Carlos M. Orallo

Harmonics Measurement With a Modulated Sliding Discrete Fourier Transform Algorithm

Accurate harmonics estimation has become a key issue in power quality assessment. This paper deals with a discrete Fourier transform (DFT)-based measurement technique, which can be easily employed to accurately determine the harmonic components of a distorted signal, i.e., voltage or current. The proposed method is based on a modulated sliding DFT algorithm, which is unconditionally stable and does not accumulate errors due to finite precision representation, and a variable sampling period technique (VSPT) to achieve a frequency adaptive mechanism. It is worth noting that the VSPT changes the sampling period for a variable grid frequency condition, leading to a constant sampling frequency under steady-state conditions. The proposed method provides: 1) high degree of accuracy; 2) structural/performance robustness; and 3) frequency adaptability. Given the modular nature of the method, it is implemented on a field programmable gate array. Simulations and experimental tests are shown to verify the performance of the proposed method.

Three-Phase Harmonic and Sequence Components Measurement Method Based on mSDFT and Variable Sampling Period Technique

This paper presents a three-phase harmonic and sequence components measurement method based on modulated sliding discrete Fourier transform (mSDFT) and a variable sampling period technique. The proposal allows measuring the harmonic components of a three-phase signal and computes the corresponding imbalance by estimating the instantaneous symmetrical components. In addition, an adaptive variable sampling period is used to obtain a sampling frequency multiple of the main frequency. By doing so, DFT typical errors, known as spectral leakage and picket-fence effect, are mitigated in steady state. The proposal is tested with different disturbances by simulation and experimental results. Some results obtained with a power quality monitor implemented with the proposed system are also presented. The high rejection to distortion in the electrical network, frequency adaptability, flexibility, and good performance in power quality monitor application render the proposed method a promising alternative for signal processing from the mains.

Thyristor Gate Control implementation on FPGA for particle accelerator facilities

This paper provides the general description, design guidelines and implementation issues of a digital Thyristor Gate Control (TGC) system developed for particle accelerator facilities. The present proposal improves the TGC performance by replacing the conventional synchronization method based on a single phase zero crossing Phase Lock Loop (PLL) with a novel three-phase synchronous method known as Variable Sampling Period Filter PLL (VSPF-PLL). The proposal is implemented in a custom board and it is tested in a 6-phase power converter under a very distorted mains.

Three-phase harmonics measurement method based on mSDFT

This work presents a three-phase harmonics measurement method based on the mSDFT (Modulated Sliding Discrete Fourier Transform) and a variable sampling period technique. The proposal allows measuring the harmonic components of a three-phase signal and computes the corresponding imbalance by estimating its positive, negative and zero sequence. In addition, an adaptive variable sampling period is used in order to obtain a sampling frequency multiple of the main frequency. mSDFT high rejection to distortions in the electrical network and flexibility of proposed method makes it an interesting alternative for the design of grid power monitors.

Single Bin Sliding Discrete Fourier Transform

The conventional method for spectrum analysis is the discrete Fourier transform (DFT), usually implemented using a fast Fourier transform (FFT) algorithm. However, certain applications require an online spectrum analysis only on a subset ofM frequencies of an N-point DFT ðM < NÞ. In such cases, the use of single-bin sliding DFT (Sb-SDFT) is preferred over the direct application of FFT. The purpose of this chapter is to provide a concise overview of the Sb-SDFT algorithms, analyze their performance, and highlight advantages and limitations. Finally, a technique to mitigate the spectral leakage effect, which arises when using the Sb-SDFT in nonstationary conditions, is presented.

Evaluación y comparación de algoritmos de clasificación de eventos de tensión mediante su implementación en un DSP

This paper assesses the experimental implementation of three voltage events classification algorithms. They are known in the literature as symmetrical component algorithm, six-phase algorithm and space vector algorithm. They use the fundamental voltages and sequences components estimated by a sequence detector proposed by the authors previously. This detector is synchronized with the network achieving phase and frequency adaptation and high rejection to the network disturbances. From implementation of classification algorithm and detector on a DSP (Digital Signal Processor), the performance of each algorithm in the classification of real events and their possible application in a PQM (Power Quality Monitor) was evaluated.

Evaluation of voltage events detection methods

This work presents an comparison of some methods for voltage events detection. This evaluation is part of a wider study, which aims to develop a power quality monitor. Performance of evaluated methods is analyzed under demanding conditions, where the input signals present frequency variations, harmonic content and events of different magnitude, duration and initial phase. The conclusions of this analysis are the basis for the choice of the best suited methods for a real application.

Evaluation of three-phase voltage dips classification algorithms based on computational intelligence

In this paper are evaluated three different three-phase voltage dip classification algorithms developed by the authors. All them are based in the information provided by a sequence detector developed in a previuos work. The first algorithm is a logical classifier, the second it is based on fuzzy logic, and the third algorithm is a neural network adequately trained for this purpose. This evaluation is part of a wider work, and it will be used to the potential development of a power quality monitor. The performance of the algorithms under test in the classification of voltage dips, in ideal conditions and with variations in the phase and frequency, and high harmonic content is assessed. The conclusions of this analysis are the basis for the development and implementation of some of the functions of this instrument.