Optimized complex power quality classifier using one vs. rest support vector machine

Nowadays, power quality issues are becoming a significant research topic because of the increasing inclusion of very sensitive devices and considerable renewable energy sources. In general, most of the previous power quality classification techniques focused on single power quality events and did not include an optimal feature selection process. This paper presents a classification system that employs Wavelet Transform and the RMS profile to extract the main features of the measured waveforms containing either single or complex disturbances. A data mining process is designed to select the optimal set of features that better describes each disturbance present in the waveform. Support Vector Machine binary classifiers organized in a ?One Vs Rest? architecture are individually optimized to classify single and complex disturbances. The parameters that rule the performance of each binary classifier are also individually adjusted using a grid search algorithm that helps them achieve optimal performance. This specialized process significantly improves the total classification accuracy. Several single and complex disturbances were simulated in order to train and test the algorithm. The results show that the classifier is capable of identifying >99% of single disturbances and >97% of complex disturbances.Fil: de Yong, David Marcelo. Universidad Nacional de Río Cuarto. Facultad de Ingeniería. Departamento de Electricidad y Electrónica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Bhowmik, Sudipto. Nexant Inc; Estados UnidosFil: Magnago, Fernando. Universidad Nacional de Río Cuarto. Facultad de Ingeniería. Departamento de Electricidad y Electrónica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentin

Automatic voltage control in electrical power system based on expert systems

En este trabajo se presenta el diseño de un controlador experto para el nivel de tensión en un sistema eléctrico de potencia. La utilización del concepto de nodo piloto permite mantener la lista de controladores estable ante los cambios topológicos de la red. La normativa del Operador Eléctrico de la Provincia de Alberta – Canadá, es utilizada para lograr el perfil óptimo de tensiones. La validación del controlador se realiza mediante una simulación sobre un caso de biblioteca y se compara la solución obtenida con la brindada por un flujo óptimo de potencia y con la de un algoritmo genético. Como resultado fundamental se obtiene el tratamiento unificado del perfil de tensiones y el despacho óptimo de reactivo sin necesidad de recurrir a un algoritmo de dos pasos. El controlador propuesto resulta apto para su aplicación en línea y en tiempo real, así como flexible a la hora de tratar con problemas de difícil formulación analítica.This paper presents the design of an expert controller applied to voltage level control in a power system. The use of pilot node concept allows to keep stable the list of controllers against topological changes in the network. To achieve the optimal voltage profile, the Alberta Electric System Operator regulations are used. The controller validation is performed by simulating a case library and the solution is compared with results provided by an optimal power flow and a genetic based algorithm. The main advantage of the propose model is the unified treatment of the voltage profile and the reactive dispatch without the need of a two-step algorithm. The proposed controller is suitable for online real-time applications and it is flexible when dealing with problems that present a complex analytical formulation.Fil: Vaschetti, Jorge Carlos. Universidad Tecnológica Nacional. Facultad Regional Córdoba; ArgentinaFil: Magnago, Fernando. Universidad Nacional de Río Cuarto. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Sauchellis, Victor. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentin

Plataforma de ensayo para caracterización de módulos fotovoltaicos comerciales

Un parámetro muy importante en el comportamiento de un generador fotovoltaico (FV) es la temperatura de trabajo del mismo. Esto se debe a que la temperatura de trabajo influye sobre la característica I-V del módulo. El aumento de la temperatura produce una reducción de la potencia máxima del generador FV y por consiguiente una pérdida significativa de rendimiento. La influencia de la temperatura sobre la curva característica I-V de un módulo fotovoltaico es descripta a partir de dos coeficientes: α [mA/K] y β [mV/K] proporcionados por los fabricantes de paneles fotovoltaicos. Los fabricantes proporcionan, además, el coeficiente γ [%/K] que describe la variación del punto máximo de potencia sobre la característica P-V sobre un FV para diferentes temperaturas del mismo. El coeficiente α describe la variación de la corriente de cortocircuito con la temperatura. El coeficiente describe la reducción de la tensión a circuito abierto del módulo fotovoltaico a medida que la temperatura del mismo aumenta. Por lo tanto, la determinación de estos parámetros es muy importante para determinar el comportamiento de la característica I-V del generador en función de las variaciones de temperatura. El objetivo de este trabajo es desarrollar un equipo experimental para la determinación de los coeficientes α y β de módulos fotovoltaicos comerciales, que permiten la caracterización I-V de los mismos. A partir de estos coeficientes es posible además, el trazado de la curva estándar I-V para el módulo solar ensayado. Los resultados experimentales muestran un buen comportamiento del algoritmo implementado, y se proponen a futuro otras topologías en la etapa de potencia del equipo.One of the critical parameter that establishes the behavior of a photovoltaic (PV) generator is the working temperature because it influences the curve I-V of the P-V module. An increase in the temperature produces a maximum power reduction and as a consequence a significant performance decrease. The temperature influence on the I-V curve is described by two parameters, α [mA/K] and β [mV/K], which are typically given by the PV manufacturers. Coefficient α represents the short circuit variation with the temperature. Coefficient β represents the open circuit voltage changes with the temperature. That is the reason of the importance of these parameters determination on the maximum generation power calculation considering the temperature changes. The objective of this work is to develop a prototype to determine coefficients α and β of commercial PV modules, to determine the modules characteristics. The calculation allows building the module standardized I-V curve.Asociación Argentina de Energías Renovables y Medio Ambiente (ASADES

Power system reliability considering combined cycle plants

In the nineties in Argentina, the growth of thermal power generation was mainly based on combined cycle plants. Currently, one problem associated with the use of combined cycle plants is the fact that they need to share the use of natural gas with commercial, industrial and domestic uses. Hence, the natural gas availability is becoming a critical issue. Therefore, power system reliability studies must consider fuel availability into the models, and as a consequence, reliability models must take into account the joint operation of electrical generation and natural gas systems. The aim of this paper is to evaluate the influence of combined cycle plants on reliability studies applied to system generation capacity and their dependency on natural gas availability. Monte Carlo simulation method is used to determine reliability indices such as Loss of Load Expectation, Loss of Energy Expectation, Loss of Load Frequency, and Loss of Load Duration. The IEEE RTS 96 test system is used as the base system, with is modified in order to incorporate combined cycle plants.Fil: Alemany, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Nacional de Río Cuarto. Facultad de Ingeniería. Departamento de Electricidad y Electrónica; Argentina. Centro de Investigaciones Cientificas ; Facultad de Ciencias Exactas Fisicas y Naturales ; Universidad Nacional de Cordoba;Fil: Moitre, Diego Carlos Alberto. Universidad Nacional de Río Cuarto; Argentina. Pontificia Universidad Católica de Chile; ChileFil: Magnago, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Nacional de Río Cuarto. Facultad de Ingeniería. Departamento de Electricidad y Electrónica; Argentina. Centro de Investigaciones Cientificas ; Facultad de Ciencias Exactas Fisicas y Naturales ; Universidad Nacional de Cordoba; . Texas A&M University; Estados Unido

A importância das interações entre plantas e animais para a manutenção das espécies arbóreas ameaçadas no sul da Bahia

In the present study, we investigated the importance of mutualistic networks between plants and ani-mals for the maintenance of endangered tree species in southern Bahia. About 82% of the tree species under study are dispersed by animals, have an average diameter of 16.89 mm and their main dispers-ers are birds, primates and rodents (pacas). We reveal an intense relationship between endangered tree species in southern Bahia and seed-dispersing animals. The species in question already have threats inherent to their individual characteristics, but we demonstrate that one more factor can be added to these threats, the extinction of large seed dispersers.En el presente estudio investigamos la importancia de las redes mutualísticas entre plantas y animales para la manutención de especies arbóreas amenazadas de extinción en el sur de Bahia. Cerca del 82% de las especies arbóreas en estudio son dispersas por animales, presentan un diámetro promedio de 16.89 mm y poseen como principales dispersores aves, primates y roedores (pacas). Revelamos una intensa relación entre las especies arbóreas amenazadas de extinción en el sur de Bahia y animales dispersores de semillas. Las especies en cuestión ya poseen amenazas inherentes a sus características individuales, sin embargo, demostramos que un factor adicional puede ser agregado a estas amenazas, la extinción de grandes dispersores de semillas.No presente estudo investigamos a importância das redes mutualísticas entre plantas e animais para a manutenção de espécies arbóreas ameaçadas de extinção no Sul da Ba-hia. Cerca de 82% das espécies arbóreas em estudo são dispersas por animais, apresen-tam diâmetro médio de 16,89 mm e possuem como principais dispersores aves, prima-tas e roedores (pacas). Revelamos uma intensa relação entre as espécies arbóreas amea-çadas de extinção no Sul da Bahia e animais dispersores de sementes. As espécies em questão já possuem ameaças inerentes às suas características individuais, porém, de-monstramos que mais um fator pode ser agregado a essas ameaças, a extinção de gran-des dispersores de sementes

