Readings Of Meters Research Articles

Design of electrical power telemetering system using microcontroller device via GSM

"Traditionally, reading of energy meters is done by human operators who move from house to house collecting readings. This exercise requires huge labor operator numbers and a lot of time to achieve complete reading of meters in a particular area. This paper endeavors to do away with this problem by using a telemetering system. With this system, power can be measured from a remote site. To achieve this, readings from an energy meter on site are processed by a microcontroller device that then sends the energy consumption information to a Global System Mobile (GSM) module. The GSM module then sends this information using microwaves to a particular mobile subscriber who receives it in the form of an Short Message Service (SMS). The reading is also transmitted to a web based telemetering system through a server. In the remote site, a remote computer which can access the internet is able to obtain data from the server through the internet. The microcontroller is developed in such a way that it achieves communication between the energy meter and the particular server using Transmission Control Protocol(TCP) protocol. Software programs are also developed to facilitate transfer of data to the user at remote site. With the web based telemetering system connected to the internet, electrical energy measurements can be accessed globally. The efficiency of the transmission channel is important for the success of both SMS and web based telemetering systems. Keywords: Telemetering system, remote sites, GSM "

DESIGN OF ELECTRICAL POWER TELEMETERING SYSTEM USING MICROCONTROLLER DEVICE VIA GSM

Traditionally, reading of energy meters is done by human operators who move from house to house collecting readings. This exercise requires huge labor operator numbers and a lot of time to achieve complete reading of meters in a particular area. This paper endeavors to do away with this problem by using a telemetering system. With this system, power can be measured from a remote site. To achieve this, readings from an energy meter on site are processed by a microcontroller device that then sends the energy consumption information to a Global System Mobile(GSM) module. The GSM module then sends this information using microwaves to a particular mobile subscriber who receives it in the form of an Short Message Service(SMS). The reading is also transmitted to a web based telemetering system through a server. In the remote site, a remote computer which can access the internet is able to obtain data from the server through the internet. The microcontroller is developed in such a way that it achieves communication between the energy meter and the particular server using Transmission Control Protocol(TCP) protocol. Software programs are also developed to facilitate transfer of data to the user at remote site. With the web based telemetering system connected to the internet, electrical energy measurements can be accessed globally. The efficiency of the transmission channel is important for the success of both SMS and web based telemetering systems.

Safflower (Carthamus tinctorius L.) crop adaptation to residual moisture stress: conserved water use and canopy temperature modulation are better adaptive mechanisms.

Oilseeds with high productivity and tolerance to various environmental stresses are in high demand in the food and industrial sectors. Safflower, grown under residual moisture in the semi-arid tropics, is adapted to moisture stress at certain levels. However, a substantial reduction in soil moisture has a significant impact on its productivity. Therefore, assessing genetic variation for water use efficiency traits like transpiration efficiency (TE), water uptake, and canopy temperature depression (CTD) is essential for enhancing crop adaptation to drought. The response of safflower genotypes (n = 12) to progressive soil moisture depletion was studied in terms of water uptake, TE, and CTD under a series of pot and field experiments. The normalised transpiration rate (NTR) in relation to the fraction of transpirable soil water (FTSW) varied significantly among genotypes. The genotypes A-1, Bhima, GMU-2347, and CO-1 had higher NTR-FTSW threshold values of 0.79 (R2 = 0.92), 0.74 (R2 = 0.96), 0.71 (R2 = 0.96), and 0.71 (R2 = 0.91), respectively, whereas GMU-2644 had the lowest 0.38 (R2 = 0.93). TE was high in genotype GMU-2347, indicating that it could produce maximum biomass per unit of water transpired. At both the vegetative and reproductive stages, significant positive relationships between TE, SPAD chlorophyll metre reading (SCMR) (p < 0.01) and CTD (p < 0.01) were observed under field conditions by linear regression. The genotypes with high FTSW-NTR thresholds, high SCMR, and low CTD may be useful clues in identifying a genotype's ability to adapt to moisture stress. The findings showed that the safflower genotypes A-1, Bhima, GMU-2347, and CO-1 exhibited an early decline and regulated water uptake by conserving it for later growth stages under progressive soil water depletion.

