A study of the effects of time aggregation and overlapping within the framework of IEC standards for the measurement of harmonics and interharmonics

Producción CientíficaThe increasing incorporation of power electronics and other non-linear loads, in addition to their energy advantages, also implies a poor power quality, especially as regards harmonic pollution. Different solutions have been proposed to measure harmonic content, taking the International Electrotechnical Commission (IEC) standards as a reference. However, there are still some issues related to the measurement of the harmonic, and especially, interharmonic content. Some of those questions are addressed in this work, such as the problem derived from the instability of the values obtained by applying the discrete Fourier transform to each sampling window, or the appearance of local peaks when there are tones separated by multiples of the resolution. Solutions were proposed based on time aggregation and the overlapping of windows. The results demonstrate that aggregation time, window type, and overlapping can improve the accuracy in harmonic measurement using Fourier transform-based methods, as defined in the standards. The paper shows the need to consider spectral and time groupings together, improving results by using an appropriate percentage of overlap and an adaptation of the aggregation time to the harmonic content

Analysis of the use of the Hanning Window for the measurement of interharmonic distortion caused by close tones in IEC standard framework

Producción CientíficaThe widespread use of devices based on power electronics and other nonlinear loads has led to an increase in harmonic distortion that affects the quality of power systems. Therefore, the correct measurement of harmonic and interharmonic content is necessary. The International Electrotechnical Commission (IEC) standards define the concepts of spectral and time grouping required for such measurements. This paper demonstrates that the procedures defined in the IEC standards are not sufficiently accurate when several close interharmonic tones interact due to the lack of stability of the values that the Discrete Fourier Transform obtains in each sampling window, and to the inaccuracy in the measurement of interharmonic groups and rates when using the Hanning window. This paper proposes novel solutions based on time aggregation and the use of other groupings and alternative windows. The results obtained are compared with the results produced by applying the rectangular window indicated in the standards, using sensitivity analysis varying one of the tones and using experimental results measuring the output signals of frequency inverters driving induction motors. The proposed method achieves greater accuracy and stability in the measurement of spectral groupings and their related distortion rates in signals with abundant and dispersed interharmonic content

Conversion of a network section with loads, storage systems and renewable generation sources into a smart microgrid

This paper shows an experimental application case to convert a part of the grid formed by renewable generation sources, storage systems, and loads into a smart microgrid. This transformation will achieve greater efficiency and autonomy in its management. If we add to this the analysis of all the data that has been recorded and the correct management of the energy produced and stored, we can achieve a reduction in the electricity consumption of the distribution grid and, with this, a reduction in the associated bill. To achieve this transformation in the grid, we must provide it with intelligence. To achieve this, a four steps procedure are proposed: identification and description of the elements, integration of the elements in the same data network, establishing communication between the elements and the control system, creating an interface that allows control of the entire network. The microgrid of CEDER-CIEMAT (Renewable Energy Centre in Soria, Spain) is presented as a real case study. This centre is made up of various sources of generation, storage, and consumption. All the elements that make up the microgrid are incorporated into free software, Home Assistant, allowing real-time control and monitoring of all of them thanks to the intelligence that has been provided to the grid. The novelty of this paper is that it describes a procedure that is not reported in the current literature and that, being developed with Home Assistant, is free and allows the control and management of a microgrid from any device (mobile, PC) and from any place, even though not on the same data network as the microgrid.Peer ReviewedObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No ContaminantPostprint (published version

Power consumption analysis of electrical installations at healthcare facility

Producción CientíficaThis paper presents a methodology for power consumption estimation considering harmonic and interharmonic content and then it is compared to the power consumption estimation commonly done by commercial equipment based on the fundamental frequency, and how they can underestimate the power consumption considering power quality disturbances (PQD). For this purpose, data of electrical activity at the electrical distribution boards in a healthcare facility is acquired for a long time period with proprietary equipment. An analysis in the acquired current and voltage signals is done, in order to compare the power consumption centered in the fundamental frequency with the generalized definition of power consumption. The results obtained from the comparison in the power consumption estimation show differences between 4% and 10% of underestimated power consumption. Thus, it is demonstrated that the presence of harmonic and interharmonic content provokes a significant underestimation of power consumption using only the power consumption centered at the fundamental frequency.SEP-CONACYT, under grant 222453-2013FOMIX, under grant QRO-2014-C03-250269FOFIUAQ-FIN20161

