José María Sierra-Fernández

• PhD
• Professor (Assistant) at Universidad de Cádiz

Cloud-induced photovoltaic variability can affect grid stability and power quality, especially in electricity systems with high penetration levels. The availability of irradiance field forecasts in the scale of seconds and meters is fundamental for an adequate control of photovoltaic systems in order to minimize their impact on distribution network...

Lab sessions in engineering education are designed to reinforce theoretical concepts. However, usually there are not enough time to reinforce all of them. Remote and virtual lab give students more time for reinforce those concepts. In particular, with remote labs, this can be done interacting with real lab equipment and specific configurations. Thi...

The current high penetration of distributed generation (DG) has set up a challenge for energy management and consequently for the monitoring and assessment of power quality (PQ) continuous disturbances and events. Besides, new types of hybrid disturbances have appeared, due to the uncontrolled (spatial and temporal) connection of non-linear loads....

Higher-Order Statistics (HOS) have been frequently applied in Power Quality Disturbance (PQD) analysis as a reliable tool for event detection. This paper outlines a technique based on mean, variance and zero-lag third and fourth cumulants – skewness and kurtosis – along with the Total Harmonic Distortion (THD) index for PQD detection. These statist...

Very short-term solar forecasts are gaining interest for their application on real-time control of photovoltaic systems. These forecasts are intimately related to the cloud motion that produce variations of the irradiance field on scales of seconds and meters, thus particularly impacting in small photovoltaic systems. Very short-term forecast model...

This paper presents a higher-order statistics-based approach of detecting transients that uses the fourth-order discrete spectrogram to monitor the power supply in a node of the domestic smart grid. Taking advantage of the mixed time–frequency domain information, the method allows for the transient detection and the subsequent identification of the...

The present works deals with the presentation and test of a novel Power Quality index, based in Higher-Order cumulants. Synthetics are used for test different start point, amplitude and length for the most common Power Grid disturbances (DIP, Oscillatory Transient, Harmonic Temporal Distortion and Impulsive Transient), obtaining a high accuracy (ov...

The aim of this work is by using artificial neural networks (ANNs) compare six regression algorithms supported by 14 power-quality features, based on higher-order statistics (HOS). In addition, we have combined time and frequency domain estimators to deal with non-stationary measurement sequences; the final target is to implement the system in a sm...

This paper presents a novel virtual instrument for PQ assessment, based in higher-order statistics. It implements a new power-quality index, which is thought to trigger the measurement procedure when an electrical fault comes about. The user interfaces include not only the online variance charts but also the skewness and kurtosis graphs, along with...

This paper proposes a technique based in the graphical cluster analysis to be implemented in Smart Power Quality Analyzers (SPQA), a proposal Instrument Class S, according to the standard UNE-EN 61000-4-30, with the goal of monitoring electrical grids where new events arise as a consequence of the penetration of new energy resources. In the presenc...

A comparative analysis between two higher-order statistics in the frequency domain, combined with wavelets’ filters, confirms the existence of three frequency sub-bands that characterize the species emission. De-noising via wavelet eliminates the symmetrical noise and reveals non-Gaussian features. Here, we show that the spectral kurtosis enhances...

Power-line signal analysis according to international standards implies the acquisition of signals with a stable frequency. However, the value of this frequency falls in a relatively wide range. That frequency stability allows the adoption of an acquisition scheme where it is not allowed to use another window function other than the rectangular one...

Autonomous measurement units are indispensable for the development of the smart grid in order to get faster processing responses, stability, and to provide the user with information regarding power quality (losses, harmonics, outages, steady-state and transient events). In this paper, the development of a novel FPGA-based real-time analyzer is pres...

In addition to the solar radiation, wind is other atmospheric parameter which affects the production of concentrated solar plants. The defence strategies, focused on preventing wind damages in collectors, force unproductive configurations in the solar field wasting part of the available resource. This brief note aims to define an efficient approach...

Higher-order statistics demonstrate their innovative features to characterize power quality events, beyond the traditional and limited Gaussian perspective, integrating time-frequency features and within the frame of a Higher-Order Neural Network (HONN). With the massive advent of smart measurement equipment in the electrical grid (Smart Grid), and...

For the development of the future smart grid, the detection of power quality events is a key issue for the power system monitoring. Voltage sags, swells, harmonics (variations) and interruptions, which produce large losses in commercial and industrial consumers, are the main events to be considered due to the sensitivity of equipment to these elect...