Development of smart energy monitoring using NB-IOT and cloud

IoT-based applications are growing in popularity nowadays because they offer effective answers to numerous current problems. In this research, With the aim of decreasing human efforts for monitoring the power units and increasing users' knowledge of excessive electricity usage, an IoT-based electric metre surveillance system utilising an Android platform has been developed. With the help of an Arduino Uno and an optical sensor, the electric analyser pulse is captured. To reduce human mistake and the expense of energy usage, a low-cost wireless network of sensors for digital energy metres is implemented alongside a smartphone application that can autonomously read the metre of the unit. In this research, an intelligent power monitoring system with effective communication modules has been developed to make wise use of the electricity. The controller, NB-IoT connection module, and cloud are the three main components of an IOT-based smart energy metre system. The controller is essential for maintaining the functionality of each component. This solution reduces the need for human involvement in electricity maintenance by connecting energy metres to the cloud using an NB-IoT communication module. The IoT-based metre reading system in the proposed work is created to monitor and analyse the metre reading, and the service provider can cut off the source of electricity whenever the customer fails to pay the monthly bill. It also eliminates the need for human intervention, provides accurate metre reading, and guards against billing errors. The proposed SPM improves the overall accuracy ranges of 7.42, 27.83, and 20% better than DR, OREM, and SLN respectively.

Investigation and mapping of geological construction materials in parts of chemoga river sub basin, debre markos, Ethiopia

Currently the demands of geomaterials are intensively increasing all over the country regarding to the expansions of towns for the consumption of engineering structures and buildings. Therefore, searching workable, serviceable and accessible geomaterials nearby areas is a vital subject to stabilize the inflation of geomaterials. The present research was carried out in the Chemoga river sub basin in the Southern direction of Debre Markos town, North Western Ethiopia. To meet out the objectives, detailed surface explorations were carried out through systematically selected travel lines (across the strike and along streams) to detect the different lithologic formations and the contacts; A number of representative rock samples were collected for visual interpretations; GPS reading and metallic meter were the materials used in the field to quantify stratigraphic units, bedding thickness and lamination the lithologic formations; The Brunton compass was used in the field to measure the orientation (dip direction, dip amount and strikes) of geological structures. Besides to this, related literatures were reviewed to have a general background on the subject matter.Basalt and Sandstone are the dominant lithogical units in the study area and have existed with about an average thickness of 500 m and 145 m respectively. Fresh to slightly weathered basalt and columnar basalt that used as a masonry stones are ease to access, workable and the most dominant lithologic units in the study area. Fine to coarse grain reddish to light color sandstone interbedded with siltstone and mudstone is well exposed. Based on the detail field exploration and judgments, Sandstone unit has been well exposed in a desirable potential and quality. And based on the detail field investigation and researcher judgment, the sandstone resource could answer the demands of construction materials for the surrounding areas of Debre Markos town for several thousand of years. Geometrically, mostly massive and steep rock faces are well developed which are difficult for quarrying process and required high explosive materials. Generally, a sandstone rock unit is surrounded by three major normal faults and inaccessible as compared to basalt unit. Regarding to environmental influences/effects, the area is sparsely farmed and it is not common that an extractive activity does not show any environmental and social impacts. Chert is exposed on geographically limited area and rarely observed following stream cuts. Chert and basalt units are slightly to highly weathered and showed alterations on the surface. Finally, the potential and the spatial distribution of geomaterials are investigated and revealed on the map using ArcGIS software and on the basis of the findings of the present research, recommendations are forwarded.

A multitask cascading convolutional neural network for high-accuracy pointer meter automatic recognition in outdoor environments

Pointer meter automatic recognition (PMAR) in outdoor environments is a challenging task. Due to variable weather and uneven lighting factors, hand-crafted features or shallow learning techniques have low accuracy in meter recognition. In this paper, a multitask cascading convolutional neural network (MC-CNN) is proposed to improve the accuracy of meter recognition in outdoor environments. The proposed MC-CNN uses cascaded CNN, including three stages of meter detection, meter cropping and meter reading. Firstly, the YOLOV4 Network is used for meter detection to quickly determine the meter location from captured images. In order to accurately cluster pointer meter prior boxes in the YOLOV4 Network, an improved K-means algorithm is presented to further enhance the detection accuracy. Then, the detected meter images are cropped out of the captured images to remove redundant backgrounds. Finally, a meter-reading network based on an adaptive attention residual module (AARM) is proposed for reading meters from cropped images. The proposed AARM not only contains an attention mechanism to focus on essential information and efficiently diminish useless information, but also extracts information features from meter images adaptively. The experimental results show that the proposed MC-CNN can effectively achieve outdoor meter recognition, with high recognition accuracy and low relative error. The recognition accuracy can reach 92.6%. The average relative error is 2.5655%, which is about 3% less than the error in other methods. What is more, the proposed approach can obtain rich information about the type, limits, units and readings of the pointer meter and can be used when multiple pointer meters exist in one captured image simultaneously. Additionally, the proposed approach can significantly improve the accuracy of the recognized readings, and is also robust to natural environments.

