IoT-Based Alternating Current Electrical Parameters Monitoring System

Varela-Aldás, José; Silva, Steven; Palacios-Navarro, Guillermo

doi:10.3390/en15186637

Cited by 12 publications

(3 citation statements)

References 39 publications

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“…Furthermore, the close agreement analysis for electric power and energy between the proposed wireless AC power monitoring module and CM3286-1 AC Power Meters for single phase 110/220 V AC appliances are 1.4586%/0.07037% and 0.0807%/0.0216%, respectively. In the literature review, the work of Varela-Aldás revealed that an AC electric parameter monitoring system consisting of two commercialized PZEM-004t V3.0 power energy meters integrated with a M5Stack Core ESP32 IoT platform was validated with the Gen 2 Vue Energy Monitor device with the accuracy in electric power and energy of over 1.95% and 0.81%, respectively [15]. The closeness of agreement of the proposed wireless AC power monitoring module illustrates better performance in the observations of both electric power and energy as compared to the integrated PZEM-004t V3.0 power energy meters and M5Stack Core ESP32 IoT platform.…”

Section: Discussionmentioning

confidence: 99%

“…A commercially available PZEM-004t power energy meter integrated with raspberry PI 3 to monitor and control electric loads for energy conversion was addressed by Limprapton et al, which offered the voltage, current, electric power and energy [14]. Varela-Aldás et al used a M5Stack Core ESP32 IoT platform to integrate two PZEM-004t V3.0 power energy meters and developed a web-based and mobile APP applications for AC electric parameters monitoring system which was validated with the Gen 2 Vue Energy Monitor device with the accuracy in electric power and energy over 1.95% and 0.81%, respectively [15]. In the previous work, a compact and sufficient reliability AC power monitoring module with a ZMPT101B voltage sensor and an ACS712-20 current sensor were integrated with an ATMega328 MCU to monitor the electrical parameters of voltage, current, electric power and energy, and pf [16].…”

Section: Literature Reviewmentioning

confidence: 99%

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Design and Evaluation of Wireless Power Monitoring IoT System for AC Appliances

2022

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The paper is aimed to develop a wireless alternating current (AC) power monitoring module which features the advantage of cost-effectiveness and sufficient reliability for the proposed AC power monitoring Internet of Things (IoT) system. The novel wireless AC power monitoring module consists of both ZMPT101B voltage sensor and ACS712-20 current sensor; a 16-bit analog-to-digital (ADC) ADS1114 with I2C interface and WeMos D1 Mini Wi-Fi module were integrated for monitoring refrigerator and air conditioner appliances with the ratings of single-phase 110/220 VAC, respectively. First, both analog readings of V/I sensors for AC appliances are converted into data streams in compliance with I2C (inter-integrated circuit) protocol, and are forwarded to a WeMos D1 Mini Wi-Fi module for the corresponding values of instantaneous electric power and energy, power factor (pf), and frequency well programmed in the built-in ESP8266EX IoT-based microcontroller unit (MCU) based on the well-known AC power fundamentals. All of the important AC power parameters are sent to the ThingSpeak IoT platform through Wi-Fi network. The visualization of voltage, current, electric power and energy, pf, and frequency is illustrated in the ThingSpeak IoT platform. Both close agreement and confidence of the proposed AC power monitoring IoT system for both refrigerator and air conditioner are evaluated with two CM3286-1 AC Power Meters. Taking the commercialized CM3286-1 instrument as reference, the values of mean absolute percentage error (MAPE) for above six electrical parameter readings are all less than 2%. The evaluation results illustrate sufficient closeness of agreement and confidence for the proposed wireless AC power monitoring IoT system for in situ monitoring AC appliances with single-phase 110/220 VAC ratings. Furthermore, the cost of the proposed AC power monitoring module is less than 100 USD, which makes the novel module more cost-effective than commercialized AC power meters which generally cost over 1000 USD. The novelties of the work are the following: (1) the introduction of ADS1114 provides I2C interface directly for Wi-Fi module to reduce the capital cost of the proposed wireless AC power monitoring module; (2) the sufficient confidence of the proposed AC power monitoring IoT system has been validated with closeness of agreement as compared to the commercialized CM3286-1 AC Power Meters. These make the assessment action of environmental, social, and governance (EGS) for stakeholders much more feasible with the advantages of cost-effectiveness and sufficient confidence.

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Section: Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Design and Evaluation of Wireless Power Monitoring IoT System for AC Appliances

2022

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“…This device also includes a TC voltage and current sensor that allows measurements of 127/220 V voltage and current up to 100 A. The ESP32 module collabo-rates with this tool to monitor electrical energy consumption effectively [23][24][25]. For on-site monitoring, the I2C serial communication protocol is employed to display data on an LCD screen.…”

Section: Monitoring Energy Demand Consumptionmentioning

confidence: 99%

Energy Management Model for a Remote Microgrid Based on Demand-Side Energy Control

Benavides,

Arévalo,

Ortega

et al. 2023

Energies

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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.

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