Statistical Analysis of the Global Solar Radiation in Cúcuta using the ANOVA Model

Objective: This paper presents a statistical analysis of solar radiation in the city of Cúcuta, aiming to provide a detailed description of its variability between 2005 and 2015. This information represents an assessment tool to study the solar potential of the region for photovoltaic system design, motivated by the need to improve the cost-effectiveness of this technology, and thus increase its penetration in the Colombian electric grid. Methodology: Three weather databases with hourly data were studied, from which the one with the largest amount of data available was selected. By means of the R Studio software, two types of statistical methods were executed: single factor variance analysis (ANOVA) and Bonferroni test. From this, graphs representing the statistical summary of solar radiation values in the last decade were obtained. Results: The ANOVA showed a p-value of 6,28x10-7, indicating that there is a statistically significant difference in the sample mean between the different years of study. Likewise, the years and months with the greatest deviation and the possible causes for the variability of this parameter were identified. Conclusions: Despite showing a stable behavior, the radiation of the city of Cúcuta requires a very specific analysis for its use in applications that need a high sensitivity in the handling of this information, since there are statistically significant variations that can occur for its use. Funding: Universidad Francisco de Paula Santander        Objetivo: Esta investigación presenta un análisis estadístico de la radiación solar en la ciudad de Cúcuta, con el objetivo de brindar una descripción detallada de su variabilidad entre los años 2005 y 2015. Esta información representa una herramienta evaluativa en el estudio del potencial solar de la región para el diseño de sistemas fotovoltaicos, partiendo de la necesidad de mejorar la relación costo/beneficio de esta tecnología, y así incrementar su penetración en la matriz eléctrica colombiana. Metodología: Se realizó un estudio de tres bases de datos climatológicas con información horaria, seleccionando aquella con la mayor cantidad de datos disponibles. Por medio del software R Studio, se ejecutaron dos tipos de métodos estadísticos: análisis de la varianza de un solo factor (ANOVA) y test de Bonferroni. A partir de esto, se obtuvieron gráficas que representan el resumen estadístico de los valores de radiación solar en la última década. Resultados: El análisis ANOVA arrojó un valor p de 6,28x10-7, indicando que existe una diferencia estadísticamente significativa de la media muestral entre los diferentes años de estudio. Asimismo, se identificaron los años y meses con mayor desviación y las posibles causas de la variabilidad de este parámetro. Conclusiones: A pesar de tener un comportamiento estable, la radiación de la ciudad de Cúcuta requiere de un análisis muy específico para su uso en aplicaciones que necesiten una alta sensibilidad en el manejo de esta información, ya que hay variaciones estadísticamente significativas que se pueden presentar para su uso. Financiamiento: Universidad Francisco de Paula Santander.      

Técnicas de Adquisición y Procesamiento de Señales Electrocardiográficas en la Detección de Arritmias Cardíacas

The development of ambulatory monitoring systems and its electrocardiographic (ECG) signal processing techniques has become an important field of investigation, due to its relevance in the early detection of cardiovascular diseases such as the arrhythmias. The current trend of this technology is oriented to the use of portable equipment and mobile devices such as Smartphones, which have been widely accepted due to the technical characteristics and common integration in daily life. A fundamental characteristic of these systems is their ability to reduce the most common types of noise by means of digital signal processing techniques.  Among the most used techniques are the adaptive filters and the Discrete Wavelet Transform (DWT) which have been successfully implemented in several studies. There are systems that integrate classification stages based on artificial intelligence, which increases the performance in the process of arrhythmias detection. These techniques are not only evaluated for their functionality but for their computational cost, since they will be used in real-time applications, and implemented in embedded systems. This paper shows a review of each of the stages in the construction of a standard ambulatory monitoring system, for the contextualization of the reader in this type of technology.El desarrollo de sistemas de  monitoreo  ambulatorio  y  sus  técnicas  de  procesamiento  de  la  señal  electrocardiográfica (ECG) se han convertido en un importante campo de investigación, debido a su relevancia en la detección temprana de enfermedades cardiovasculares, tales como arritmias. La tendencia actual de esta tecnología está orientada al uso de equipos portátiles y dispositivos móviles como los Smartphones, que han sido ampliamente aceptados debido a sus características técnicas y a su integración, cada vez más común, en la vida diaria. Una característica fundamental de estos sistemas es su capacidad de reducir los tipos más comunes de ruido mediante técnicas de procesamiento de señales digitales. Entre las técnicas más utilizadas se encuentran los filtros adaptativos y la Transformada Discreta Wavelet (DWT, por sus siglas en inglés), los cuales han sido implementados exitosamente en diversos estudios. Así mismo, se reportan sistemas que integran etapas de clasificación basadas en inteligencia artificial, con lo cual se aumenta el rendimiento en el proceso de detección de arritmias. En este sentido, estas técnicas no solo son evaluadas por su funcionalidad, sino por su costo computacional, debido a que deben ser utilizadas en aplicaciones en tiempo real, e implementadas en sistemas embebidos. Este documento presenta una revisión del estado del arte de cada una de las etapas en la construcción de un sistema de monitoreo ambulatorio estándar, para la contextualización del lector en este tipo de tecnologías