Design of Automatic Management System of Electric Power Marketing Charges and Accounts Based on Robot Process Automation

In the automation construction of marketing charge accounts in power supply enterprises, the key is the automation system of electric energy measurement. It covers all levels of measurement points and collection terminals in the whole network, and integrates measurement management, analysis, monitoring and information collection. The traditional electricity charge management of electric power enterprises is the process of manual meter reading, accounting and charging. Meter readers go to each customer every month to read the meter according to the meter reading time and meter reading card, record the number of electric energy meters on the meter reading card, and then copy the data of the meter reading card on the accounting card. Manual meter reading can't meet the current demand. Therefore, this paper will study the automatic management of electric power marketing charges based on RPA (Robot process automation), and build an automatic management system of electric power marketing charges. Through the comparative analysis of experimental data, the experimental results of the response accuracy of different systems show that this system is still more advantageous, and the accuracy of this system is the highest, with an average accuracy of 81.59%. However, the accuracy of reference method and reference method are 62.72% and 46.95% respectively. A perfect charging system based on RPA can not only improve the service level and corporate image of power supply companies, but also improve the management level of power supply companies, thus improving the economic benefits of enterprises.

On the effect of sampling frequency on the electricity theft detection performance

Electricity theft is a common problem in many countries and affects the revenue of the electricity industry significantly. Recently, machine and deep learning techniques are being used widely to detect thieves by analysing the consumption patterns. While the prediction accuracy of these methods depends on the number and quality of the existing samples used for training models, the majority of previous research work focussed on data with high sampling frequencies, for example, data from smart grids. However, based on technological and operational limitations, the rate of metre reading is too low in many countries, which can affect detection performance. To investigate the effect of sampling frequency on the performance of detection methods, we designed a processing framework to evaluate different classification algorithms on versions of a challenging dataset obtained by down-sampling the original data at various rates. We used different features from time, frequency and time-frequency domains and their combinations in our investigations. Experimental results show that the performance of the models decreases with a small slope up to the sampling frequency of one data per week. The performance degradation rate is significant for data with lower sampling frequencies. We also proposed a bagging network that could improve the overall detection performance at different sampling frequencies.

Instrument reading recognition by deep learning of capsules network model for digitalization in Industrial Internet of Things

AbstractUsing the intelligent image recognition method to recognize the reading of the unintelligent manual reading meter is an important approach to expand the sensing means and reduce the cost of transformation of the Industrial Internet of Things. Traditional methods based on morphology and back propagation neural networks are difficult to solve the problems of shadow, deflection, and dimness in the industrial environment. In this article, the deep learning‐based capsule networks for pointer instruments and digital display instruments were proposed to implement unintelligent manual reading meter recognition using. Due to the complex structure and a large number of parameters, the basic capsule network is difficult to run on devices with low computing resources. To overcome this issue, the improved capsule network model was designed to reduce the parameters of the model. The experimental results show that the improved capsule network improves the recognition accuracy by 13% and reduces the parameters by 23%.

