Circuitos electrónicos aplicados con amplificadores operacionales

El obieto de la presente obra es, como su tí¡rlo indica, el tratamiento de los circuitos y sistemas electrónicos basados en el ampüficador operacional (AO). Está concebida fundamentalmente para estudiantes universitarios de grado de electrónica y materias afines, entre las que cabe citar la Ingeniería Industrial, las Ciencias Físicas y las Comunicaciones, sin olüdar a la Formación Profesional. Aborda el analisis de numerosas aplicaciones de circütos electrónicos en los diferentes ámbitos de la Tecnología. El libro también aborda el tratamiento de circuitos digitales, cuya base de operación se basa en la Electrónica Analógtca.232 pág

Two deep learning approaches to forecasting disaggregated freight flows: convolutional and encoder–decoder recurrent

Time series forecasting of disaggregated freight flow is a key issue in decision-making by port authorities. For this purpose and to test new deep learning techniques we have selected seven time series of imported goods from Morocco to Spain through the port of Algeciras, and we have tested two forecasting deep neural networks models: dilated causal convolutional and encoder–decoder recurrent. We have experimented with four different granularities for each series: quarterly, monthly, weekly and daily. The results show that our neural network models can manage these raw series without first removing seasonality or trend. We also highlight the ability of neural models to work with a fixed input size of one year, being able to make good predictions using the same input size for all granularities. The two deep learning models have globally improved the benchmarks of the M4 Competition of forecasting. Each neural network model obtains its best results under different circumstances: the recurrent one with daily granularity and intermittent series, and the convolutional one with weekly and monthly granularitie

Reliability Monitoring Based on Higher-Order Statistics: A Scalable Proposal for the Smart Grid

The increasing development of the smart grid demands reliable monitoring of the power quality at different levels, introducing more and more measurement points. In this framework, the advanced metering infrastructure must deal with this large amount of data, storage capabilities, improving visualization, and introducing customer-oriented interfaces. This work proposes a method that optimizes the smart grid data, monitoring the real voltage supplied based on higher order statistics. The method proposes monitoring the network from a scalable point of view and offers a two-fold perspective based on the duality utility-prosumer as a function of the measurement time. A global PQ index and 2D graphs are introduced in order to compress the time domain information and quantify the deviations of the waveform shape by means of three parameters. Time-scalability allows two extra features: long-term supply reliability and power quality in the short term. As a case study, the work illustrates a real-life monitoring in a building connection point, offering 2D diagrams, which show time and space compression capabilities, as well

Intelligent Methods for Characterization of Electrical Power Quality Signals using Higher Order Statistical Features

This paper considers a few important techniques classification for to identify several power quality disturbances. For this purpose, a process based in HOS has been realized to extract features that help in classification. In this stage the geometrical pattern established via higher-order statistical measurements is obtained, and this pattern is function of the amplitudes and frequencies of the power quality disturbances associated to the 50-Hz power-line. Once the features are managed will be segmented to form training and test sets and them will be applied in the statistical methods used to perform automatic classification of PQ disturbances. The best technique of those compared is selected according to correlation and mistake rates

Demand and Storage Management in a Prosumer Nanogrid Based on Energy Forecasting

Energy efficiency and consumers' role in the energy system are among the strategic research topics in power systems these days. Smart grids (SG) and, specifically, microgrids, are key tools for these purposes. This paper presents a three-stage strategy for energy management in a prosumer nanogrid. Firstly, energy monitoring is performed and time-space compression is applied as a tool for forecasting energy resources and power quality (PQ) indices; secondly, demand is managed, taking advantage of smart appliances (SA) to reduce the electricity bill; finally, energy storage systems (ESS) are also managed to better match the forecasted generation of each prosumer. Results show how these strategies can be coordinated to contribute to energy management in the prosumer nanogrid. A simulation test is included, which proves how effectively the prosumers' power converters track the power setpoints obtained from the proposed strategy.Spanish Agencia Estatal de Investigacion ; Fondo Europeo de Desarrollo Regional

Detection and characterization of amplitude defects using spectral kurtosis

Peer Reviewe

Administraciones públicas y organizaciones de voluntariado : contenido y alcance de sus interacciones

El proceso de reestructuración del estado de bienestar provoca la redefinición de las relaciones entre las administraciones públicas y el tercer sector. En este proceso, las entidades de acción social cobran un protagonismo creciente y se plantean nuevas formas de aproximación a las administraciones públicas. La comunicación analiza el contenido y el alcance de dichas interacciones en el espacio autonómico y local, expone las tendencias que siguen las administraciones públicas en su aproximación a las organizaciones de acción social y el modo en que dichas organizaciones operan ante las administraciones. Por último, adelantamos una valoración de las interpretaciones realizadas en los últimos años.The process of change of the Welfare State causes redefinition of the relations between the public administrations and organizations of the Third Sector. In this process, the entities of social action receive an increasing protagonism and new forms of approximation to the public administration appear. The article is about the content and the scope of the above mentioned interactions in the autonomic and local space. It exposes the trends that the public administrations follow in their approximation to the organizations of the social action and the way in that organizations act with the administrations. It advances, likewise, one valuation of the interpretations realized in the last years

LED street lighting: A power quality comparison among street light technologies

High-pressure sodium lamps are currently the main lamps used in public lighting. However, the possibility of using high-power light emitting diode (LEDs) for street lighting is growing continuously due to their greater energy efficiency, robustness, long life and light control. The aim of this paper is to study the power quality of high-power lighting networks based on LED and high-pressure sodium lamps. Both electromagnetic and dimmable electronic ballasts, which can dim the lamp output smoothly and uniformly, have been used connected to high-pressure sodium lamps. High-pressure sodium lamps connected to electronic equipment have been tested with different arc power levels using dimming on a 230V power supply. The study presented in this paper is completely based on measurements, including harmonic currents in the frequency range up to 150 kHz for all the technologies. The main results show a broadband spectrum in LED lamps which confirms other research in Fuorescent lamps powered by high-frequency ballasts. Results also indicate a decrease in the harmonic value with increasing harmonic order, and a decrease in the harmonic value at half load (60%) compared with full load (100%). Although total harmonic distortion of the current is lower with highpressure sodium lamps connected to electronic rather than electromagnetic ballasts, LED lamps achieved the lowest total harmonic distortion of curren

Forecasting PM10 in the Bay of Algeciras Based on Regression Models

Different forecasting methodologies, classified into parametric and nonparametric, were studied in order to predict the average concentration of PM10 over the course of 24 h. The comparison of the forecasting models was based on four quality indexes (Pearson’s correlation coefficient, the index of agreement, the mean absolute error, and the root mean squared error). The proposed experimental procedure was put into practice in three urban centers belonging to the Bay of Algeciras (Andalusia, Spain). The prediction results obtained with the proposed models exceed those obtained with the reference models through the introduction of low-quality measurements as exogenous information. This proves that it is possible to improve performance by using additional information from the existing nonlinear relationships between the concentration of the pollutants and the meteorological variables

Power quality events detection using fourth-order spectra

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 plants and power inverters. Higher-order statistics in the frequency domain manage to distinguish 3 types of electrical anomalies (sags, swells and transients), with an accuracy of 83%