Noise Amplitude in Ambient PMU Data and its Impact on Load Models Identification

Authors

Keywords:

Ambient PMU Data, Load Modeling, Noise, PMU Noise, PMU, ZIP Load Model

Abstract

A current trend in load modeling topic is to take advantage of ambient data from Phasor Measurement Units (PMU) to estimate the parameters of load models. In this context, the estimation algorithms or methodologies that are proposed or investigated need to be evaluated in a controlled environment, where, among other things, synthetic PMU measurements obtained from simulations are used. These synthetic measurements require the addition of noise to be like the real ones. The problem found in the literature is the large difference in noise magnitudes used by the authors in their research. These magnitudes in several cases are inconsistent with each other and even seem to be exaggerated. It is for this reason that the present work determines the noise contained in the ambient data reported by PMU. The reliability of the results of this work is based, among other things, on the use of real PMU measurements, located in two different countries, with diverse reporting rates, and located at high, medium, and low voltage. Moreover, this work quantifies the impact that noise has on load modeling with ambient PMU data. In conclusion, the main results of this work are two. The first one covers the noise magnitudes contained in ambient PMU data. The second one demonstrates that noise has a significant and negative impact on load modeling.

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Author Biographies

Joffre Remigio Constante Segura, Universidad Técnica de Cotopaxi

Joffre R. Constante is Electrical Engineering from Universidad Politécnica Salesiana (2013), Master in Energy Efficiency from Escuela Politécnica Nacional (2016), and PhD candidate in Electrical Engineering from Universidad Nacional de San Juan - Argentina. He has professional experience as: i) Technical Analyst at Instituto de Investigación Geológico y Energético (IIGE); ii) Technical Analyst of tariffs at Agencia de Regulación y Control de Energía y Recursos Naturales no Renovables (ARCERNNR), and iii) Technical Research Assistant at Operador Nacional de Electricidad from Ecuador (CENACE). He currently works as professor at  Universidad Tecnica de Cotopaxi in the field of Electrical Power Systems.

Graciela Colomé, Instituto de Energía Eléctrica UNSJ-CONICET

D. Graciela Colomé is PhD in Electrical Engineering, graduated in 2009, from the Universidad Nacional de San Juan (UNSJ), Argentina. Professor and consultant at the Institute of Electric Energy (IEE), UNSJ – CONICET. Coordinator of the Electrical Engineering career (2011-2018) and director of the Graduate Studies Department of the School of Engineering (2016-2021). She is currently director of research and technology transfer projects. Her main fields of research are: modeling, simulation, supervision, stability, and control of electrical power systems.

Diego Echeverría, Operador Nacional de Electricidad CENACE

Diego Echeverria received his degree in Electrical Engineering from Escuela Politécnica Nacional from Quito, in 2006. In 2021, he obtained his PhD degree in Electrical Engineering from the Universidad Nacional de San Juan - Argentina. He currently works at the Operador Nacional de Electricidad from Ecuador (CENACE) and holds the position of National Manager of Technical Development. Additionally, he is a part-time Professor of the Master's Degree in Electricity at the Universidad Técnica de Copotaxi, and at the Pontificia Universidad Católica from Ecuador, Esmeraldas. His areas of interest are: Real Time Power System Stability, PMU's Synchrophasor Measurement Systems, Power System Reliability and Power System Emergency Control.

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Published

2024-07-31

How to Cite

Constante Segura, J. R., Colomé, G., & Echeverría, D. (2024). Noise Amplitude in Ambient PMU Data and its Impact on Load Models Identification. IEEE Latin America Transactions, 22(8), 678–685. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/8878

Issue

Section

Electric Energy