Departamento de Ingeniería Eléctrica

URI permanente para esta comunidadhttps://hdl.handle.net/10953/37

En esta Comunidad se recogen los documentos generados por el Departamento de Ingeniería Eléctrica y que cumplen los requisitos de Copyright para su difusión en acceso abierto.

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Mostrando 1 - 13 de 13

A Platform for Analysing Huge Amounts of Data from Households, Photovoltaics, and Electrical Vehicles: From Data to Information
(MDPI, 2022-12-01) Cano-Ortega, Antonio; García-Cumbreras, Miguel Ángel; Sánchez-Sutil, Francisco; de-la-Casa-Hernández, Jesús
Analytics is an essential procedure to acquire knowledge and support applications for determining electricity consumption in smart homes. Electricity variables measured by the smart meter (SM) produce a significant amount of data on consumers, making the data sets very sizable and the analytics complex. Data mining and emerging cloud computing technologies make collecting, processing, and analysing the so-called big data possible. The monitoring and visualization of information aid in personalizing applications that benefit both homeowners and researchers in analysing consumer profiles. This paper presents a smart meter for household (SMH) to obtain load profiles and a new platform that allows the innovative analysis of captured Internet of Things data from smart homes, photovoltaics, and electrical vehicles. We propose the use of cloud systems to enable data-based services and address the challenges of complexities and resource demands for online and offline data processing, storage, and classification analysis. The requirements and system design components are discussed.
Calibration of a Class A Power Quality Analyser Connected to the Cloud in Real Time
(MDPI, 2024-08-13) Cano-Ortega, Antonio; Sánchez-Sutil, Francisco; Casa-Hernández, Jesús; Baier, Carlos; Gilabert-Torres, Carlos
Power quality measurements are essential to monitor, analyse and control the operation of smart grids within power systems. This work aims to develop and calibrate a PQ network analyser. As the penetration of non-linear loads connected to power systems is increasing every day, it is essential to measure power quality. In this sense, a power quality (PQ) analyser is based on the high-speed sampling of electrical signals in single-phase and three-phase electrical installations, which are available in real time for analysis using wirelessWi-Fi (Wireless-Fidelity) networks. The PQAE (Power Quality Analyser Embedded) power quality analyser has met the calibration standards for Class A devices from IEC 61000-4-30, IEC 61000-4-7 and IEC 62586-2. In this paper, a complete guide to the tests included in this standard has been provided. The Fast Fourier Transform (FFT) obtains the harmonic components from the measured signals and the window functions used reduce spectral leakage. The window size depends on the fundamental frequency of, intensity of and changes in the signal. Harmonic measurements from the 2nd to 50th harmonics for each phase of the voltage and each phase and neutral of the current have been performed, using the Fast Fourier transform algorithm with various window functions and their comparisons. PQAE is developed on an open-source platform that allows you to adapt its programming to the measurement needs of the users.
Design and Implementation of a Smart Energy Meter Using a LoRa Network in Real Time
(MDPI, 2021-12-17) Sánchez-Sutil, Francisco; Cano-Ortega, Antonio; de-la-Casa-Hernández, Jesús
Nowadays, the development, implementation and deployment of smart meters (SMs) is increasing in importance, and its expansion is exponential. The use of SMs in electrical engineering covers a multitude of applications ranging from real-time monitoring to the study of load profiles in homes. The use of wireless technologies has helped this development. Various problems arise in the implementation of SMs, such as coverage, locations without Internet access, etc. LoRa (long range) technology has great coverage and equipment with low power consumption that allows the installation of SMs in all types of locations, including those without Internet access. The objective of this research is to create an SM network under the LoRa specification that solves the problems presented by other wireless networks. For this purpose, a gateway for residential electricity metering networks using LoRa (GREMNL) and an electrical variable measuring device for households using LoRa (EVMDHL) have been created, which allow the development of SM networks with large coverage and low consumption.
Design and Testing of a Power Analyzer Monitor and Programming Device in Industries with a LoRA LPWAN Network
(MDPI, 2021-02-11) Sánchez-Sutil, Francisco; Cano-Ortega, Antonio
Electrical installations represent an important part of the industry. In this sense, knowing the state of the electrical installation in real time through the readings of the installed power analyzers is of vital importance. For this purpose, the RS485 bus can be used, which most electrical installations already have. An alternative to the bus wiring and its distance limitation is the use of low-power wide area networks (LPWAN). The long range (LoRa) protocol is ideal for industries due to its low-power consumption and coverage of up to 10 km. In this research, a device is developed to control all the reading and programming functions of a power analyzer and to integrate the device into the LoRa LPWAN network. The power analyzer monitor and programming device (PAMPD) is inexpensive and small enough to be installed in electrical panels, together with the power analyzer, without additional wiring. The information collected is available in the cloud in real time, allowing a multitude of analysis be run and optimization in real time. The results support high efficiency in information transmission with average information loss rate of 3% and a low average transmission time of 30 ms.
Development and Calibration of an Open Source, Low-Cost Power Smart Meter Prototype for PV Household-Prosumers
(MDPI, 2019-08-07) Sánchez-Sutil, Francisco; Cano-Ortega, Antonio; de-la-Casa-Hernández, Jesús; Rus-Casas, Catalina
Smart meter roll-out in photovoltaic (PV) household-prosumers provides easy access to granular meter measurements, which enables advanced energy services. The design of these services is based on the training and validation of models. However, this requires temporal high-resolution data for generation/load profiles collected in real-world household facilities. For this purpose, this research developed and successfully calibrated a new prototype for an accurate low-cost On-time Single-Phase Power Smart Meter (OSPPSM), which corresponded to these profiles. This OSPPSM is based on the Arduino open-source electronic platform. Not only can it locally store information, but can also wirelessly send these data to cloud storage in real-time. This paper describes the hardware and software design and its implementation. The experimental results are presented and discussed. The OSPPSM demonstrated that it was capable of in situ real-time processing. Moreover, the OSPPSM was able to meet all of the calibration standard tests in terms of accuracy class 1 (measurement error 1%) included in the International Electrotechnical Commission (IEC) standards for smart meters. In addition, the evaluation of the uncertainty of electrical variables is provided within the context of the law of propagation of uncertainty. The approximate cost of the prototype was 60 € from eBay stores.
Energy Management Model for a Remote Microgrid Based on Demand-Side Energy Control
(MDPI, 2023-12-28) Benavides, Darío; Arévalo, Paul; Cano-Ortega, Antonio; Sánchez-Sutil, Francisco; Villa-Ávila, Edisson
The internet of things is undergoing rapid expansion, transforming diverse industries by facilitating device connectivity and supporting advanced applications. In the domain of energy production, internet of things holds substantial promise for streamlining processes and enhancing efficiency. This research introduces a comprehensive monitoring and energy management model tailored for the University of Cuenca’s microgrid system, employing internet of things and ThingSpeak as pivotal technologies. The proposed approach capitalizes on intelligent environments and employs ThingSpeak as a robust platform for presenting and analyzing data. Through the integration of internet of things devices and sensors, the photovoltaic system’s parameters, including solar radiation and temperature, are monitored in real time. The collected data undergo analysis using sophisticated models and are presented visually through ThingSpeak, facilitating effective energy management and decision making. The developed monitoring system underwent rigorous testing in a laboratory microgrid setup, where the photovoltaic system is interconnected with other generation and storage systems, as well as the electrical grid. This seamless integration enhances visibility and control over the microgrid’s energy production. The results attest to the successful implementation of the monitoring system, highlighting its efficacy in improving the supervision, automation, and analysis of daily energy production. By leveraging internet of things technologies and ThingSpeak, stakeholders gain access to real-time data, enabling them to analyze performance trends and optimize energy resources. This research underscores the practical application of internet of things in enhancing the monitoring and management of energy systems with tangible benefits for stakeholders involved.
Influence of Data Sampling Frequency on Household Consumption Load Profile Features: A Case Study in Spain
(MDPI, 2020-10-23) de-la-Casa-Hernández, Jesús; Sánchez-Sutil, Francisco; Cano-Ortega, Antonio; Baier, Carlos
Smart meter (SM) deployment in the residential context provides a vast amount of data of high granularity at the individual household level. In this context, the choice of temporal resolution for describing household load profile features has a crucial impact on the results of any action or assessment. This study presents a methodology that makes two new contributions. Firstly, it proposes periodograms along with autocorrelation and partial autocorrelation analyses and an empirical distribution-based statistical analysis, which are able to describe household consumption profile features with greater accuracy. Secondly, it proposes a framework for data collection in households at a high sampling frequency. This methodology is able to analyze the influence of data granularity on the description of household consumption profile features. Its e ectiveness was confirmed in a case study of four households in Spain. The results indicate that high-resolution data should be used to consider the full range of consumption load fluctuations. Nonetheless, the accuracy of these features was found to largely depend on the load profile analyzed. Indeed, in some households, accurate descriptions were obtained with coarse-grained data. In any case, an intermediate data-resolution of 5 s showed feature characterization closer to those of 0.5 s.
Modeling of PV Module and DC/DC Converter Assembly for the Analysis of Induced Transient Response Due to Nearby Lightning Strike
(MDPI, 2021-01-08) Formisano, Alessandro; de-la-Casa-Hernández, Jesús; Petrarca, Carlo; Sánchez-Sutil, Francisco
Photovoltaic (PV) systems are subject to nearby lightning strikes that can contribute to extremely high induced overvoltage transients. Recently, the authors introduced a 3D semianalytical method to study the electromagnetic transients caused by these strikes in a PV module. In the present paper we develop an improved model of the PV module that: (a) takes into account high-frequency effects by modelling capacitive and inductive couplings; (b) considers the electrical insulation characteristics of the module; (c) includes the connection to a DC/DC converter. The whole process involves three major steps, i.e., the magnetic-field computation, the evaluation of both common-mode- and differential-mode-induced voltages across the PV module, and the use of the calculated voltages as input to a lumped equivalent circuit of the PV module connected to the DC/DC converter. In such a framework, the influence of the PV operating condition on the resulting electrical stresses is assessed; moreover, the relevance or insignificance of some parameters, such as the module insulation or the frame material, is demonstrated. Finally, results show that the induced overvoltage are highly dependent both on the grounding of the conducting parts and on the external conditions such as lightning current waveforms and lightning channel (LC) geometry.
Monitoring of the E ciency and Conditions of Induction Motor Operations by Smart Meter Prototype Based on a LoRa Wireless Network
(MDPI, 2019-09-16) Cano-Ortega, Antonio; Sánchez-Sutil, Francisco
The installation of smart meters in the industry to monitor induction motors (IMs) provides easy access to the measurements of the electrical and mechanical variables, which improves the installation process. Using smart meters in industry requires temporary high-resolution data to improve the energy e ciency (EE) and power factor (PF) of IMs. For these purposes, Long Range (LoRa) is an ideal wireless protocol for the usage in industries due to its low energy consumption. In addition, it provides secure communications and long range indoors and outdoors. LoRa avoids the need to install antennas or routers to extend coverage, as each gateway can service 300 LoRa devices with distances of up to 10 km. For this purpose, this research successfully developed a new prototype for a low-cost IM E ciency Monitoring System using LoRa (IMEMSL). IMEMSL is based on the Arduino open-source electronic platform. It sends the acquired data through the LoRa low-power wide-area-network (LPWAN) and cloud access gateway. This document describes the hardware and software design and implementation. The experimental results are presented and discussed. Received Signal Strength Indicator (RSSI) and time on air measured endorse the use of LoRa for this type of meters. The approximate cost of the prototype was ¿72 and ¿93 for the versions without and with Global Positioning System (GPS), respectively.
Performance Optimization LoRa Network by Artificial Bee Colony Algorithm to Determination of the Load Profiles in Dwellings
(MDPI, 2020-01-21) Cano-Ortega, Antonio; Sánchez-Sutil, Francisco
This paper presents a system to improve the performance of the Long Range (LoRa) network using an algorithm derived from the artificial bee colony (ABC), which obtains a minimum packet lost rate (PLR) in the LoRa network and allows to more accurately determine load profiles of dwellings, with smaller a time measurement and less data transmission. The developed algorithm calculates the configuration parameters of the LoRa network, monitoring in real time the data traffc, and is implemented in gateway LoRa network monitor (GLNM). Intelligent measurement equipment has been developed to determine the dwelling load profiles. This energy measurement device for dwelling (EMDD) measures the variables and consumption of electricity in each home with measurement times that can be configured. This research also develops the GLNM gateway, which monitors and receives data from the EMDDs installed and uploads them to the cloud using Firebase. This developed system allows to perform demand forecasting studies, analysis of home consumption, optimization of electricity tariffs, etc., applied to smart grids.
Power Factor Compensation Using Teaching Learning Based Optimization and Monitoring System by Cloud Data Logger
(MDPI, 2019-05-10) Cano-Ortega, Antonio; Sánchez-Sutil, Francisco; de-la-Casa-Hernández, Jesús
The main objective of this paper is to compensate power factor using teaching learning based optimization (TLBO), determine the capacitor bank optimization (CBO) algorithm, and monitor a system in real-time using cloud data logging (CDL). Implemented Power Factor Compensation and Monitoring System (PFCMS) calculates the optimal capacitor combination to improve power factor of the installation by measure of voltage, current, and active power. CBO algorithm determines the best solution of capacitor values to install, by applying TLBO in di erent phases of the algorithm. Electrical variables acquired by the sensors and the variables calculated are stored in CDL using Google Sheets (GS) to monitor and analyse the installation by means of a TLBO algorithm implemented in PFCMS, that optimizes the compensation power factor of installation and determining which capacitors are connected in real time. Moreover, the optimization of the power factor in facilities means economic and energy savings, as well as the improvement of the quality of the operation of the installation.
Smart Control and Energy Efficiency in Irrigation Systems Using LoRaWAN
(MDPI, 2021-10-24) Sánchez-Sutil, Francisco
Irrigation installations in cities or agricultural operations use large amounts of water and electrical energy in their activity. Therefore, optimising these resources is essential nowadays. Wireless networks offer ideal support for such applications. The long-range wide-area network (LoRaWAN) used in this research offers a large coverage of up to 5 km, has low power consumption and does not need additional hardware such as repeaters or signal amplifiers. This research develops a control and monitoring system for irrigation systems. For this purpose, an irrigation algorithm is designed that uses rainfall probability data to regulate the irrigation of the installation. The algorithm is complemented by checking the sending and receiving of information in the LoRa network to reduce the loss of information packets. In addition, two temperature and humidity measurement devices for LoRaWAN (THMDLs) and an electrovalve control device for LoRaWAN (ECDLs) were developed. The hardware and software were also designed, and prototypes were built with the development of the electronic board. The wide coverage of the LoRaWAN allows the covering of small to large irrigation areas.
Smart Public Lighting Control and Measurement System Using LoRa Network
(MDPI, 2020-01-09) Sánchez-Sutil, Francisco; Cano-Ortega, Antonio
The installation of smart meters in smart cities to monitor streetlights (SLs) provides easy access to measurements of electrical variables and lighting levels, which improves the operation of installation. The use of smart meters in cities requires temporary high-resolution data to improve the energy e ciency (EE) of SLs. Long range (LoRa) is an ideal wireless protocol for use in smart cities due to its low energy consumption, secure communications, and long range indoors and outdoors. For this purpose, we developed a low-cost new system and successfully evaluated it by developing three devices, namely the measure and control device for street lights (MCDSL), lighting level measurement device (LLMD) and gateway LoRa network (GWLN), based on the Arduino open-source electronic platform. This paper describes the hardware and software design and its implementation. Further, an algorithm has been developed to enhance the energy e ciency of public lights using MCDSL, the energy e ciency for street lights (EESL) algorithm, that use the illumination level measured on the same set of SLs with a dynamic control, which assumed di erent lighting levels throughout the night, and adjusted luminous flux based on the tra c intensity of pedestrians. It sends the acquired data through the LoRa low-power wide-area-network (LPWAN) to the cloud.

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