Fundamental frequency suppression for the detection of broken bar in induction motors at low slip and frequency

Producción CientíficaBroken rotor bar (BRB) is one of the most common failures in induction motors (IMs) these days; however, its identification is complicated since the frequencies associated with the fault condition appear near the fundamental frequency component (FFC). This situation gets worse when the IM slip or the operation frequency is low. In these circumstances, the common techniques for condition monitoring may experience troubles in the identification of a faulty condition. By suppressing the FFC, the fault detection is enhanced, allowing the identification of BRB even at low slip conditions. The main contribution of this work consists of the development of a preprocessing technique that estimates the FFC from an optimization point of view. This way, it is possible to remove a single frequency component instead of removing a complete frequency band from the current signals of an IM. Experimentation is performed on an IM operating at two different frequencies and at three different load levels. The proposed methodology is compared with two different approaches and the results show that the use of the proposed methodology allows to enhance the performance delivered by the common methodologies for the detection of BRB in steady state.CONACyT scholarship (415315)Project FOFI-UAQ 2018 FIN201812PRODEP UAQ-PTC-385 gran

Identification of the electrical load by C-means from non-intrusive monitoring of electrical signals in non-residential buildings

Producción CientíficaLa acción combinada de diferentes equipos conectados a una instalación eléctrica es capaz de provocar cambios inesperados en el tipo de carga dentro de la instalación; estas variaciones de carga son responsables de algunas fallas eléctricas. En este artículo se presenta una metodología para clasificar e identificar los tipos de carga en entornos industriales. Las cantidades de energía (EPQ) y los valores actuales se utilizan para establecer índices con el fin de utilizarlos como características para un algoritmo C-means y realizar la clasificación de carga. La experimentación se realiza en un centro de salud recogiendo datos eléctricos en diferentes tableros de distribución eléctrica. Los resultados obtenidos del método de clasificación muestran variaciones en el comportamiento de la carga a lo largo del día. Además, algunas clases se pueden utilizar para reconocer equipos en la instalación eléctrica para su posterior inspección o detección de fallas

Spectral kurtosis based methodology for the identification of stationary load signatures in electrical signals from a sustainable building

Producción CientíficaThe increasing use of nonlinear loads in the power grid introduces some unwanted effects, such as harmonic and interharmonic contamination. Since the existence of spectral contamination causes waveform distortion that may be harmful to the loads that are connected to the grid, it is important to identify the frequency components that are related to specific loads in order to determine how relevant their contribution is to the waveform distortion levels. Due to the diversity of frequency components that are merged in an electrical signal, it is a challenging task to discriminate the relevant frequencies from those that are not. Therefore, it is necessary to develop techniques that allow performing this selection in an efficient way. This paper proposes the use of spectral kurtosis for the identification of stationary frequency components in electrical signals along the day in a sustainable building. Then, the behavior of the identified frequencies is analyzed to determine which of the loads connected to the grid are introducing them. Experimentation is performed in a sustainable building where, besides the loads associated with the normal operation of the building, there are several power electronics equipment that is used for the electric generation process from renewable sources. Results prove that using the proposed methodology it is possible to detect the behavior of specific loads, such as office equipment and air conditioning.Universidad de Valladolid y Consejo Mexicano de Ciencia y Tecnología (CONACYT) - (grant 743842)Universidad Autónoma de Querétaro, Fondo para el Desarrollo del Conocimiento (FONDEC-UAQ 2020) - (project FIN202011

