Juan R. Camarillo-Peñaranda

Characterization of phase-angle jump in radial systems using incremental voltage phasors

A methodology for characterizing the phase-angle jump associated to voltage sags in radial systems using incremental voltage quantities is presented in this paper. The incremental voltage phasor is defined as the difference between the pre-fault and the during-fault voltage phasors at the point of common coupling. The characteristics of this phasor are stated for different fault conditions as a function of system impedances. Both fault impedance and source neutral grounding impedance are considered in the analysis. Furthermore, the vector representation of phasors and impedance diagrams are employed as a graphical aid for understanding the incremental quantities behavior as a function of the system parameters. Finally, the theoretical analysis is confirmed using simulations in the ATP-EMTP environment. The results of this work can be useful in future works for fault classification and fault location in radial systems.

Fault classification and voltage sag parameters computation using voltage ellipses

A fault classification and voltage sag parameters computation using voltage ellipses in Clarkes domain is presented in this paper. The voltage sag parameters computed are the point-on-wave of initiation and recovery, residual voltage, and phase-angle jump. A change in the phase reference in Clarkes transformation is proposed to simplify the fault classification procedure. The point-on-wave of initiation and recovery are defined based on the reference circle in Clarkes domain described by the system during normal operation. The residual voltage and phase-angle jump are computed using the expressions of alpha and beta components in Clarkes domain and using some trigonometric theorems. The proposed fault classification and voltage sag characteristics computation are applied to real data provided by IEEE 1159.2 WG. The proposed fault classification algorithm is capable of classifying events and computing the residual voltage and phase-angle jump. Also, the voltage sag duration of short events and multistage events is successfully computed. This work is an incremental contribution in the field of voltage sag analysis in the time domain using Clarkes transformation.

Behavior of phase voltages due to faults in radial power systems: An educational tool

A study of the impact of the means of grounding on the voltage sag and swell characterization is presented in this paper. Only temporary overvoltages and undervoltages caused by faults are considered. The voltage divider model is employed, and the symmetrical components are used to obtain the phasor voltages at the point of common coupling as functions of the means of grounding of the system and the distance between the point of common coupling and the fault location. A computational tool that shows the phasor behavior during a fault event is developed. Also, a zone classification is proposed based on the location of voltage vectors depending on the fault type. This zone classification may be a cornerstone for new methods of fault classification and location in future works.

Characterization of sags due to faults in radial systems using three-phase voltage ellipse parameters

A characterization and classification of sags due to faults in radial systems considering the grounding method of the source using parametric equations and voltage ellipse parameters is presented in this paper. The Clarkes transformation is used to compute parametric equations in the αβ framework based on the expressions of three phase voltages in the time domain. The parametric equations deduced allow to calculate, point by point, the values of the ellipses of each type of fault in each time. The deduced parametric equations and voltage ellipse parameters are tested in a simulated distribution system and with real data provided by IEEE 1159.2 Working Group. Also, the relation with the well-known ABC classification was established. The deduced parametric equations are a useful tool for the people that need to make decisions with limited time in order to reduce the time to obtain results and the uncertainty in the decision-making process.

Reconfiguración de paneles fotovoltaicos para reducción del consumo de hidrógeno en las celdas de combustible de sistemas híbridos

Hybrid generation combines advantages from fuel cell systems with non-predictable generation approaches, such as photovoltaic and wind generators. In such hybrid systems, it is desirable to minimize as much as possible the fuel consumption, for the sake of reducing costs and increasing the system autonomy. This paper proposes an optimization algorithm, referred to as population-based incremental learning, in order to maximize the produced power of a photovoltaic generator. This maximization reduces the fuel consumption in the hybrid aggregation. Moreover, the algorithms speed enables the real-time computation of the best configuration for the photovoltaic system, which also optimizes the fuel consumption in the complementary fuel cell system. Finally, a system experimental validation is presented considering 6 photovoltaic modules and a NEXA 1.2KW fuel cell. Such a validation demonstrates the effectiveness of the proposed algorithm to reduce the hydrogen consumption in these hybrid systems.

A novel fault classification method using Wavelet transform and Artificial Neural Networks

A novel fault classification method using Wavelet transform and Artificial Neural Networks is presented in this paper. First, Clarkes transformation is applied to the fault signals in order to obtain the alpha, beta, and zero components. Next, the space-vector magnitude is extracted from alpha and beta components. Then, the Wavelet transform is applied to the space-vector magnitude and zero sequence component in order to calculate the energy distribution in the Wavelet detailed levels. Finally, this Wavelet energy distribution is fed up to an Artificial Neural Network classifier in order to match the input energy pattern to its output. By applying this method, an accuracy of 100% is obtained, even with noisy data. The application of this method creates an opportunity for protecting transmission lines and providing additional information to the system operator in a short time.

Reconfiguration of Photovoltaic Arrays Based on a GPU-Accelerated Exhaustive Search Algorithm

This paper proposes a parallel exhaustive search algorithm to find the best electrical configuration of PV arrays. This information is required to reconfigure, in real-time, the PV array in order to mitigate the power losses caused by partial shading and other mismatching conditions. The algorithm is based on a parameterized model of the PV system, and it is designed to run in commercial graphic processing units (GPU). This GPU-accelerated approach provides a significant reduction in the processing time compared with the classical CPU-only serial algorithm. Hence, the proposed GPU-based reconfiguration enables to reconfigure, in real-time, PV systems much larger contrasted with the CPU-only approach.

Modelado del Generador de Corriente Directa Incluyendo los Efectos de la Saturación Magnética y la Temperatura

Resumen es: En este articulo se propone la inclusion del efecto de la temperatura sobre la resistencia de campo al modelo del generador de corriente directa DC1A val...

Recomendaciones para Seleccionar Índices para la Validación de Modelos

A set of recommendations to select error indices to model validation is presented in this paper. The recommendations are based on the comparison of indices used to validate dynamic systems. Nine error indices and one fit index are presented and mathematically defined. Based on the data reported in literature to validate models, step function and sine function are selected, as patron signals, to evaluate the index results. As a relevant contribution of this paper, recommendations to select and interpret error indices during the validation of physical system models are given.