102 research outputs found

    Caracterización del sustrato bentónico del arrecife Tuxpan, Veracruz, México, con énfasis en la comunidad de corales escleractinios

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    Se caracteriza el sustrato bentónico del arrecife Tuxpan, Veracruz, México con énfasis en la comunidad de corales escleractinios para definir el patrón de riqueza y cobertura coralina de las formaciones tipo plataforma de Veracruz.117 fototransectos, fueron distribuidos en 4 zonas y 16 ambientes arrecifales durante 2015. Se tomaron un total de 2.920 fotografías sobre transectos de 25 m para estimar la cobertura con el programa Coral Point Count. La riqueza y cobertura coralina fueron comparadas para determinar su semejanza entre zonas y ambientes arrecifales, a partir de los grupos morfo funcionales (GMF), usando pruebas estadísticas o ecológicas. 36 especies componen la comunidad de corales escleractinios y la riqueza coralina mostró diferencias entre zonas, siendo mayor en las pendientes. De acuerdo con el análisis de escalamiento multidimensional no métrico (NMDS) y ANOSIM, los GMF y la cobertura específica de corales caracterizaron 4 zonas arrecifales: planicie, cresta, pendiente de barlovento y pendiente de sotavento. La cobertura coralina en sotavento, es inversamente proporcional a la profundidad, donde los valores más altos fueron observados entre 3 y 15 m. En barlovento, no se evidenció una relación de la cobertura coralina con la profundidad y los valores más altos se registraron entre 10 y 20 m. La caracterización de las zonas del arrecife Tuxpan puede servir como modelo de los arrecifes tipo plataforma de Veracruz así como para los planes de manejo de esta Área Natural Protegida, especialmente en las actividades de esnórquel y buceo

    Validation of the SAFRAN meteorological analysis system in the Northeast of Spain

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    Póster elaborado para la European Geosciences Union General Assembly celebrada los días 22-27 de abril de 2012 en Vien

    Design and Test of a High-Performance Wireless Sensor Network for Irradiance Monitoring

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    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 networks. Irradiance sensor networks have proved to be efficient tools for supporting these forecasts, but the costs of monitoring systems with the required specifications are economically justified only for large plants and research purposes. This study deals with the design and test of a wireless irradiance sensor network as an adaptable operational solution for photovoltaic systems capable of meeting the measurement specifications necessary for capturing the clouds passage. The network was based on WiFi, comprised 16 pyranometers, and proved to be stable at sampling periods up to 25 ms, providing detailed spatial representations of the irradiance field and its evolution. As a result, the developed network was capable of achieving comparable specifications to research wired irradiance monitoring network with the advantages in costs and flexibility of the wireless technology, thus constituting a valuable tool for supporting nowcasting systems for photovoltaic management and control

    Online System for Power Quality Operational Data Management in Frequency Monitoring Using Python and Grafana

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    This article proposes a measurement solution designed to monitor the instantaneous frequency in power systems. It uses a data acquisition module and a GPS receiver for time stamping and traceability. A Python-based module receives data, computes the frequency, and finally transfers the measurement results to a database. The frequency is calculated with two different methods, which are compared in the article. The stored data is visualized using the Grafana platform, thus demonstrating its potential for comparing scientific data. The system as a whole constitutes an efficient, low-cost solution as a data acquisition system.This research is funded by the Spanish Ministry of Science and Education through the project PID2019-108953RB-C21; has been co-financed by the European Union under the 2014-2020 ERDF Operational Program. Additionally, funding for frequency monitoring comes from the Andalusian-FEDER project FEDER-UCA18-108516 (Intelligent Techniques for visualization and data compression of PQ data in the smart grid)

    Reconfigurable Web-Interface Remote Lab for Instrumentation and Electronic Learning

