Electrical Monitoring System Research Articles

Framework of Internet of Things (IoT) based Electricity Monitoring System with Web Application

Framework of Internet of Things (IoT) based Electricity Monitoring System with Web Application

Design and implementation of internet of things-based electrical monitoring system

Many modern monitoring and controlling projects such as systems in factories, home, and other used the internet of things (IoT). These devices perform self-functions without requiring manual intervention in order to improve convenience and safety. Electrical networks are one of the most important areas in which IoT systems can control, monitor, detect, and alarm for faultier, because detecting faults, monitoring network data, and finding the best solutions in a smaller duration of time to improve the efficiency and reliability of electrical networks. This paper proposes a system on the basis of a wireless sensor network (WSN). This system monitors and controls a variety of electrical and environmental variables, including power consumption, weather temperature, humidity, flame, lighting, and detection cut in the cable in electrical poles. Each sensor is a node and is connected to a microcontroller board separately. The data collected by these sensors is display and monitored on a web page and saved in a local server's database, this site was created with a variety of web programming languages. The system was developed using a free global domain. The website having a database for storing real-time sensor information.

Electric Equipment Transportation Condition Monitoring and Intelligent Early Warning System Based on Big Data Technology

Electric Equipment Transportation Condition Monitoring and Intelligent Early Warning System Based on Big Data Technology

Design of Motor Intelligent Monitoring and Fault Diagnosis System Based on LoRa

Aiming at the characteristics of low intelligence of the current motor cluster and superconducting electrical equipment monitoring system, high construction and maintenance costs of wired transmission methods. The wireless sensor network constructed by LoRa technology is applied to the motor operating state monitoring system, while the data transmission efficiency of the system is improved by optimizing the topology of the wireless sensor network (WSN) and processing the transmission data redundancy. The system uses STM32F407ZET6 as the main controller, builds an offline operating state library, and uses HMM model for training to achieve real-time acquisition and fault diagnosis of the status information of the cluster system motor's voltage, current, speed, and position. Practical application shows that the system is running well and can realize the acquisition of the motor's running status and fault diagnosis.

Research on Intelligent Fire Risk Perception System of High-rise Building Based on Big Data of Internet of Things

Due to the characteristics of high-rise buildings, such as dense personnel, complex structure and many combustibles, fire safety problems are more prominent. Aiming at the fire problem of high-rise buildings, based on the Internet of Things and big data technology, the intelligent fire risk perception system of high-rise buildings is studied. Through the functional modules of fire water monitoring system, intelligent electricity monitoring system and fire automatic alarm system, the hydraulic and water level of fire water, the current and voltage values of key nodes such as distribution cabinets, and the on-duty personnel in fire control room are mastered in real time, so as to grasp the specific location of fire in time and accurately, so as to realize the intelligent control of fire safety of high-rise buildings.

Development and realization of the electric energy monitoring system for cloud-based intelligent buildings

With the in-depth development of cloud computing technology and the continuous application of various new technologies in the process of modern building construction, the application of embedded technology, communication sensing technology, cloud computing technology and other technologies to create energy-saving building energy monitoring systems has become a research hotspot. This paper first compares and analyzes the network structure of the traditional building energy monitoring system and cloud-based building energy monitoring system, and then focuses on the overall architecture of the system and the design and implementation of the terminal intelligent monitoring unit. On the one hand, the development of building energy monitoring system based on cloud computing realizes cloud processing of building energy monitoring. On the other hand, the control strategy formulated by big data effectively improves the overall energy saving efficiency of the building.

