State of the art and trends in the monitoring, detection and diagnosis of failures in electric induction motors

Producción CientíficaDespite the complex mathematical models and physical phenomena on which it is based, the simplicity of its construction, its affordability, the versatility of its applications and the relative ease of its control have made the electric induction motor an essential element in a considerable number of processes at the industrial and domestic levels, in which it converts electrical energy into mechanical energy. The importance of this type of machine for the continuity of operation, mainly in industry, is such that, in addition to being an important part of the study programs of careers related to this branch of electrical engineering, a large number of investigations into monitoring, detecting and quickly diagnosing its incipient faults due to a variety of factors have been conducted. This bibliographic research aims to analyze the conceptual aspects of the first discoveries that served as the basis for the invention of the induction motor, ranging from the development of the Fourier series, the Fourier transform mathematical formula in its different forms and the measurement, treatment and analysis of signals to techniques based on artificial intelligence and soft computing. This research also includes topics of interest such as fault types and their classification according to the engine, software and hardware parts used and modern approaches or maintenance strategies

Nuevo Modelo de Distribución de Corriente Contínua en Baja Tensión en Smart Buildings

En este trabajo se revisan una serie de conceptos, todos ellos relacionados con las microrredes de baja tensión de tipo de en corriente continua. Se exponen varias de las características propias de estas microrredes, diferentes tipos de cargas que alimentarían la microrred y posibles formas de conectar ésta al suministro. Se realiza un estudio de los niveles de potencia demandada más comunes, así como de las pérdidas en la red y las formas de evitar éstas, y cómo se generaría la corriente de la red de continua. Además, se exponen varios casos de estudios ya operativos sobre el modelo de continua

Fault Detection of Wind Turbine Induction Generators through Current Signals and Various Signal Processing Techniques

Producción CientíficaIn the wind industry (WI), a robust and effective maintenance system is essential. To minimize the maintenance cost, a large number of methodologies and mathematical models for predictive maintenance have been developed. Fault detection and diagnosis are carried out by processing and analyzing various types of signals, with the vibration signal predominating. In addition, most of the published proposals for wind turbine (WT) fault detection and diagnosis have used simulations and test benches. Based on previous work, this research report focuses on fault diagnosis, in this case using the electrical signal from an operating WT electric generator and applying various signal analysis and processing techniques to compare the effectiveness of each. The WT used for this research is 20 years old and works with a squirrel-cage induction generator (SCIG) which, according to the wind farm control systems, was fault-free. As a result, it has been possible to verify the feasibility of using the current signal to detect and diagnose faults through spectral analysis (SA) using a fast Fourier transform (FFT), periodogram, spectrogram, and scalogram

Maintenance models applied to wind turbines. A comprehensive overview

Producción CientíficaWind power generation has been the fastest-growing energy alternative in recent years, however, it still has to compete with cheaper fossil energy sources. This is one of the motivations to constantly improve the efficiency of wind turbines and develop new Operation and Maintenance (O&M) methodologies. The decisions regarding O&M are based on different types of models, which cover a wide range of scenarios and variables and share the same goal, which is to minimize the Cost of Energy (COE) and maximize the profitability of a wind farm (WF). In this context, this review aims to identify and classify, from a comprehensive perspective, the different types of models used at the strategic, tactical, and operational decision levels of wind turbine maintenance, emphasizing mathematical models (MatMs). The investigation allows the conclusion that even though the evolution of the models and methodologies is ongoing, decision making in all the areas of the wind industry is currently based on artificial intelligence and machine learning models

Diagnosis of broken bars in wind turbine squirrel cage induction generator: Approach based on current signal and generative adversarial networks

Producción CientíficaTo ensure the profitability of the wind industry, one of the most important objectives is to minimize maintenance costs. For this reason, the components of wind turbines are continuously monitored to detect any type of failure by analyzing the signals measured by the sensors included in the condition monitoring system. Most of the proposals for the detection and diagnosis of faults based on signal processing and artificial intelligence models use a fault-free signal and a signal acquired on a system in which a fault has been provoked; however, when the failures are incipient, the frequency components associated with the failures are very close to the fundamental component and there are incomplete data, the detection and diagnosis of failures is difficult. Therefore, the purpose of this research is to detect and diagnose failures of the electric generator of wind turbines in operation, using the current signal and applying generative adversarial networks to obtain synthetic data that allow for counteracting the problem of an unbalanced dataset. The proposal is useful for the detection of broken bars in squirrel cage induction generators, which, according to the control system, were in a healthy state

Simulation of a solar-assisted air-conditioning system applied to a remote school

Producción CientíficaIn this work, we present an absorption cooling system with 35 kW capacity driven by solar thermal energy, installed in the school of Puertecitos, Mexico, an off-grid community with a high level of social marginalization. The cooling system provides thermal comfort to the school’s classrooms through four 8.75-kW cooling coils, while a 110-m2 field of evacuated tube solar collectors delivers the thermal energy needed to activate the cooling machine. The characteristics of the equipment installed in the school were used for simulation and operative analysis of the system under the influence of typical factors of an isolated coastal community, such as the influence of climate, thermal load, and water consumption in the cooling tower, among others. The aim of this simulation study was to determine the best operating conditions prior to system start-up, to establish the requirements for external heating and cooling services, and to quantify the freshwater requirements for the proper functioning of the system. The results show that, with the simulated strategies implemented, with a maximum load operation, the system can maintain thermal comfort in the classrooms for five days of classes. This is feasible as long as weekends are dedicated to raising the water temperature in the thermal storage tank. As the total capacity of the system is distributed in the four cooling coils, it is possible to control the cooling demand in order to extend the operation periods. Utilizing 75% or less of the cooling capacity, the system can operate continuously, taking advantage of stored energy. The cooling tower requires about 750 kg of water per day, which becomes critical given the scarcity of this resource in the community.CONACYT-SENER-SUSTENTABILIDAD ENERGÉTICA (project P09)Programa Iberoamericano de Ciencia y Tecnología para el Desarrollo (project 518RT0558

Study of unwanted emissions in the CENELEC-A band generated by distributed energy resources and their influence over narrow band power line communications

Producción CientíficaDistributed Energy Resources might have a severe influence on Power Line Communications, as they can generate interfering signals and high frequency emissions or supraharmonics that may cause loss of metering and control data. In this paper, the influence of various energy resources on Narrowband Power Line Communications is described and analyzed through several test measurements performed in a real microgrid. Accordingly, the paper describes the effects on smart metering communications through the Medium Access Control (MAC) layer analysis. Results show that the switching frequency of inverters and the presence of battery chargers are remarkable sources of disturbance in low voltage distribution networks. In this sense, the results presented can contribute to efforts towards standardization and normative of emissions at higher frequencies higher, such as CENELEC EN 50160 and IEC/TS 6274

The profile of studies on renewable energy in sustainable supply chain

Over the years, has been growing policies aiming toreducethe green-houses gases emissions–GHG, which lead for the searching ofsustainable alter-native solutions. One waymitigatesthe GHG emissionsisthe use of renewable energy sources. Nevertheless, for the use of such resources there are a series of processes inherent to the energy production and consumption, being the supply chain one of the principals. Based on this, the main objective of present article is tomapthe roleof renewable energies inside the context of sustainable supply chain, observing how the studies have been developed, looking for the main re-searchers, organizations andcollaboration networks, being at final a mapping of the 15 most cited studies in area. The research was carried out with the papers published atWeb of Science database, using VantagePoint software to quantify the information’s, including the evolution of studies over time until 2019.It was possible to perceivethat the researchhasbeen growingsince 2010, moreover, subjects related to biomass, biofuels and photovoltaic energy were the most re-currentat the most cited. However, within this framework, the theme presented itself as new and that there are still great potentials to be exploredThe authors would like to thank CNPqby the scholarship awarded, IFRJfor the availability of VantagePoint softwareand the project “Ciudades Inteligentes, total-mente integrales, eficiente y sostenibles (CITIES), n. de processo: 518RT0557”.info:eu-repo/semantics/publishedVersio

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

Study of a hybrid solar absorption-cooling and flash-desalination system

Producción CientíficaIn this work, the analysis of a hybrid LiBr/H2O absorption-cooling and flash-desalination system, using solar thermal energy as heat source, is presented. An absorption open-cycle with three pressure levels is used in combination with a single-stage flash-desalination process to use the coolant as product water, resulting in an increase in cooling and desalination efficiency. For the application, a 20-room coastal hotel complex in San Felipe, Baja California, Mexico, is taken as a case study and the sizing of the solar collection and storage system is carried out for the operation of the proposed hybrid system, during the summer operative period. The operational dynamics during the week with the highest ambient temperatures are presented. The dimensioning of the solar collector’s area and the energy storage resulted in a collection area of 620 m2 with 30 m3, respectively, reaching a solar fraction of 69%. The absorption-cooling subprocess showed an increase of 13.88% in the average coefficient of performance (COP) compared to conventional LiBr/H2O absorption systems. Also, considering that the system provides cooling and desalination simultaneously, the average COPG is 1.64, which is 2.27 times higher than the COP of conventional LiBr/H2O single-effect absorption units. During the critical week, the system presented a desalinated water production of 16.94 m3 with an average performance ratio (PR) of 0.83, while the average daily water production was 2406 kg/day; enough to satisfy the daily water requirements of four people in a coastal hotel in Mexico or to cover the basic services of 24 people according to the World Health Organization