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    Lab sessions in Engineering education are designed to reinforce theoretical concepts. However, there is usually not enough time to reinforce all of them. Remote and virtual labs give students more time to reinforce those concepts. In particular, with remote labs, this can be done interacting with real lab instruments and specific configurations. This work proposes a flexible configuration for Remote Lab Sessions, based on some of 2019 most popular programming languages (Python and JavaScript). This configuration needs minimal network privileges, it is easy to scale and reconfigure. Its structure is based on a unique Reception-Server (which hosts User database, and Time Shift Manager, it is accessible from The Internet, and connects Users with Instruments-Servers) and some Instrument-Servers (which manage hardware connection and host experiences). Users always connect to the Reception-Server, and book a shift for an experience. During the time range associate to that shift, User is internally forwarded to Instrument-Server associated with the selected experience, so User is still connected to the Reception-Serer. In this way, Reception-Server acts as a firewall, protecting Instrument-Servers, which never are open to The Internet. A triple evaluation system is implemented, User session logging with auto-evaluation (objectives accomplished), a knowledge test and an interaction survey. An example experience is implemented, controlling a DC source using Standard Commands for Programmable Instruments

    Site Characterization Index for Continuous Power Quality Monitoring Based on Higher-order Statistics

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    The 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). Besides, there are new types of disturbances owing to the uncontrolled connections of non-linear loads. The stochastic behaviour triggers the need for new holistic indicators which also deal with big data of PQ in terms of compression and scalability so as to extract the useful information regarding different network states and the prevailing PQ disturbances for future risk assessment and energy management systems. Permanent and continuous monitoring would guarantee the report to claim for damages and to assess the risk of PQ distortions. In this context, we propose a measurement method that postulates the use of two-dimensional (2D) diagrams based on higher-order statistics (HOSs) and a previous voltage quality index that assesses the voltage supply waveform in a continous monitoring campaign. Being suitable for both PQ and reliability applications, the results conclude that the inclusion of HOS measurements in the industrial metrological reports helps characterize the deviations of the voltage supply waveform, extracting the individual customers' pattern fingerprint, and compressing the data from both time and spatial aspects. The method allows a continuous and robust performance needed in the SG framework. Consequently, the method can be used by an average consumer as a probabilistic method to assess the risk of PQ deviations in site characterization.This work was supported by the Spanish Ministry of Science and Innovation (Statal Agency for Research), and the EU (AEI/FEDER/UE) via project PID2019-108953RB-C21 Strategies for Aggregated Generation of Photovoltaic Plants: Energy and Meteorological Operational Data (SAGPVEMOD), and the precedent TEC2016-77632-C3-3-R

    Lista de los peces de Tuxpan, Veracruz, México | Checklist of fishes from Tuxpan, Veracruz, Mexico

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    En este trabajo se presenta una lista sistemática de los peces del municipio de Tuxpan, Veracruz con base en los muestreos efectuados de 2007 a 2012 en los ecosistemas costeros. Para esto se hicieron 282 censos visuales y se colectaron 772 ejemplares en los arrecifes coralinos, además de la revisión de 132 organismos procedentes de las capturas camaronera y atunera. Se listan 372 especies pertenecientes a 221 géneros y 93 familias que representan el 71 % de la ictiofauna veracruzana. Se incluyen 13 nuevos registros, entre ellos Pterois volitans. Las familias con mayor riqueza fueron: Sciaenidae (22 especies), Serranidae (22 especies), Carangidae (18 especies) y Gobiidae (18 especies). En la ictiofauna tuxpeña destacan los componentes marino y estuarino que comparten 109 especies. A pesar de que es una de las faunas de Veracruz mejor conocidas, se sugiere aumentar el esfuerzo de investigación en los sistemas marinos y dulceacuícolas. Palabras clave: Ictiofauna, inventario, Veracruz. ABSTRACT A systematic checklist of fishes from Tuxpan, Veracruz is presented in this paper, based in sampling done from 2007 to 2012 on coastal ecosystems. For this purpose, 282 visual censuses were done and 772 specimens were collected at coral reefs, as well as 132 fishes pertained to shrimp and tuna fisheries were studied. 372 fish species belonging to 221 genera and 93 families which represent 71 % of Veracruz´s ichthyofauna. 13 new records are included, between these, Pterois volitans. The families with highest number of species were: Sciaenidae (22 species), Serranidae (22 species), Carangidae (18 species) and Gobiidae (18 species). Estuarine and marine components were the most important in Tuxpan’s ichthyofauna and they share 109 species. In spite of this fauna is well known, we suggest to enhance the research in marine and fresh water ecosystems. Key words: Ichthyofauna, inventory, Veracru

    Methodology for the Surveillance the Voltage Supply in Public Buildings Using the ITIC Curve and Python Programming

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    This paper proposes an easy-to-implement method for detecting and assessing two of the most frequent PQ (Power Quality) problems: voltage sags and swells. These can affect sensitive equipment such as computers, programmable logic controllers, contactors, etc. Therefore, it is of great interest to implement it in any laboratory, not only for protection reasons but also as a safeguard for claims against the supply company. Thanks to the actual context, in which it is possible to manage big volumes of data, connect multiple devices with IoT (Internet of Things), etc., it is feasible and of great interest to monitor the voltage at specific points of the network. This makes it possible to detect voltage sags and swells and diagnose which points are more prone to this type of problems. For the detection of sags and swells, a program written in Python is in charge of crawling all the files in the database and target those RMS values that fall outside the established limits. Compared to LabVIEW, which might have been the most logical alternative, being the acquisition hardware from the same company (National Instruments), Python has a higher computational performance and is also free of charge, unlike LabVIEW. Thanks to the libraries available in Python, it allows a hardware control close to what is possible using LabVIEW. Implemented in MATLAB, the ITIC (Information Technology Industry Council) power acceptability curve reflects the impact of these power quality disturbances in electrical power systems. The results showed that the combined action of Python and MATLAB performed well on a conventional desktop computer.10 página

    Current Status and Future Trends of Power Quality Analysis

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    In this article, a systematic literature review of 153 articles on power quality analysis in PV systems published in the last 20 years is presented. This provides readers with an overview on PQ trends in several fields related to instrumental techniques that are being used in the smart grid to visualize the quality of the energy, establishing a solid literature base from which to start future research. A preliminary appreciation allows us to intuit that higher-order statistics are not implemented in measurement equipment and that traditional instrumentation is still used for the performance of measurement campaigns, not yielding the expected results since the information processed does not come from an electrical network from 20 years ago. Instead, current networks contain numerous coupled load effects; thus, new disturbances are not simple; they are usually complex events, the sum of several types of disturbances. Likewise, depending on the type of installation, the objective of the PQ analysis changes, either by detecting certain events or simply focusing on seeing the state of the network

    Statistical Dataset and Data Acquisition System for Monitoring the Voltage and Frequency of the Electrical Network in an Environment Based on Python and Grafana

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    This article presents a unique dataset, from a public building, of voltage data, acquired using a hybrid measurement solution that combines Python (TM) for acquisition and Grafana (TM) for results representation. This study aims to benefit communities, by demonstrating how to achieve more efficient energy management. The study outlines how to obtain a more realistic vision of the quality of the supply, that is oriented to the monitoring of the state of the network; this should allow for better understanding, which should in turn enable the optimization of the operation and maintenance of power systems. Our work focused on frequency and higher order statistical estimators which, combined with exploratory data analysis techniques, improved the characterization of the shape of the stress signal. These techniques and data, together with the acquisition and monitoring system, present a unique combination of low-cost measurement solutions, which have the underlying benefit of contributing to industrial benchmarking. Our study proposes an effective and versatile system, which can do acquisition, statistical analysis, database management and results representation in less than a second. The system offers a wide variety of graphs to present the results of the analysis, so that the user can observe them and identify, with relative ease, any anomalies in the supply which could damage the sensitive equipment of the correspondent installation. It is a system, therefore, that not only provides information about the power quality, but also significantly contributes to the safety and maintenance of the installation. This system can be practically realized, subject to the availability of internet access
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