Efficient Design of Energy Disaggregation Model with BERT-NILM Trained by AdaX Optimization Method for Smart Grid

One of the basic conditions for the successful implementation of energy demand-side management (EDM) in smart grids is the monitoring of different loads with an electrical load monitoring system. Energy and sustainability concerns present a multitude of issues that can be addressed using approaches of data mining and machine learning. However, resolving such problems due to the lack of publicly available datasets is cumbersome. In this study, we first designed an efficient energy disaggregation (ED) model and evaluated it on the basis of publicly available benchmark data from the Residential Energy Disaggregation Dataset (REDD), and then we aimed to advance ED research in smart grids using the Turkey Electrical Appliances Dataset (TEAD) containing household electricity usage data. In addition, the TEAD was evaluated using the proposed ED model tested with benchmark REDD data. The Internet of things (IoT) architecture with sensors and Node-Red software installations were established to collect data in the research. In the context of smart metering, a nonintrusive load monitoring (NILM) model was designed to classify household appliances according to TEAD data. A highly accurate supervised ED is introduced, which was designed to raise awareness to customers and generate feedback by demand without the need for smart sensors. It is also cost-effective, maintainable, and easy to install, it does not require much space, and it can be trained to monitor multiple devices. We propose an efficient BERT-NILM tuned by new adaptive gradient descent with exponential long-term memory (Adax), using a deep learning (DL) architecture based on bidirectional encoder representations from transformers (BERT). In this paper, an improved training function was designed specifically for tuning of NILM neural networks. We adapted the Adax optimization technique to the ED field and learned the sequence-to-sequence patterns. With the updated training function, BERT-NILM outperformed state-of-the-art adaptive moment estimation (Adam) optimization across various metrics on REDD datasets; lastly, we evaluated the TEAD dataset using BERT-NILM training.

Application of electric meter in the smart distribution network

The purpose is to promote equipment automation in the smart distribution network and improve the electricity detection accuracy and reliability of power equipment. Here, electric meters in the smart distribution network are studied. Firstly, the current electricity detection methods are discussed. Secondly, the common electric meter fault mechanisms are summarized and analyzed. Finally, the GM (Grey Mole) (1,1) is optimized through ACO (Ant Colony Optimization) algorithm and is used for detection and investigation of the real-time electric meter monitoring system. Then, simulation experiments are conducted based on the user’s electricity consumption data. The results indicate that the load correction value optimized by the ACO algorithm is closer to the actual load than the predicted value, and the absolute residual value is greatly reduced compared with the predicted value. At the same time, the prediction trend is more similar. This shows that the ACO-optimized GM can effectively improve the accuracy of the electric meter monitoring system.

Feasibility of Using Electrical Impedance Spectroscopy for Assessing Biological Cell Damage during Freezing and Thawing.

This study was performed to test bioimpedance as a tool to detect the effect of different thawing methods on meat quality to aid in the eventual creation of an electric impedance-based food quality monitoring system. The electric impedance was measured for fresh pork, thawed pork, and during quick and slow thawing. A clear difference was observed between fresh and thawed samples for both impedance parameters. Impedance was different between the fresh and the frozen-thawed samples, but there were no impedance differences between frozen-thawed samples and the ones that were frozen-thawed and then stored at +3 °C for an additional 16 h after thawing. The phase angle was also different between fresh and the frozen-thawed samples. At high frequency, there were small, but clear phase angle differences between frozen-thawed samples and the samples that were frozen-thawed and subsequently stored for more than 16 h at +3 °C. Furthermore, the deep learning model LSTM-RNN (long short-term memory recurrent neural network) was found to be a promising way to classify the different methods of thawing.

Research on thermal imaging fault detection system based on weibull distributed electrical system

A fault prediction analysis is performed In order to use infrared thermal imaging technology to detect electrical system faults, based on Weibull distribution technology. First, the principle is explained, the key technologies and factors of infrared thermal imaging and the electrical fault monitoring system are analyzed, and the available technologies are summarized. The detection process and analysis research are established with the help of on-site inspection and analysis results for power system fault analysis and research. The research shows that the method is effective for fault detection and trend analysis, and provides a reference for power fault detection and prediction analysis.

