperforms the CSWTFM method across key performance parameters, such as Total Vector Error (TVE), Frequency Error (FE), and Rate of Change of Frequency Error (RFE). The three-phase approach shows significant improvements in accuracy and robustness, particularly in challenging conditions where the single-phase approach struggles. The study also highlights the sensitivity of both methods to the coherence of the dictionary and the impact of different weighting functions on overall performance. This work not only confirms the superiority of the CS-3WTFM method for power system applications but also opens up avenues for future research, including real-time implementation, extension to even more challenging scenarios, and the development of adaptive weighting techniques.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/226951