ABSTRACT. There are various methods and equipment for measure greenhouse variables with IoT, however, most of them have disadvantages such as: expensiveness, limited coverage, or no update capacity through new technologies. Hence, this article aims to explain the development of a greenhouse variable measurement system, whose magnitudes will be recorded in a database to later be accessed from a device connected to the internet, with the possibility of reconfigure it in order to measure other variables and/or adapt it to other sensors. A methodology for the use of a FPGA based data acquisition and processing card, in addition to a Raspberry-Pi Iot system are described, with which it is sought to establish communication with the measurement sensors: TMP006 (non-invasive IR temperature), TSL230 (solar radiation), SHT75 (air temperature and relative humidity), and FC-28 (soil humidity). The developed system stores the acquired information in a database located on local and external servers using open-source code. Communication protocols are used to measure the variables. Statistical tests were performed for the monitored data, verifying its accuracy. The performance of the sensors reached correlations over .9 in most of the cases. Lower correlations and significant measurement errors depend specifically on the selected sensor.

ABSTRACT. With the incorporation of Information and Communication Technologies into the Electric Grids, the concept of Smart Electric Grids arises. One of the main components in Smart Grid is the use of Embedded Systems that allow the processing and communication of a great diversity of information and applications. However, the use of Information and Communication Technologies in the Smart Grid also brings a series of new challenges, one of them, cybersecurity. When processing and communicating information between the various devices that make up the SG, the information needs to be confidential, comprehensive, and available at all times. Cyber Security in SG has been a subject little studied in Intelligent Measurement Systems. Cryptography techniques require high computational capabilities since complex mathematical operations are performed. Unfortunately, these new embedded devices have limited capacity for processing, storage, energy, among others. This article presents a study of cryptographic techniques to implement them in embedded devices (Raspberry Pi), a comparison is made of algorithms that can be used in smart meters to provide authenticity to said devices.

ABSTRACT. In this paper we present the design of a smart device for energy consumption monitoring in real time. The hardware of this device is based on low cost components such as the micro-controller NodeMcu ESP8266. The firmware installed in the micro-controller allows us to implement an IoT architecture to transmit the data obtained by the sensors to the web server. The data storage are visualised in real time using a Website. We use open source platforms such as HTML, PHP, MySQL database and the language programming Python. We implement a Multilayer Perceptron for recognising the home appliance operating with the IoT device, which includes a wide variety of appliances. We believe the recognition capability is an important functionality for the user in order to better understand the energy consumption process. The system can assign to each home appliance its energy consumption value without user intervention in the database.

ABSTRACT. Machine learning is widely used to create mathematical models that explain or predict events based on previous observations. Within the most used algorithms are the naive Bayesian classifier, K- nearest neighbors or vector support machines. An area of potential application is behavioral pharmacology, that evaluates the behavior of experimental subjects injected with different substances to identify beneficial or toxic effects. Present study, classical statistical and machine learning techniques were used to evaluate the effect of progesterone (0.5 and 2 mg / kg) in the raised arms and open field maze. The results were compared between both data analysis approaches, identifying an anxiolytic-like effect of the 2 mg / kg dose of progesterone, similar to that produced by diazepam. The results of the analysis using classical statistical techniques show an anxiolytic-like effect of progesterone at a dose of 2 mg / kg. Consistently the machine learning techniques identified this effect, and further allowed generating predictive models with a reduced number of variables. This enabled automatically identify the variables that provide more information to differentiate the experimental groups.

ABSTRACT. This document presents the development of the first prototype of an IoT system usig LoRa communication and FIWARE services. The information obtenained by LoRa’s Open Source components and services, LoRaWAN and ChirpStack, is transferred to the Orion Context Broker (OCB) and then is used in the different services of FIWARE CrateDB and Grafana, used for storage and data visualization. Finally in results are shown the data collection carried out from the city of Aguascalientes, Mexico, where geolocation and humidity and temperature sensors were used and connected to SODAQ ExpLoRer Cards

ABSTRACT. In this paper, a control strategy for a battery charger is developed. The battery charger is composed by cascade connection of two power converters; the first one is based on the traditional H-bridge converter topology that performs the rectification function and the second is a bidirectional DC-DC converter that behaves as a buck converter to charge a battery bank. The proposed control methodology for the battery charger is composed of three loops, referred as power factor correction loop performed by a proportional-resonant controller that guarantees the tracking of a desired grid current reference. A voltage regulation loop conformed by a PI controller is proposed to regulate the DC-Link, which is the middle stage that links the PFC stage with the DC-DC stage. For the battery charging stage, a PI controller is implemented to guarantee a constant input current to the battery bank. Also, an external loop to generate the current reference on the constant voltage mode is proposed. Numerical simulations are performed to evaluate the performance of the proposed control strategy.

ABSTRACT. This paper shows a high-power resonant converter applied to an induction steel-melting furnace. Resonant DC-DC converters are increasingly used in applications that require high-power density and high-efficiency. At the same time, a control system for the series resonant converter is introduced in order to reduce the switching power losses. The main advantage of resonant converters is their soft-switching which solves the problem of high-frequency operation. The resonant load topology is also studied and applied. In this way, zero-voltage switching (ZVS) is achieved in the H-bridge converter. This control algorithm aims to achieve its optimum operating point. In this case, the operating frequency in the resonant converter can vary over a wide range during the melting cycle in the induction furnace. The resonant converter has variable frequency control and phase-shift modulation so that the LLC resonant tank can operate at the resonance point in the load. Matlab-Simulink has been the software used to develop the high-power resonant converter, as well as to support the previous analysis. The simulation results obtained are shown in the paper.

ABSTRACT. This paper analyzes the stability of a PI controller for the input voltage regulation of a three-phase two-level inverter within a PV application. The stability analysis is carried out through the Hermite-Biehler criterion, which is used in the parameterization of a robust region in which the system is stable. The stability region gives all the proportional and integral gains of the PI controller that stabilize the linearized closed-loop system. Simulation results show that the system is stable under power changes in the PV array.

ABSTRACT. To guarantee the adequate interaction among controllers and systems in order to be controlled, it is imperative that the design, implementation and traditional testing of control algorithms depending on the plant are performed. It is not always posible to have the actual plant for initial testing, algorithm debugging and controller adjustments, nor is it safe, as it is economically and operationally impractical, as well as risky. Using scale plants is costly and time-consuming and it does not completely eliminate the inherent danger of disruptions and failures caused by testing algorithms. A major drawback of testing is the imperative need for interaction between the controller and the plant to be controlled, the above in order to achieve reliable and safe controller settings. To mend this drawback, there are different alternatives; among them, the processor-in-the-loop (PIL) approach, which allows the observation of more realistic performance of the algorithms at an affordable cost. This paper presents an implementation guide for the PIL approach between Matlab / Simulink and Texas Instruments' C2000 family control hardware. This approach is applied to the evaluation of distributed generation units of synchronization algorithms. In particular, two algorithms for phase-locked loops (PLL) are considered: DSOGI-PLL and DSOGI-PLL with FLL; The Matlab / Simulink PLL is used to validate the implementations, but the latter is not processed in PIL. The PLLs are processed in a digital signal controller (DSCs) and the inverter and electrical power system (IEP Systems) are implemented in Simulink.

ABSTRACT. This paper addresses the problem of sinusoidal voltage generation in linear loads using a voltage source inverter (VSI). The port-Hamiltonian structure in open-loop is used to design a passivity-based controller with proportional-integral gains (PI-PBC) in order to develop the control strategy. The main advantage of using passivity-based controllers corresponds to the possibility of guaranteeing asymptotic stability by transforming the trajectory tracking problem into a regulation control one. In addition to the PI-PBC, a linear load estimator is employed based on an integral formulation to determine the value of the equivalent conductance in the load, which reduces the number of current sensors. Numerical validations demonstrate that the sinusoidal voltage provided by the VSI to the load has a tracking error lower than $1~\%$, with harmonic distortions lower than $2.6~\%$, both for voltage and currents in the load. All the simulations were conducted in MATLAB/Simulink using the SimPowerSystems library version 2017$a$.

ABSTRACT. Nowadays, the integration of renewable energy sources in electrical systems has significantly increased planning tasks. Due to the greater complexity that these studies imply, different computational and mathematical strategies must be used. Therefore, the analysis of electrical systems that integrate alternative forms of generation is of interest, and, in turn, the study of the environmental impact that the integration of said forms of generation entails is also essential. In this paper, a solution to the Environmental Economic Dispatch problem is obtained, considering the integration of wind energy. The solution to the proposed mathematical models is carried out through a free software computing platform; this platform is Scilab. Test scenarios with thermal generation units and wind farms are analyzed. The results presented allow us to analyze the impact of the integration of wind energy in power generation, generation costs, and polluting emissions.

ABSTRACT. Transmission systems are exposed to faults due to a variety of phenomena such as lightning, electrical component faults, aging equipment, and human error. Despite this, the electrical systems must have the ability to remain reliably and safely during all possible operating conditions. This fact requires advanced protection systems that must open circuit breakers in the case of a fault, in addition to having a quick repair strategy. In a such sense, many methods have been developed to locate and detect faults in transmission and distribution systems. The methods can be divided into several categories, techniques that use impedance, methods that make use of transient signals, techniques based on artificial intelligence, among other approaches. This work reviews most of the techniques that have been developed and that are commonly used to locate and detect faults in transmission systems. Therefore, from this review, opportunities in the area of investigation of fault location in the power transmission and distribution system can be further explored.

ABSTRACT. This paper presents the design of a converter for handling fixtures type LEDs suspension heights used in industry. The power converter is powered from the 480 V AC mains and provides an output voltage of 48 V DC, it has a power factor greater than 0.9 for a power of 150W. The converter is composed of two stages: the first is a SEPIC operating in continuous conduction mode, the integrated UC3853 is used to correct the power factor and the second stage is a full bridge converter operating in continuous conduction mode for the management of the array of LEDs, this stage has the ability to dimming. The design of each stage and the simulations in the LTspice software are presented considering the models of real components to reduce the time in their implementation.

ABSTRACT. The extensive use of power converters inside most of the electrical and electronic appliances has increased demand in the last few years so for getting this DC power, an interface must be provided between the AC power line and load requiring DC voltage. Conventional AC/DC conversion involves diode rectifiers with a large capacitor to reduce DC voltage ripple. Therefore, there is a need to ensure that the current harmonics of any equipment connected to AC main line are limited to comply with the regulatory standard. This requirement is satisfied by introducing some form of Power Factor Correction (PFC) techniques to make the input current sinusoidal and reduce the harmonics. The most popular topology for active PFC is boost converter as it draws continuous input current. In this paper, single-phase power factor correction using a boost converter is presented for grid-interface DC applications. The operating principles are detailed and described, as well as the design considerations of the proposed controller. The proposed power converter control and operation are verified experimentally using a 50W prototype

ABSTRACT. Nowadays the use of batteries as energy storage systems has increased, however, it is essential to manage the stored or released energy to obtain the maximum storage capacity and at the same time extend the useful life of the battery. Battery management systems control power flow based on load requirements and also on the knowledge of the state of the battery. The state of the battery is determined by variables such as the state of charge, the state of health and the state of operation. However, since they are internal states that can only be estimated from external variables such as the current and voltage of the battery, it is necessary to carry out an identification of the parameters of a given battery based, for example, on an equivalent electrical circuit model or of other type. Model parameters can be obtained using various identification methods. This paper reviews some of the most common methodologies and power converters used which are found in the specialized literature for the identification of the parameters of the battery model and their main features are compared.