Perancangan Sistem Online Monitoring Pembebanan Transformator Distribusi Menggunakan Mikrokontroller

Electric energy is basically one of the main needs used in various activities in the community. In the distribution of electricity energy is required a reliable system so that the continuity of electricity energy that reaches consumers can be guaranteed well. One of the systems that needs to be maintained is the system related to distribution in addition to transmission and power generation systems. Reliability and quality of power must be maintained properly. Transformer damage is usually affected by overload which can harm the transformer itself as well as transformer insulation. A hot transformer can cause a short circuit that can cause the transformer to explode, so that the damage to the transformer can shorten the life of use both in terms of tools and oil. Electricity monitoring system has been widely implemented with the installation of electric measuring instruments on the transformer panel before entering the load. This research aims to build a prototype transformer monitoring module in real time based on the Internet of Things. This research is in line with Unhas research plan related to innovations in the field of Energy and the development of smart grid systems that can optimize the utilization of various new and renewable sources that vary, while being able to control the efficient use patterns of electricity energy on the downstream side through the protocol of informatics technology systems that have advanced today

Electricity Monitoring System based on Fuzzy Logic and Internet of things

a smart home concept that has a remote control system based on the Internet of things, to provide convenience and security for owners to control household electronic equipment such as lights, tv, and fans, not only controlling the house but homeowners can monitor power, voltage, current and electricity bills in real-time as well as the status of the electrical load used in a lit state or not. And users can also limit the use of power to prevent overloads that impact rising bills or electricity usage costs—monitoring lighting automatically on the house's terrace using the fuzzy logic method and monitoring bathroom lights by detecting the presence and absence of movement. The switch system on electrical devices can be replaced using the ESP8266 microcontroller to be connected to android with the Openhabian application installed. This control system can also be done anywhere without area restrictions as long as the user can connect to the Internet.

Design of Monitoring System for Electric Vehicle Charging Facilities Based on Cloud Platform

Faced with the increasingly severe pressure of traditional energy consumption and environmental problems, electric vehicles have become the hotspot and trend of the development of the world automobile industry due to their energy-saving and environmental protection characteristics. The cloud platform in the paper was introduced into the monitoring system of electric vehicle charging facilities, and a model of electric vehicle charging facility monitoring system based on cloud platform was proposed. Aiming at the difficulty of charging facility monitoring system in large concurrent data processing, a M/M/C queuing theory model was presented. Data concurrency control algorithm. The transmission process of the data frame in the monitoring system was analyzed, and the concurrent processing algorithm was applied to the large charging station for analysis experiments. The experimental results showed that the proposed algorithm not only satisfied the real-time and concurrency requirements of data frame transmission, but also proved that the gateway optimization method could accurately derive the optimal number of gateways.

Intelligent energy management based on SCADA system in a real Microgrid for smart building applications

Energy management is one of the main challenges in Microgrids (MGs) applied to Smart Buildings (SBs). Hence, more studies are indispensable to consider both modeling and operating aspects to utilize the upcoming results of the system for the different applications. This paper presents a novel energy management architecture model based on complete Supervisory Control and Data Acquisition (SCADA) system duties in an educational building with an MG Laboratory (Lab) testbed, which is named LAMBDA at the Electrical and Energy Engineering Department of the Sapienza University of Rome. The LAMBDA MG Lab simulates in a small scale a SB and is connected with the DIAEE electrical network. LAMBDA MG is composed of a Photovoltaic generator (PV), a Battery Energy Storage System (BESS), a smart switchboard (SW), and different classified loads (critical, essential, and normal) some of which are manageable and controllable (lighting, air conditioning, smart plugs operating into the LAB). The aim of the LAMBDA implementation is making the DIAEE smart for energy saving purposes. In the LAMBDA Lab, the communication architecture consists in a complex of master/slave units and actuators carried out by two main international standards, Modbus (industrial serial standard for electrical and technical monitoring systems) and Konnex (an open standard for commercial and domestic building automation). Making the electrical department smart causes to reduce the required power from the main grid. Hence, to achieve the aims, results have been investigated in two modes. Initially, the real-time mode based on the SCADA system, which reveals real daily power consumption and production of different sources and loads. Next, the simulation part is assigned to shows the behavior of the main grid, loads and BESS charging and discharging based on energy management system. Finally, the proposed model has been examined in different scenarios and evaluated from the economic aspect.