Solar radiation estimation models based on artificial intelligence applied to the photovoltaic electrical generation for norte de Santander, Colombia

Determinar de forma precisa la cantidad de irradiación que podría capturar el sistema. Determinar de forma precisa la eficiencia en el proceso de conversión de energía desde irradiación solar a energía eléctrica por parte de la implementación física.The absence of direct measurements of solar radiation in many countries around the world (due to the high costs of installation and maintenance of the measuring devices) has been identified (in the Colombian case by the Energy Mining Planning Unit) as one of the main barriers for the deployment of photovoltaic systems. In this sense, estimation techniques have been developed in the literature for locations where this variable is not measured. These techniques take advantage of the correlation between the irradiance and other climatic parameters of wider distribution and easier access to construct models that forecast with high accuracy the solar potential of a specific place. Thus, the current research exposes the implementation of an indirect estimation model designed with Artificial Intelligence that uses the temperature, humidity, wind speed and sunshine duration to predict the irradiation, as a tool for sizing photovoltaic systems in Norte de Santander (Colombia) where solar radiation measurements are available just in three of the 40 municipalities in which the region is geographically divided

Sistema adaptativo de inferencia neuro-difusa (ANFIS) para la estimación de la radiación solar global

Objective: To propose an Adaptive Neuro-Fuzzy Inference System (ANFIS) for the estimation of global solar radiation in the city of Cúcuta (Norte de Santander, Colombia). Methodology: Historical records of ambient temperature, solar brightness, wind speed, relative humidity, hour, and global solar radiation from 2005 to 2015 were obtained from IDEAM database. ANFIS networks with different configurations were created using the data from IDEAM and Fuzzy Logic Toolbox in Matlab. After comparing statistical errors, the ANFIS model with the minimum RMSE was selected. Results: The statistical errors of the model are: R2 = 0.9115, RMSE = 124,23 Wh/m2, and MAPE = 27,8 %, which show high accuracy for the estimation of global solar radiation in the city of Cúcuta. Conclusions: The proposed ANFIS network is a model based on artificial intelligence with enough accuracy to design photovoltaic systems in the region under study, where there is a lack of pyranometers to constantly measure the solar resource.Objetivo: Proponer un sistema adaptativo de inferencia neuro-difusa (ANFIS) para la estimación de la radiación solar global en la ciudad de Cúcuta (Norte de Santander, Colombia) Metodología: A partir de registros históricos del IDEAM se obtuvieron las variables: temperatura ambiente, brillo solar, velocidad del viento, humedad relativa, hora de medición y radiación solar global entre los años 2005 y 2015. Usando la herramienta Fuzzy Logic Toolbox de Matlab y los datos del IDEAM se crearon redes ANFIS con diferentes configuraciones. Después de comparar los errores estadísticos, se escogió el modelo ANFIS que minimizara el RMSE. Resultados: Los errores estadísticos del modelo son: R2 = 0.9115, RMSE = 124,23 Wh/m2 y MAPE = 27,8 %, evidenciando una alta precisión para la estimación de la radiación solar global en el territorio seleccionado. Conclusiones: La red ANFIS propuesta es un modelo basado en inteligencia artificial con precisión suficiente para ser usado en el diseño de sistemas fotovoltaicos en la región, que no cuenta con una amplia red de piranómetros para medir el recurso solar

Techniques of Acquisition and Processing of Electrocardiographic Signals in the Detection of Cardiac Arrhythmias

The development of ambulatory monitoring systems and its electrocardiographic (ECG) signal processing techniques has become an important field of investigation, due to its relevance in the early detection of cardiovascular diseases such as the arrhythmias. The current trend of this technology is oriented to the use of portable equipment and mobile devices such as Smartphones, which have been widely accepted due to the technical characteristics and common integration in daily life. A fundamental characteristic of these systems is their ability to reduce the most common types of noise by means of digital signal processing techniques.  Among the most used techniques are the adaptive filters and the Discrete Wavelet Transform (DWT) which have been successfully implemented in several studies. There are systems that integrate classification stages based on artificial intelligence, which increases the performance in the process of arrhythmias detection. These techniques are not only evaluated for their functionality but for their computational cost, since they will be used in real-time applications, and implemented in embedded systems. This paper shows a review of each of the stages in the construction of a standard ambulatory monitoring system, for the contextualization of the reader in this type of technology