Estimación instantánea de fasores oscilantes usando fi ltros TaylorK-Kalman

La matriz de transición de estados que aproxima un polinomio de Taylor de orden K a la envolvente compleja y sus primeras derivadas conduce a una pluralidad de representaciones de la señal pasabanda de una oscilación en un sistema de potencia. Disponiendo del vector de estados con las derivadas del polinomio, es posible aplicar el algoritmo de Kalman a estos modelos de señal truncados y obtener observadores (filtros) capaces de estimar el fasor dinámico y sus derivadas. Las estimaciones obtenidas con esta técnica son instantáneas (sin retraso), un atributo importante para aplicaciones de control o de monitoreo síncrono. Además, las estimaciones incluyen a la frecuencia, variable crucial para determinar la inestabilidad del sistema. El nuevo filtro reduce el vector total de error conseguido con el filtro tradicional de Kalman, es mucho más estable, y con transitorios cinco veces más cortos; además mejora las estimaciones fasoriales de oscilaciones con fluctuaciones de frecuencia

Estimación fasorial instantánea en armónicas oscilantes usando el filtro Taylor-Kalman-Fourier

Recientemente se propuso el filtro Taylork-Kalman para estimaciones instantáneas de fasores oscilantes pues reducía abruptamente el nivel de error de estimación por un factor de diez a partir del modelo de segundo orden. En este artículo, se demuestra que para órdenes superiores o iguales a dos, los filtros adquieren respuestas de fase nula y plana alrededor de la frecuencia de operación, lo que garantiza estimaciones instantáneas. El método de respuesta en frecuencia nos condujo al diseño de un filtro más robusto, referido como filtro Taylork-Kalman-Fourier, debido a su modelo de señal multiarmónico. Resulta que el banco de filtros peine logrado con K=0 es equivalente al de la transformada discreta de Fourier (DFT); y el de filtros valla obtenido con K=2 es similar a la transformada Taylor2-Fourier, pero con la ventaja de proveer estimaciones sin retardo, y con un costo computacional inferior al de la transformada rápida de Fourier (FFT). Debido a su característica instantánea, y simplicidad computacional, estos filtros son muy útiles para el análisis y control de oscilaciones armónicas en tiempo real en sistemas de potencia

Prony Method Estimation as a New Approach for Surge Comparison Testing in Turn Insulation Diagnostics for Three Phase Stator Windings

This article presents an evaluation of Prony method estimation and its implementation considerations for surge comparison test application in turn insulation diagnostics for three-phase stator windings. Surge testing diagnostics compares recorded surge voltage signals of motor winding, and a diagnostic is then defined with a defined value of EAR (error area ratio), which evaluates the difference between signals to determine a turn insulation diagnostic. First, an overview of surge testing is presented. Next, the Prony method and the considerations for its implementation in surge testing are described. Then, a numerical simulation is used to define a simulated turn fault surge voltage signal, where its parameters can be obtained with Prony method estimation and compared with EAR to evaluate its performance. Lastly, recorded surge test signals from two tested motors are used to validate Prony method estimation application for surge test diagnostics, where twelve recorded surge signals for no-fault and fault conditions were analyzed. The summary results of the surge signals parameter estimation are presented in the results and discussion section

Prony Method Estimation as a New Approach for Surge Comparison Testing in Turn Insulation Diagnostics for Three Phase Stator Windings

This article presents an evaluation of Prony method estimation and its implementation considerations for surge comparison test application in turn insulation diagnostics for three-phase stator windings. Surge testing diagnostics compares recorded surge voltage signals of motor winding, and a diagnostic is then defined with a defined value of EAR (error area ratio), which evaluates the difference between signals to determine a turn insulation diagnostic. First, an overview of surge testing is presented. Next, the Prony method and the considerations for its implementation in surge testing are described. Then, a numerical simulation is used to define a simulated turn fault surge voltage signal, where its parameters can be obtained with Prony method estimation and compared with EAR to evaluate its performance. Lastly, recorded surge test signals from two tested motors are used to validate Prony method estimation application for surge test diagnostics, where twelve recorded surge signals for no-fault and fault conditions were analyzed. The summary results of the surge signals parameter estimation are presented in the results and discussion section

Design Implication of a Distribution Transformer in Solar Power Plants Based on Its Harmonic Profile

This article presents a comparative analysis for the design considerations for a solar power generation transformer. One of the main existing problems in transformer manufacturing is in the renewable energy field, specifically the solar power generation, where the transformer connected to the inverter is operated under a certain harmonic content and operating conditions. The operating conditions of the transformer connected to the inverter are particularly unknown for each solar power plant; thus, the transformer will be subject to a particular harmonic content, which is defined by the inverter of the solar power plant. First, the fundamental calculations for solar power plant transformer and the proposed methodology for the design calculation of the distribution pad-mounted three phase transformer are presented. Then, a design study case is described where a distribution transformer and an inverter of a particular solar power plant are used for the analysis. Next, the transformer under analysis is modeled using finite element analysis in ANSYS Maxwell® software, where the transformer will be designed for a non-harmonic and harmonic content application. Lastly, the main design parameters, flux density, the core losses and the winding excitation voltage of the transformer are calculated and presented in results and discussion section

Prony Method Estimation for Motor Current Signal Analysis Diagnostics in Rotor Cage Induction Motors

This article presents an evaluation of Prony method and its implementation considerations for motor current signal analysis diagnostics in rotor cage induction motors. The broken rotor bar fault signature in current signals is evaluated using Prony method, where its advantages in comparison with fast Fourier transform are presented. The broken rotor bar fault signature could occur during the life cycle operation of induction motors, so that is why an effective early detection estimation technique of this fault could prevent an insulation failure or heavy damage, leaving the motor out of service. First, an overview of cage winding defects in rotor cage induction motors is presented. Next, Prony method and its considerations for the implementation in current signature analysis are described. Then, the performance of Prony method using numerical simulations is evaluated. Lastly, an assessment of Prony method as a tool for current signal analysis diagnostics is performed using a laboratory test system where real signals of an induction motor with broken rotor bar operated with/without a variable frequency drive are analyzed. The summary results of the estimation (amplitudes and frequencies) are presented in the results and discussion section

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6 $\times$ 6 $\times$ 6 m$^3$ liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019–2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties.DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6x6x6m3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

International audienceLiquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation