Pub Date : 2022-09-07DOI: 10.1109/ARGENCON55245.2022.9939758
Carla Rodriguez Gonzalez, C. Guzman, V. Andreo
Aedes aegypti is the main vector of dengue, chikungunya and zika viruses, which together have resulted in the highest rate of disease and mortality among emerging and/or re-emerging viruses in the Americas. Vector surveillance is a key tool for prevention and control of these diseases. In this context, a proper distribution of sensors within a city will provide timely and precise information to guide public health actions. Under the assumption that environmental variability will determine different probabilities of mosquito presence and activity, our objective was to characterise the urban coverage of Córdoba city at neighbourhood and census tracts levels in order to determine an optimal distribution for the ovitrap network based on the environmental variability. To this aim we first classified very high resolution (VHR) satellite imagery following an object based (GEOBIA) approach. Then, we estimated several landscape metrics for neighbourhood and census tracts polygons and performed a k-mean clustering to determine groups of environmentally similar polygons over the city. After different tests, we defined four environmental clusters for the census tracts and three for the neighbourhoods. Finally, we distributed 150 ovitraps over the city based on the environmental groups defined and compared this distribution with the one used by the Health Ministry, a random one and, a systematic one. It was observed that the arbitrary distribution is the least environmentally representative of the city both for neighbourhoods and census tracts. Instead, the ovitrap distribution stratified by clusters at census tracts level was the best option as it properly covers the environmental variability detected over the city.
{"title":"Environmental characterisation of an urban area to assess the distribution of Aedes aegypti monitoring system","authors":"Carla Rodriguez Gonzalez, C. Guzman, V. Andreo","doi":"10.1109/ARGENCON55245.2022.9939758","DOIUrl":"https://doi.org/10.1109/ARGENCON55245.2022.9939758","url":null,"abstract":"Aedes aegypti is the main vector of dengue, chikungunya and zika viruses, which together have resulted in the highest rate of disease and mortality among emerging and/or re-emerging viruses in the Americas. Vector surveillance is a key tool for prevention and control of these diseases. In this context, a proper distribution of sensors within a city will provide timely and precise information to guide public health actions. Under the assumption that environmental variability will determine different probabilities of mosquito presence and activity, our objective was to characterise the urban coverage of Córdoba city at neighbourhood and census tracts levels in order to determine an optimal distribution for the ovitrap network based on the environmental variability. To this aim we first classified very high resolution (VHR) satellite imagery following an object based (GEOBIA) approach. Then, we estimated several landscape metrics for neighbourhood and census tracts polygons and performed a k-mean clustering to determine groups of environmentally similar polygons over the city. After different tests, we defined four environmental clusters for the census tracts and three for the neighbourhoods. Finally, we distributed 150 ovitraps over the city based on the environmental groups defined and compared this distribution with the one used by the Health Ministry, a random one and, a systematic one. It was observed that the arbitrary distribution is the least environmentally representative of the city both for neighbourhoods and census tracts. Instead, the ovitrap distribution stratified by clusters at census tracts level was the best option as it properly covers the environmental variability detected over the city.","PeriodicalId":318846,"journal":{"name":"2022 IEEE Biennial Congress of Argentina (ARGENCON)","volume":"39 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133525229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-07DOI: 10.1109/ARGENCON55245.2022.9939959
M. Meira, Guillermo R. Bossio, J. Bossio, C. Verucchi, C. Ruschetti
Reliable detection of broken rotor bars through the analysis of sidebands around the fundamental component of the stator current at steady state is difficult when the motor operates at no-load or low load. In this work it is proposed to monitor the time evolution of the high frequency sequence components associated with broken rotor bars during the starting transient. Through simulations, the behavior of these components is analyzed for balanced and unbalanced power supply conditions, with and without harmonic distortion. The strategy proved to be independent of these conditions.