VirMALee : guía didáctica en CD sobre máquinas eléctricas

Realizado en la E.T.S. de Ingenieros Industriales de la Universidad de Valladolid, por 3 profesores del centro, para la asignatura de Máquinas Eléctricas del tercer curso de Ingeniero Industrial. Los objetivos propuestos son: fomentar el interés del alumno por las máquinas eléctricas, introducir una nueva metodología de enseñanza-aprendizaje, diversificar actividades para aumentar el rendimiento, diseñar mecanismos de actualización y servir de apoyo a la docencia. Para ello, se ha elaborado una guía tutorial sobre la asignatura. Se ha distribuido al alumnado como material didáctico de la misma. Está almacenada en un CD y también es posible su descarga a través de la página Web de la asignatura. Contiene toda la documentación de la asignatura, todos los exámenes realizados hasta la fecha, para resolver y resueltos, un manual tutorial teórico interactivo y del orden de 60 problemas, también para resolver y resueltos. Aunque la guía definitiva se ha distribuido al principio del curso 2004/2005, y por tanto, no se pueden hacer valoraciones sobre su utilización aún, si que es importante resaltar el número de peticiones del CD, 103. Por otra parte, el número de alumnos que este curso han registrado su dirección electrónica con objeto de recibir información sobre la asignatura ha aumentado en un 52 por ciento respecto del curso pasado.Junta de Castilla y León. Consejería de Educación y CulturaCastilla y LeónJunta de Castilla y León. Consejería de Educación y Cultura; Monasterio de Nuestra Señora de Prado. Autovía Puente Colgante, s. n.; 47071 Valladolid; Tel. +34983411881; Fax +34983411939; [email protected]

Analysis of the behavior of MVDC system in a distributiongrid compared to a UPFC system

Producción CientíficaThe increase in electricity demand, the incorporation of renewable energies, orthe trend toward deregulation in the power market, implies significantchanges in the power networks. Load flows are considerably altered, givingrise to technical problems in the system, such as stability limitations or voltagelevel control. In this context, the use of devices based on power electronics tointerconnect distribution grids is presented as an excellent option to help solvethese problems and control load flows and bus voltages. The topology MVDC(Medium Voltage Direct Current) is starting to be considered an option forenhancing transfer capacity and providing increased power quality at distribu-tion grids. However, this technology is still immature and relati vely unknown,for this reason, the main motivation of the article is to help spread the benefitsof integrating this technology in distribution grid and to determine the capabil-ity of the MVDC to control active and reactive power in distribution grid aswell as its behavior in the event of a short-circuit. The main novelty is to ana-lyze the behavior of the MVDC through a case study, based on a real situation,but comparing it with one of the most complete and flexible FACTS devices,Unified Power Flow Controller (UPFC), noting that MVDC technology is abetter option for operation in medium voltage networks, since allows the con-trol of the active and reactive powers independently and in the case of a short-circuit acts on the currents circulating through the electrical line mitigatingthe effect caused by the fault

A data-driven forecasting strategy to predict continuous hourly energy demand in smart buildings

Smart buildings seek to have a balance between energy consumption and occupant com-fort. To make this possible, smart buildings need to be able to foresee sudden changes in the build-ing’s energy consumption. With the help of forecasting models, building energy management sys-tems, which are a fundamental part of smart buildings, know when sudden changes in the energy consumption pattern could occur. Currently, different forecasting methods use models that allow building energy management systems to forecast energy consumption. Due to this, it is increasingly necessary to have appropriate forecasting models to be able to maintain a balance between energy consumption and occupant comfort. The objective of this paper is to present an energy consumption forecasting strategy that allows hourly day-ahead predictions. The presented forecasting strategy is tested using real data from two buildings located in Valladolid, Spain. Different machine learning and deep learning models were used to analyze which could perform better with the proposed strategy. After establishing the performance of the models, a model was assembled using the mean of the prediction values of the top five models to obtain a model with better performance. © 2021 by the authors. Licensee MDPI, Basel, Switzerlan