This paper compares classification techniques to identify several power quality disturbances in a frame of smart metering design for smart grids with high penetration of PV systems. These techniques are: Linear Discriminant Analysis (LDA), Nearest Neighbor Method (kNN), Learning Vector Quantization (LVQ) and Support Vector Machine (SVM). For this p...

This paper presents a novel non-destructive method for termite detection that uses the entropy of the continuous wavelet transform of the acoustic emission signals as an uncertainty measurement, to achieve selective frequency separation in complex impulsive-like noisy scenarios, with the aid of the spectral kurtosis as a validating tool. The goal c...

This work compares seven regression algorithms implemented in artificial neural networks (ANNs) supported by 14 power-quality features, which are based in higher-order statistics. Combining time and frequency domain estimators to deal with non-stationary measurement sequences, the final goal of the system is the implementation in the future smart g...

Spaceborne scatterometers provide accurate measurements of wind fields over the sea. This letter proposes a methodology to take advantage of the revisit time and high resolution in the wind fields retrieved from Advanced Scatterometer ASCAT-A and ASCAT-B measurements to assess complexity in their short-term evolution and in their instantaneous spat...

Two higher-order statistics in the frequency domain confirm the existence of three frequency sub-bands that characterize the species acoustic emission. In parallel, de-noising via wavelet eliminates the symmetrical noise and reveals additional non-Gaussian features. The spectral kurtosis enhances high power variability components, once the filter b...

Abstract The availability of updated information of regional wind fields is fundamental for an efficient management and prediction of wind power production. The present paper proposes a regional wind monitoring system based on the integration of different meteorological nets as a direct way to obtain this information. Concretely, we describe a moni...

Utilizando técnicas de Emisión Acústica (EA), este trabajo evalúa la corrosión en láminas de acero de reducidas dimensiones, considerando tres agentes corrosivos: Agua (H2O), Ácido sulfúrico (H2SO4) y Ácido Acético (C2H4O2). Asimismo, se analizan los efectos de borde asociados a los especímenes, y se muestra la diferencia de actuación del localizad...

This research presents a comparative analysis of wind speed forecasting methods applied to perform 1 h-ahead forecasting. The main significant development has been the introduction of low-quality measurements as exogenous information to improve these predictions. Eight prediction models have been assessed; three of these models [ persistence, autor...

This paper deals with a novel application of the Spectral Kurtosis (SK) in power-quality modeling and analysis. The two major advantages of this three-spectral analysis are: robustness to noise and the capability to detect nonlinearities, as impulsive-like signals. The first aim is to study some of the theoretical aspects of the SK estimation, perf...

In this paper are described some active functions that can be implemented in the inverters that interface the distributed energy resources to the grid can implement. These inverters are mainly placed in the grid for injecting the energy produced by the distributed generation, but they can do more than that taking advantage of their distributed loca...

This paper introduces the use of a fourth-order frequency-domain statistical estimator, the spectral kurtosis (SK), in the field of power-quality analysis. The research has been organized in the frame of a research national project and points towards the implementation of these techniques into an automatic platform to perform PQ analysis in power p...

This paper describes an intelligent measurement system for Power Quality (PQ) assessment. Computational guts are based in Higher Order Statistics (HOS) and the intelligent decision system is based in the Case-Base Reasoning (CBR) paradigm, which could re-configure its parameter according to the power net conditions. The power signal characterizatio...

This paper presents the performance results of a Virtual Instrument (VI) based in Case-Based Reasoning (CBR), conceived to online monitor the power-quality. The PC-based instrument receives data through a DAQ board and a differential probe, while maintaining economy by eliminating the extra network construction and hardware. Being flexible, present...

This paper describes an intelligent measurement system for Power Quality (PQ) assessment. Based in Higher-Order Statistics (HOS), its computational intelligence is based in the Case-Based Reasoning (CBR) paradigm. The characterization of the signal is done using the variance, the skewness and the kurtosis over a tuned sliding window. These feature...

This paper deals with the detection of power quality anomalies which preserve the frequency of the power line, in particular sags and swells. Three statistical estimators have been used (variance, skewness and kurtosis) to enhance characterization of these anomalies. The proposed measurement strategy is funded in the tuning of the signal under test...

This paper describes a virtual instrument for PQ assessment. Conceived to detect transients, sags and swells, the computational nucleus is based in higher-order statistics, which enhance the statistical characterization of the raw data, with the consequent improvement of the instrument's performance. This measurement application is thought to be us...