{"title":"Broken rotor bar detection using the full spectrum applied to the induction motor starting currents","authors":"M. Meira, Guillermo R. Bossio, J. Bossio, C. Verucchi, C. Ruschetti","doi":"10.1109/ARGENCON55245.2022.9939959","DOIUrl":"https://doi.org/10.1109/ARGENCON55245.2022.9939959","url":null,"abstract":"Reliable detection of broken rotor bars through the analysis of sidebands around the fundamental component of the stator current at steady state is difficult when the motor operates at no-load or low load. In this work it is proposed to monitor the time evolution of the high frequency sequence components associated with broken rotor bars during the starting transient. Through simulations, the behavior of these components is analyzed for balanced and unbalanced power supply conditions, with and without harmonic distortion. The strategy proved to be independent of these conditions.","PeriodicalId":318846,"journal":{"name":"2022 IEEE Biennial Congress of Argentina (ARGENCON)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133769051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-07DOI: 10.1109/ARGENCON55245.2022.9940126
Joaquin M. Bozzalla, Juan J. Silva, Jorge L. Márquez, L. Seijas
Synthetic Aperture Radar satellites are becoming increasingly important in the field of Earth observation and maritime surveillance. Given the large amount of data generated by satellite platforms, the use of advanced techniques is required to extract useful information from them. Currently, deep learning techniques applied to object detection obtain a high performance, in particular with the use of convolutional neural networks. This work proposes a model with YOLOv4 architecture trained with the HRSID dataset (with offshore and inshore images) using Transfer Learning, which obtains a performance that improves results present in the literature. A suitable set of hyperparameter values is sought and the modification of the architecture is explored in relation to the size of the input image and the structure of the SPP spatial pyramidal pooling layer. Finally, the model is tested against scenes captured with Sentinel 1 and SAOCOM 1A satellites that were not present in the training.
{"title":"A Ship Detection Model for SAR Data based on YOLOv4: Application to Images from SAOCOM and Sentinel","authors":"Joaquin M. Bozzalla, Juan J. Silva, Jorge L. Márquez, L. Seijas","doi":"10.1109/ARGENCON55245.2022.9940126","DOIUrl":"https://doi.org/10.1109/ARGENCON55245.2022.9940126","url":null,"abstract":"Synthetic Aperture Radar satellites are becoming increasingly important in the field of Earth observation and maritime surveillance. Given the large amount of data generated by satellite platforms, the use of advanced techniques is required to extract useful information from them. Currently, deep learning techniques applied to object detection obtain a high performance, in particular with the use of convolutional neural networks. This work proposes a model with YOLOv4 architecture trained with the HRSID dataset (with offshore and inshore images) using Transfer Learning, which obtains a performance that improves results present in the literature. A suitable set of hyperparameter values is sought and the modification of the architecture is explored in relation to the size of the input image and the structure of the SPP spatial pyramidal pooling layer. Finally, the model is tested against scenes captured with Sentinel 1 and SAOCOM 1A satellites that were not present in the training.","PeriodicalId":318846,"journal":{"name":"2022 IEEE Biennial Congress of Argentina (ARGENCON)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115515365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-07DOI: 10.1109/ARGENCON55245.2022.9940151
P. Salazar, P. Vásquez
Año tras año la generación fotovoltaica gana espacio en el mundo entero gracias al aparecimiento de nuevas tecnologías que abaratan el costo del kWh generado, esto ha permitido que nuevos usuarios accedan a este tipo de tecnología y es ahí donde es necesario que el modelo de análisis para el dimensionamiento se acople a las necesidades propias de cada usuario. Sobre la base de lo planteado, este artículo propone un modelo de optimización de inversiones basado en programación lineal entera mixta, que considera parámetros técnicos, económicos y tributarios modelados en la herramienta Excel y optimizado por el complemento Solver ambos de Microsoft Office 365 cuyo objetivo principal es determinar la factibilidad de que usuarios comerciales del servicio público de electricidad de Ecuador instalen sistemas de micro generación fotovoltaicos para autoconsumo de energía eléctrica.Gracias a adaptabilidad del modelo planteado puede ser utilizado para cualquier usuario comercial e inclusive por usuarios industriales y residenciales con ligeras modificaciones. Como caso de análisis se toma una institución bancaria determinando que la TIR (tasa interna de retorno), el VAN (valor actual neto) y el PRI (periodo de recuperación de la inversión) que se obtienen de este tipo de proyectos son muy competitivos en el escenario actual.
{"title":"Desarrollo de un modelo de evaluación técnico – económico para la optimización de inversiones en micro generación fotovoltaica – caso usuarios comerciales en Ecuador","authors":"P. Salazar, P. Vásquez","doi":"10.1109/ARGENCON55245.2022.9940151","DOIUrl":"https://doi.org/10.1109/ARGENCON55245.2022.9940151","url":null,"abstract":"Año tras año la generación fotovoltaica gana espacio en el mundo entero gracias al aparecimiento de nuevas tecnologías que abaratan el costo del kWh generado, esto ha permitido que nuevos usuarios accedan a este tipo de tecnología y es ahí donde es necesario que el modelo de análisis para el dimensionamiento se acople a las necesidades propias de cada usuario. Sobre la base de lo planteado, este artículo propone un modelo de optimización de inversiones basado en programación lineal entera mixta, que considera parámetros técnicos, económicos y tributarios modelados en la herramienta Excel y optimizado por el complemento Solver ambos de Microsoft Office 365 cuyo objetivo principal es determinar la factibilidad de que usuarios comerciales del servicio público de electricidad de Ecuador instalen sistemas de micro generación fotovoltaicos para autoconsumo de energía eléctrica.Gracias a adaptabilidad del modelo planteado puede ser utilizado para cualquier usuario comercial e inclusive por usuarios industriales y residenciales con ligeras modificaciones. Como caso de análisis se toma una institución bancaria determinando que la TIR (tasa interna de retorno), el VAN (valor actual neto) y el PRI (periodo de recuperación de la inversión) que se obtienen de este tipo de proyectos son muy competitivos en el escenario actual.","PeriodicalId":318846,"journal":{"name":"2022 IEEE Biennial Congress of Argentina (ARGENCON)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122134854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-07DOI: 10.1109/ARGENCON55245.2022.9939876
Diego S. Comas, Agustín Amalfitano, G.J. Meschino, V. Ballarin
La textura es una característica relevante en muchos tipos de imágenes y su representación e identificación es uno de los problemas esenciales y más desafiantes del procesamiento digital de imágenes. Una región con una textura determinada tiene propiedades estadísticas específicas, repitiendo ciertos grupos de píxeles periódicamente con algún grado de variabilidad en su apariencia y posición relativa. Dentro de las redes basadas en aprendizaje profundo, las Redes Neuronales Convolucionales (CNN) han tomado enorme impulso en procesamiento de imágenes. Su potencial está en que, una vez entrenadas, contienen información que puede ampliar el campo de conocimiento sobre el problema bajo estudio, si se encuentran mecanismos adecuados para su análisis e interpretación. La visualización de características brinda un marco adecuado para esta tarea, generando imágenes que describen qué es lo que cada filtro describe. Con un enfoque adecuado, su análisis permite dar una interpretación de las características y extraer conocimiento. En este trabajo se presenta un enfoque para la interpretación de texturas a partir de visualización de características, utilizando CNN entrenadas con bases de datos de texturas. Los resultados indican que el enfoque propuesto permite identificar patrones/características descriptas por cada filtro, dando interpretación y significado, partiendo de términos asociados con textura, como rugosidad, ondulaciones, transiciones, bordes y formas geométricas.
{"title":"Interpretación y visualización de características en texturas mediante Redes Neuronales Convolucionales","authors":"Diego S. Comas, Agustín Amalfitano, G.J. Meschino, V. Ballarin","doi":"10.1109/ARGENCON55245.2022.9939876","DOIUrl":"https://doi.org/10.1109/ARGENCON55245.2022.9939876","url":null,"abstract":"La textura es una característica relevante en muchos tipos de imágenes y su representación e identificación es uno de los problemas esenciales y más desafiantes del procesamiento digital de imágenes. Una región con una textura determinada tiene propiedades estadísticas específicas, repitiendo ciertos grupos de píxeles periódicamente con algún grado de variabilidad en su apariencia y posición relativa. Dentro de las redes basadas en aprendizaje profundo, las Redes Neuronales Convolucionales (CNN) han tomado enorme impulso en procesamiento de imágenes. Su potencial está en que, una vez entrenadas, contienen información que puede ampliar el campo de conocimiento sobre el problema bajo estudio, si se encuentran mecanismos adecuados para su análisis e interpretación. La visualización de características brinda un marco adecuado para esta tarea, generando imágenes que describen qué es lo que cada filtro describe. Con un enfoque adecuado, su análisis permite dar una interpretación de las características y extraer conocimiento. En este trabajo se presenta un enfoque para la interpretación de texturas a partir de visualización de características, utilizando CNN entrenadas con bases de datos de texturas. Los resultados indican que el enfoque propuesto permite identificar patrones/características descriptas por cada filtro, dando interpretación y significado, partiendo de términos asociados con textura, como rugosidad, ondulaciones, transiciones, bordes y formas geométricas.","PeriodicalId":318846,"journal":{"name":"2022 IEEE Biennial Congress of Argentina (ARGENCON)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125269272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-07DOI: 10.1109/ARGENCON55245.2022.9940144
C. Medina-Ramos, D. Carbonel-Olazabal, J. Betetta-Gomez, Irene Tafur-Anzualdo
This paper presents a model based on the first-order Volterra series with Laguerre polynomials to identify the dynamics of global temperature anomalies in the last century. The independent variables to use in the model must be capable of predicting future anomalies, which should be chosen after analyzing the parameters used in significant models to predict global warming. Consequently, based on such studies and the criteria of this research, the selected set of parameters related to the proposed model is the following: the anthropogenic CO2, the total solar irradiance, global population, and ocean heat content. Focused on obtaining that model, the Volterra series, six Laguerre polynomials, unitary normalization, and the correlation factors between variables were applied to identify such anomalies. Results show a mathematical model multivariate techniques consistently can outperform other models like statistical models.Further, the performance of the Volterra-Laguerre model provides evidence that the variables in this proposal can forecast temperature anomalies with an error of less than 5% in the last thirty years of the period study. The proposed model has identified the dynamics of the global temperature anomaly, and the variables reveal that industrial activities and human actions must be part of the reflection to implement international policies that cushion climatic anomalies. Safely, only effective rules will prevent the increasing global warming effect and consequently deterioration of the marine habitat, the alteration of the water cycle, and the reproductive change of vegetables.
{"title":"Global Temperature Anomaly by Volterra-Laguerre Model from CO2 Emission, Solar Irradiance, Population, and the Oceans Heat Content","authors":"C. Medina-Ramos, D. Carbonel-Olazabal, J. Betetta-Gomez, Irene Tafur-Anzualdo","doi":"10.1109/ARGENCON55245.2022.9940144","DOIUrl":"https://doi.org/10.1109/ARGENCON55245.2022.9940144","url":null,"abstract":"This paper presents a model based on the first-order Volterra series with Laguerre polynomials to identify the dynamics of global temperature anomalies in the last century. The independent variables to use in the model must be capable of predicting future anomalies, which should be chosen after analyzing the parameters used in significant models to predict global warming. Consequently, based on such studies and the criteria of this research, the selected set of parameters related to the proposed model is the following: the anthropogenic CO2, the total solar irradiance, global population, and ocean heat content. Focused on obtaining that model, the Volterra series, six Laguerre polynomials, unitary normalization, and the correlation factors between variables were applied to identify such anomalies. Results show a mathematical model multivariate techniques consistently can outperform other models like statistical models.Further, the performance of the Volterra-Laguerre model provides evidence that the variables in this proposal can forecast temperature anomalies with an error of less than 5% in the last thirty years of the period study. The proposed model has identified the dynamics of the global temperature anomaly, and the variables reveal that industrial activities and human actions must be part of the reflection to implement international policies that cushion climatic anomalies. Safely, only effective rules will prevent the increasing global warming effect and consequently deterioration of the marine habitat, the alteration of the water cycle, and the reproductive change of vegetables.","PeriodicalId":318846,"journal":{"name":"2022 IEEE Biennial Congress of Argentina (ARGENCON)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123959639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-07DOI: 10.1109/ARGENCON55245.2022.9939998
José Aravena, D. Carrasco, Emilio Contreras Boulet, Matías Uriarte, M. Díaz
Several off-the-shelf real-time control systems are available for industrial and academic applications. These systems enable real-time control and prototyping of power electronic applications. However, most of these systems have a considerable cost and are inflexible, limiting their teaching and academic research usage. Consequently, this paper presents the design and implementation of a control platform based on a low-cost easy-to-program microcontroller from Texas Instruments. The proposed control platform is intended for rapid-control-prototyping, and it considers optic PWM outputs, isolated sensing of voltage/currents, multipurpose input-outputs, and hardware protections. Experimental results are presented to validate the usefulness of the proposed control platform.
{"title":"Design and Implementation of an off-the-shelf Controller for Power Electronics Research and Teaching","authors":"José Aravena, D. Carrasco, Emilio Contreras Boulet, Matías Uriarte, M. Díaz","doi":"10.1109/ARGENCON55245.2022.9939998","DOIUrl":"https://doi.org/10.1109/ARGENCON55245.2022.9939998","url":null,"abstract":"Several off-the-shelf real-time control systems are available for industrial and academic applications. These systems enable real-time control and prototyping of power electronic applications. However, most of these systems have a considerable cost and are inflexible, limiting their teaching and academic research usage. Consequently, this paper presents the design and implementation of a control platform based on a low-cost easy-to-program microcontroller from Texas Instruments. The proposed control platform is intended for rapid-control-prototyping, and it considers optic PWM outputs, isolated sensing of voltage/currents, multipurpose input-outputs, and hardware protections. Experimental results are presented to validate the usefulness of the proposed control platform.","PeriodicalId":318846,"journal":{"name":"2022 IEEE Biennial Congress of Argentina (ARGENCON)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124024712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-07DOI: 10.1109/ARGENCON55245.2022.9939713
Ezequiel A. Marranghelli, Ramon Lopez La Valle, P. A. Roncagliolo
In the global navigation satellites systems, the trav-eling time determination of the travelling signals is the main task of the receivers. For precise positioning applications, the accuracy is expected to be less than 1 ns to limit the error to the centimeters level. Hence, the influence of the responses of the antennas cannot be ignored since they can introduce delays of the order of 10 ns, which translates into errors of a few meters. The problem becomes even more complex when compact antenna arrays are used since the mutual coupling between their elements is considerable. In this work, a signal pre-processing scheme for coupled antenna arrays to compensate their space-frequency responses is described and analyzed.
