J. J. G. de la Rosa

Short term forecasting of solar radiation

Variations of solar irradiance are known to have a significant influence on electric power generation by solar energy systems. With high connection densities of PV system in the low voltage (LV) network, this might cause to degrade electric power quality. The present study describes a multiplicative ARMA models to generate instantaneous series of global irradiation. The data set used in this work corresponding to five minutes global irradiance data were recorded in a radiometric station located in south Spain (Cordoba) during a for years period (1994-1997). The development of these models is based on removing the annual periodicity and seasonal variation of solar radiation. The method proposed considers fitting an AR model to the data. The selection of the order of the model has been made on the basis of seven different criteria. The predicted values of solar radiation are compared with the observed data series and it was found that this approach leads to optimal predictions.

ARIMA vs. Neural networks for wind speed forecasting

In this paper an ARIMA model is used for time-series forecast involving wind speed measurements. Results are compared with the performance of a back propagation type NNT. Results show that ARIMA model is better than NNT for short time-intervals to forecast (10 minutes, 1 hour, 2 hours and 4 hours). Data was acquired from a unit located in Southern Andalusia (Peñaflor, Sevilla), with a soft orography (10 minutes between measurements). This feature is which makes performance of the ARIMA model and the NNT very similar, so a simple forecasting model could be used in order to administrate energy sources. The paper presents the process of model validation, along with a regression analysis, based in real-life data.

Very short term forecasting of solar radiation

Variations of solar irradiance are known to have a significant influence on electric power generation by solar energy systems. With high connection densities of PV system in the low voltage (LV) network, this might cause to degrade electric power quality. The present study describes a multiplicative ARMA models to generate instantaneous series of global irradiation. The data set used in this work corresponding to five minutes global irradiance data were recorded in a radiometric station located in south Spain (Córdoba) during a four years period (1994–1997). The development of these models is based on removing the annual periodicity and seasonal variation of solar radiation. The method proposed considers fitting an AR model to the data. The selection of the order of the model has been made on the basis of seven different criteria. The predicted values of solar radiation are compared with the observed data series and it was found that this approach leads to optimal predictions.

Integrating power quality to automated meter reading

This paper discusses the metering technologies and communications systems that enable the development of automated meter reading (AMR) systems. Power quality is one area where the AMR system can be very valuable. This article investigates the challenges in the integration of PQ monitoring system measurements in a distribution automation system (DAS).

Automated Meter Reading Systems in Outage Management

An outage management system (OMS) is one of the main components of a distribution management system (DMS). This research work has focused on outage location and service restoration, which are the main functions of outage management system. An efficient outage location method could dramatically reduce the outage duration and costs. Thus, a fast and accurate outage management system would be very important. Metering technologies and communications systems have advanced to enable the development of automated meter reading (AMR) Systems. Outage management is one area where the AMR system can be very valuable. However, more information than the AMRs provide is necessary to locate an outage accurately. For this purpose an algorithm that makes efficient use information available from the distribution supervisory control and data acquisition (SCADA) and power line communication based AMR systems to locate the more probable outage sources has been developed. The algorithm also allows to construct a tree model of a distribution network from a data input table.

Characterizing the harmonic attenuation effect of high-pressure sodium lamps

In this paper, several high power lighting networks based on high pressures sodium (HPS) lamps with rated lamp powers of 70, 150 and 250 W have been set up. They have also been tested with different levels of power using dimming for a 220 V power supply. These have been chosen because of they are used in public lighting. Each luminaire consists of sodium lamp with dimmable electronic ballast, which can dim the lamp output smoothly and uniformly. This paper focuses on the harmonic characterization of modern HPS lamps connected to dimmable electronic ballasts. Harmonics under full and reduced power for several HPS lamps have been measured. It presents an investigation on the attenuation effect and a proposal of an index called the equivalent lamp index to characterize this effect on HPS lamps. Also it is concluded that using a combination of HPS lamps can result in a reduction of the current distortion.

Power quality for energy efficient buildings

This paper presents results from a PQ audit conducted in an IT-intensive modern office building. Some of the mayor objectives of the PQ study were: detecting the main involved disturbances by PQ monitoring, identifying the power disturbances root causes, characterizing the electromagnetic compatibility level of equipments and installation and providing guidelines for implementing energy-efficiency solutions. It has been found that the main problems for the equipment installed were harmonics and leakage currents. The widespread presence of electronic power supplies in buildings is, in most of the cases, the root cause of the proliferation of harmonics. This case study demonstrates the impacts of generalized electronic devices on the power quality of the buildings and the implications on energy uses.

Higher Order Statistics and Independent Component Analysis for Spectral Characterization of Acoustic Emission Signals in Steel Pipes

Higher order statistics (HOS) are used to characterize acoustic emission events in ring-type samples from steel pipes for the oil industry. Cumulants are used twofold. First, diagonal bispectrum allows the separation of the primary (original) deformation from the reflections produced mainly in the suppressed chord. These longitudinal reflections can hardly be extracted via second-order methods, e.g., wavelet packets and power spectra, because they are partially masked by both Gaussian and non-Gaussian noise. Second, a cumulant-based independent component analysis may be used before the bispectrum, as a preprocessing complement, in the case of multiple-source and multiple-channel recordings. This algorithm suppresses the mutual influence of the sources and sensors. Sample registers were acquired by wide-frequency-range transducers (100-800 kHz) and digitalized by a 2.5-MHz, 12-bit analog-to-digital converter.

New Model for Time-Series Forecasting Using RBFs and Exogenous Data

In this paper we present a new model for time-series forecasting using Radial Basis Functions (RBFs) as a unit of ANN ’s (Artificial Neural Networks), which allows the inclusion of exogenous information (EI) without additional preprocessing. We begin summarizing the most well known EI techniques used ad hoc, i.e. PCA or ICA; we analyse advantages and disadvantages of these techniques in time-series forecasting using Spanish banks and companies stocks. Then we describe a new hybrid model for time-series forecasting which combines ANN ’s with GA (Genetic Algorithms); we also describe the possibilities when implementing on parallel processing systems.

Analysis of voltage dips in PWM AC-DC converters

This paper presents results from about comparative analysis of the effect of voltage dip on AC-DC converters. Voltage dip analysis is a complex stochastic issue, since it involves a large variety of random factors, such as: type of short-circuits in the power system, location of faults, protective system performance and atmospheric discharges. Among all categories of electrical disturbances, the voltage dip (sag) and momentary interruption are the nemeses of the automated industrial process. In particular, the paper analyzes the effect of dip types A, C and D on the minimum dc-bus voltage of PWM boost rectifier compared with traditional diodes rectifier. The principal conclusion from the analysis is that the AC-DC converters can be unaffected by the most generalized voltage dips with small dc-bus capacitance if a relatively low-cost boost follower pre-regulator is added at the front end of the diode bridge