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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.
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.
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.
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.