{"title":"Space-Frequency Orthonormal Compensation Method for GNSS Compact Antenna Array Designs","authors":"Ezequiel A. Marranghelli, Ramon Lopez La Valle, P. A. Roncagliolo","doi":"10.1109/ARGENCON55245.2022.9939713","DOIUrl":"https://doi.org/10.1109/ARGENCON55245.2022.9939713","url":null,"abstract":"In the global navigation satellites systems, the trav-eling time determination of the travelling signals is the main task of the receivers. For precise positioning applications, the accuracy is expected to be less than 1 ns to limit the error to the centimeters level. Hence, the influence of the responses of the antennas cannot be ignored since they can introduce delays of the order of 10 ns, which translates into errors of a few meters. The problem becomes even more complex when compact antenna arrays are used since the mutual coupling between their elements is considerable. In this work, a signal pre-processing scheme for coupled antenna arrays to compensate their space-frequency responses is described and analyzed.","PeriodicalId":318846,"journal":{"name":"2022 IEEE Biennial Congress of Argentina (ARGENCON)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128503634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-07DOI: 10.1109/ARGENCON55245.2022.9939920
M. Bierzychudek, Axel Britos, J. Casais
This paper presents a surge protection module designed to protect measurement instruments against overcurrent and overvoltage. The module was designed to be used with wireless instruments for high voltage metrology, but it can also be used with any other type of instrumentation. The characterization performed shows that the surge protection module introduces negligible errors in measurements.
{"title":"Surge protection module for wireless instruments used on a High Voltage Metrology","authors":"M. Bierzychudek, Axel Britos, J. Casais","doi":"10.1109/ARGENCON55245.2022.9939920","DOIUrl":"https://doi.org/10.1109/ARGENCON55245.2022.9939920","url":null,"abstract":"This paper presents a surge protection module designed to protect measurement instruments against overcurrent and overvoltage. The module was designed to be used with wireless instruments for high voltage metrology, but it can also be used with any other type of instrumentation. The characterization performed shows that the surge protection module introduces negligible errors in measurements.","PeriodicalId":318846,"journal":{"name":"2022 IEEE Biennial Congress of Argentina (ARGENCON)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129233353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-07DOI: 10.1109/ARGENCON55245.2022.9939919
Sergio N. Bragagnolo, Rodrigo M. Schierloh, Jorge C. Vaschetti, J. R. Vega
Los grandes usuarios en Argentina tienen una tarifa especifica que establece dos escalones para el precio de la energía, dependiendo si su demanda es superior (o igual) a 300 kW o inferior. En el primer caso, el costo de la energía es mayor al 40 % y es el motivo principal para la aplicación de estrategias de gestión de demanda en los usuarios con una potencia cercana a los 300 kW. Al gestionar el consumo, el beneficio es doble, dado que se reduce significativamente la factura eléctrica al evitar que el usuario exceda los 300 kW y se disminuye el consumo. En este artículo, se propone una gestión óptima de los aires acondicionados de un centro de diagnóstico por imágenes que tiene picos de potencia superiores a 300 kW. La gestión considera a los equipos de aire acondicionado como las únicas cargas controlables y permite minimizar los costos de energía mientras maximiza el confort térmico. La estrategia se basa en un control predictivo de horizontes deslizantes que utiliza un algoritmo genético para resolver el problema de optimización. Además, el control contempla restricciones eléctricas y de temperatura. El desempeño se evalúa contra el control on-off de los aires acondicionados del centro, y los resultados muestran una reducción significativa del costo eléctrico y un mantenimiento del confort debido al recorte de los picos de demanda y a una pequeña disminución de la energía consumida.
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