Multiobjective Optimization Model for Wind Power Allocation

There is an increasing need for the injection to the grid of renewable energy; therefore, to evaluate the optimal location of new renewable generation is an important task. The primary purpose of this work is to develop a multiobjective optimization model that permits finding multiple trade-off solutions for the location of new wind power resources. It is based on the augmented -constrained methodology. Two competitive objectives are considered: maximization of preexisting energy injection and maximization of new wind energy injection, both embedded, in the maximization of load supply. The results show that the location of new renewable generation units affects considerably the transmission network flows, the load supply, and the preexisting energy injection. Moreover, there are diverse opportunities to benefit the preexisting generation, contrarily to the expected effect where renewable generation displaces conventional power. The proposed methodology produces a diverse range of equivalent solutions, expanding and enriching the horizon of options and giving flexibility to the decision-making process

Effects of flaxseed supplementation on lipid metabolism, oxidative balance and genetic damage in goats

Epidemiological evidence indicates that flaxseed reduces oxidative stress and cholesterol levels in blood. In this study we evaluated the lipid profile, oxidation of plasma lipids and genetic damage in goats fed on a diet supplemented with flaxseed. Thirteen adult male goats were split in two experimental groups; one of them was fed on a conventional diet of alfalfa and ground corn and the other group was fed on the same diet supplemented with 5% of flaxseed. Blood samples were obtained every 7 days to quantify the Thiobarbituric Acid-Reactive Substances (TBARs), total cholesterol, HDL, LDL and triacylglycerols. Additionally, 3 blood samples and 3 oral mucosa samples were taken to each animal every 15 days to perform comet assay and micronucleus test. Flaxseed supplementation produces a remarkable antioxidant effect in plasma in a three months period that could explain the antigenotoxic effect determined through both micronucleus test and comet assay. In addition, we also found a reduction of LDL/HDL ratio and cholesterol levels in animals supplemented with flaxseed.Fil: Cecchini, Maria Eugenia. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria. Departamento de Clínica Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Roma, Dardo Andrés. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria. Departamento de Clínica Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Magnago, Franco. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria. Departamento de Clínica Animal; ArgentinaFil: Vilchez, Maria Laura. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Varea, María Cristina. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales; ArgentinaFil: Torreta, María Elena. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria; ArgentinaFil: Aiassa, Delia Elba. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales; ArgentinaFil: Mañas, Fernando Javier. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria. Departamento de Clínica Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentin

Psychological symptoms, mental fatigue and behavioural adherence after 72 continuous days of strict lockdown during the COVID-19 pandemic in Argentina

Background An early and prolonged lockdown was adopted in Argentina during the first wave of COVID-19. Early reports evidenced elevated psychological symptoms. Aims To explore if the prolonged lockdown was associated with elevated anxiety and depressive symptoms; if mental fatigue was associated with lockdown adherence (a phenomenon called ‘behavioural fatigue’); and if financial concerns were associated with lockdown adherence and emotional symptoms. Method The survey included standardised questionnaires to assess depressive (PHQ-9) and anxious (GAD-7) symptoms, mental fatigue, risk perception, lockdown adherence, financial concerns, daily stress, loneliness, intolerance to uncertainty, negative repetitive thinking and cognitive problems. LASSO regression analyses were carried out to predict depression, anxiety and lockdown adherence Results The survey reached 3617 adults (85.2% female) from all provinces of Argentina after 72 days of lockdown. Data were collected between 21 May 2020 and 4 June 2020. In that period, Argentina had an Oxford stringency index of 85/100. Of those surveyed, 45.6% and 27% met the cut-offs for depression and anxiety, respectively. Mental fatigue, cognitive failures and financial concerns were correlated with psychological symptoms, but not with adherence to lockdown. In regression models, mental fatigue, cognitive failures and loneliness were the most important variables to predict depression, intolerance to uncertainty and lockdown difficulty were the most important for anxiety, and perceived threat was the most important for predicting lockdown adherence. Conclusions During the extended lockdown, psychological symptoms increased, being enhanced by mental fatigue, cognitive difficulties and financial concerns. We found no evidence of behavioural fatigue. Thus, feeling mentally fatigued is not the same as being behaviourally fatigued.Fil: Torrente, Fernando Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; ArgentinaFil: Yoris Magnago, Adrián Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; ArgentinaFil: Low, Daniel Mark. Harvard Medical School; Estados Unidos. Massachusetts Institute of Technology; Estados UnidosFil: Lopez, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; ArgentinaFil: Bekinschtein, Pedro Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; ArgentinaFil: Vázquez, Gustavo H.. Queen's University Medical School; CanadáFil: Manes, Facundo Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; ArgentinaFil: Cetkovich Bakmas, Marcelo Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentin