Online tracking of sub-transient generator model variables using dynamic phasor measurements

Marchi, Pablo; Messina, Francisco; Vega, Leonardo Rey; Galarza, Cecilia G.

doi:10.1016/j.epsr.2019.106057

Cited by 11 publications

(3 citation statements)

References 15 publications

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“…Using the same criterion as in [28], the measurement vector is composed of the real and imaginary parts of the voltage phasor at the point of connection:…”

Section: Synchronous Generator Genrou Modelmentioning

confidence: 99%

Loss of Excitation Detection in Synchronous Generators Based on Dynamic State Estimation

Marchi

Estevez

Messina

et al. 2020

IEEE Trans. Energy Convers.

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In this paper, we present a new approach to the detection of Loss-Of-Excitation (LOE), a typical failure of synchronous generators. Unlike most of the algorithms proposed in the literature, which only use the information available at the point of connection, we also take advantage of prior knowledge of the generator model. To track the field voltage and the other state variables, we have chosen the Constrained Unscented Kalman Filter (CUKF) as the core estimation technique, with phasor measurements as the input for this filtering algorithm. Detection of LOE is then performed by using the Faulty Modes Detection and Diagnosis (FMDD) algorithm, which combines the normal operation and a LOE-based model to decide in real-time whether an LOE has occurred or not. Results of simulations using a small two-area power system and the IEEE 39-bus system show that LOE detection times can be significantly reduced as compared to conventional and state-of-the-art approaches. Moreover, we observe that the new fault detection signal used to trip the generator can avoid short-term voltage stability problems.

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“…Using the same criterion as in [28], the measurement vector is composed of the real and imaginary parts of the voltage phasor at the point of connection:…”

Section: Synchronous Generator Genrou Modelmentioning

confidence: 99%

Loss of Excitation Detection in Synchronous Generators Based on Dynamic State Estimation

Marchi

Estevez

Messina

et al. 2020

IEEE Trans. Energy Convers.

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, the mechanical and electrical subsystem parameters are considered known in these proposals. In practical applications, these parameters are typically only known from baseline testing, but can significantly deviate from their nominal values due to aging, component replacements, and initial measurement errors [21].…”

Section: Introductionmentioning

confidence: 99%

PMU‐based decentralised mixed algebraic and dynamic state observation in multi‐machine power systems

Lorenz-Meyer

Bobtsov

Nikolaev

et al. 2020

IET Generation Trans & Dist

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The authors propose a novel decentralised mixed algebraic and dynamic state observation method for multi‐machine power systems with unknown inputs and equipped with phasor measurement units (PMUs). More specifically, they prove that for the third‐order flux‐decay model of a synchronous generator, the local PMU measurements provide enough information to reconstruct algebraically the load angle and quadrature‐axis internal voltage. Due to the algebraic structure, a high numerical efficiency is achieved, which makes the method applicable to large‐scale power systems. Also, they prove that the relative shaft speed can be globally estimated combining a classical immersion and invariance observer with – the recently introduced – dynamic regressor extension and mixing parameter estimator. This adaptive observer ensures global convergence under weak excitation assumptions that are verified in applications. The proposed method neither requires the measurement of exogenous input signals such as the field voltage and the mechanical torque nor the knowledge of mechanical subsystem parameters.

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“…This is a new field of application that promises to improve the current models. In Reference [90], the authors proposed a methodology to enhance the synchronous generator model, based on PMU measurements. First, the estimation of the variables (frequency, voltage, and current phasors) of the dynamic state were obtained.…”

mentioning

confidence: 99%

Advanced Distribution Measurement Technologies and Data Applications for Smart Grids: A Review

et al. 2020

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The integration of advanced measuring technologies in distribution systems allows distribution system operators to have better observability of dynamic and transient events. In this work, the applications of distribution grid measurement technologies are explored in detail. The main contributions of this review are: (a) a comparison of eight advanced measurement devices for distribution networks, based on their technical characteristics, including reporting periods, measuring data, precision, and sample rate; (b) a review of the most recent applications of micro-Phasor Measurement Units, Smart Meters, and Power Quality Monitoring devices used in distribution systems, considering different novel methods applied for data analysis; and (c) an input-output table that relates measured quantities from micro-Phasor Measurement Units and Smart Meters needed for each specific application found in this extensive review. This paper aims to serve as an important guide for researches and engineers studying smart grids.

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Online tracking of sub-transient generator model variables using dynamic phasor measurements

Cited by 11 publications

References 15 publications

Loss of Excitation Detection in Synchronous Generators Based on Dynamic State Estimation

Loss of Excitation Detection in Synchronous Generators Based on Dynamic State Estimation

PMU‐based decentralised mixed algebraic and dynamic state observation in multi‐machine power systems

Advanced Distribution Measurement Technologies and Data Applications for Smart Grids: A Review

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