Research on the Intelligent Building Electrical Monitoring System Based on Computer Web

With the development of computer information technology, the traditional building electrical monitoring system has been unable to meet the needs of users. However, the automation degree of the electrical equipment in the current intelligent building is also low. Especially for the electrical monitoring system, there is no convenient and real-time management and service architecture, so there is still a large room for improvement. Based on this, this paper first analyses the intelligent building electrical monitoring system based on Web, then studies the related technology of intelligent building web monitoring system development, and finally gives the implementation strategy of intelligent building electrical monitoring system based on computer web.

Analysis of Custom IoT Based Electricity Monitoring System

Electricity is a resource that currently exists in various sectors of the community. Each person’s electricity needs are different depending on the needs of the electronic equipment used. Excessive use of electronic equipment creates extreme electrical power. Electricity consumption is an issue that discussed since a long ago. This research aims to present a custom electronic sensor to monitor electricity consumption based on the Internet of Things. It also explained the correlation between input and output points from the custom electronic sensor. This research method consists of 4 steps: system requirement, system design, system implementation, and last, testing and analysis. The system developed is able to get the current, voltage, and power data. The data then processed by Arduino UNO and directly send by ESP8266 to Blynk Application on Android smartphones via Internet communication. The voltage testing is done in the voltage and current sensors to get the program’s main loop’s constant values. The system input value and the Blynk Application value are also measured to check the system’s error.

Implementation of The Internet of Things for Monitoring The Company's Electrical Power Consumption

This research aims to design an electric panel monitoring system using the Internet of Things technology in company buildings so that consumers can monitor real-time electricity consumption. The energy consumption monitoring method that we propose uses PM2100 by implementing a real-time monitoring function of the power consumption of a 3-phase electric panel. The monitoring system implementation results show that the value is very close to measuring the digital multimeter measuring instrument. The monitoring system produces a current measurement accuracy of 97.38% with an error of 2.62%, while the 3-phase voltage measurement error is 0.616%. This system design helps companies obtain information faster to be considered data to improve efficiency in the Company.

In-situ marine gas hydrate production methane leaks electrical monitoring system

In the process of gas hydrate exploitation, methane leakage needs to be monitored in real time, so an in-situ electrical monitoring system for methane leakage is designed. The monitoring system is mainly composed of monitoring cable, acquisition station, power module and general control platform. According to the electrical principle, the system carries out regional monitoring on the seabed formation, forms the resistivity map, and realizes methane leakage monitoring. The cost of the monitoring system is low, and it can be remotely controlled or automatically collected data according to the preset program, so the system has good application and research value.

Electrical Control Online Monitoring System Based on Internet of Things

In order to improve the stability of the electrical control system, based on the Internet of Things technology, this paper constructs an online monitoring system for electrical control based on the Internet of Things. Based on actual needs, communication requirements, and common communication methods in the remote monitoring system, this paper combines the requirements of actual remote communication to conduct a detailed comparative analysis of the principles, performance characteristics, reliability, cost, maintenance, and other aspects of various communication methods, proposes a plan that can meet the communication requirements of the system, and completes the design of the wireless linear link communication network. In addition, according to the three‐tier architecture of the Internet of Things, this paper comprehensively uses the technologies related to the Internet of Things to design and develop the perception layer, transmission layer, and application layer. Finally, this paper designs experiments to test the performance of the system constructed in this paper. The research results show that the online monitoring system based on the Internet of Things constructed in this paper meets the needs of intelligent monitoring of the electrical control system.

Information Acquisition Function of Intelligent Meter Measurement and Control Unit in Electric Energy Information Acquisition and Monitoring System

The traditional smart meter is relatively solid in the hardware architecture design, and gradually can not meet the needs of energy measurement and control in the future. After the in-depth analysis of the metering function will be affected by various external factors, the paper designs a new hardware structure of "dual core- one expansion module" smart meter, through the actual scheme of separation of metering core and management core The measurement and control chip with various parameters is integrated in the expansion module, which is processed and calculated by the management core, so as to realize the localization protection and alarm function of intelligent meters. Combined with the application status of energy Internet, this paper designs the position and function support scheme of the new smart meter in the energy network, and verifies the practical problems to be solved after adding a variety of measurement and control function modules. The research results have a good reference significance for the development of smart meters and meter master control in the future.