Investigation of Intelligent Substation Inspection Robot by Using Mobile Data

Substation equipment inspection is essential for the power industry. The expansion of the smart grid scale improves the transmission capacity and enhances the likelihood of power plant facilities failure. To ensure the safety of the electric power supply, it is essential to inspect substation equipment. Metal commercial equipment can be traversed by remote inspection robots equipped with magnetic wheels. It is possible to use robots like this to examine equipment and pipelines remotely. In many cases, these gadgets are able to scale vertical surfaces and even traverse obstacles with a variety of shapes. Finally, researchers in the field of robotics have indicated that challenges such as restricted onboard battery capacity, undependable line fault detection, electrical insulation, power mechanism, and advanced control techniques for outer wind disruption are highly promising research areas. To build an unmanned, intelligent, and succeeded substation, the substation progressively implements inspection robots instead of physical exertion. Hence, in this paper, the mobile-based Intelligent Tracking Framework (MITF) has been proposed using inspection robots. This inspection robot is autonomous and can be used for various tracking tools: visual, infrared, and partial charge–discharge camera. The robot is integrated with a camera and thermal infrared imager sensors that have been collectively designated as workload. These inspection sensors are used to detect environmental parameters such as reading meters, evaluation thermoelectric temperature. The accurate localization of working loads and the inspection robot electromagnetic interference within substations have been resolved. This mobile robot delivers innovative monitoring and precise detection for the unmanned substation and smart substation. The suggested approach’s effectiveness is verified through experiment results based on the electrical equipment of the substation. The experimental outcome of the proposed method boosts the Meter Reading Analysis (94.19%), Transmission Capacity Analysis (98.5%), Workload Analysis (98.9%), Temperature Analysis (97.6%), and Safety Analysis (95.41%).

Data-driven optimization and statistical modeling to improve meter reading for utility companies

Utility companies collect usage data from meters on a regular basis. The usage data are collected automatically using radio-frequency identification (RFID) technology. Each meter transmits signals from an RFID tag that are read by a vehicle-mounted reading device within a specified distance. Routing the vehicles can be modeled by a close-enough vehicle routing problem on a street network. In practice, there is uncertainty while reading meters. The signal transmitted by an RFID tag is discontinuous, and the range that each meter can be read is different and stochastic due to weather conditions, surrounding obstacles, interference, and decreasing battery life of the RFID tags. These factors can lead to meters not being read. A vehicle has to be sent at a later time to read the missed meters, and this leads to increased costs for a utility company due to additional operational costs and overtime payments to drivers. Our aim is to address the uncertainty issues of the RFID technology by generating routes that are both cost-effective and robust (we seek to minimize the number of missed reads). We use data analytics, optimization, and Bayesian statistical models to address the uncertainty. Simulation experiments using real data show that the hierarchical Bayesian statistical model gives better results compared to other Bayesian statistical models. Utility companies can potentially integrate the results from the hierarchical Bayesian statistical model into their route generating software as a decision-support tool to produce routes that are more cost-effective and robust than the routes that they currently generate.

Optimalno podešavanje rezolucije registra električne energije pametnog brojila

Technical losses in the transmission network are: losses of power, i.e. electrical energy, which are a consequence of the consumption of power, i.e. energy for heating the elements in the transmission network due to the existence of active resistance in these elements, losses due to hysteresis, losses due to eddy currents, losses due to drain currents in insulation, losses due to corona and dielectric losses. With the most frequent use of smart meters for indirect connection in operation in a plant set up to display electricity from the secondary side, the active electricity will be read on the meter screen with an additional error. Then the transformation ratios of voltage and current instrument transformers are set in the smart meter as 1:1. In order to obtain the actual value of energy, it is necessary to multiply the measured value of electricity from the meter by the transformation ratios of instrument transformers. Another way is to adjust the actual transformation ratios of voltage and current instrument transformers in the smart meter, so that the actual value of electricity in megawatts can be read on the meter screen. In this paper, the errors of electricity reading are considered, taking into account: transformation ratios of measuring transformers, resolutions and units of electricity, methods of setting smart meters, internal constants of meters, nominal secondary currents of electric meters and the prescribed maximum energy that is registered on the screen of electric meter. It investigates how much larger the errors of secondarily set electric meters for indirect connection with the usual resolution for displaying electricity in three decimal places and the unit of measurement in kilowatt hours compared to other possible settings for reading meters. Errors in the calculation of technical losses of electricity on high-voltage transmission lines and cables and power transformers are noticeable.

Design and Implementation of Intelligent Meter Reading System in Smart Power Grid

Design and research the intelligent meter reading system, collect electric energy data in real time, and realize the remote reading function through the wireless network. The intelligent meter reading system adopts a three-tier structure of meter reading data processing layer, meter reading data presentation layer and meter reading data storage layer to enhance the efficiency and stability of the system. The design includes the operator module, the operation management module, and the system database and logical structure of the data maintenance module to enhance data security performance. Design the user interface of the intelligent meter reading system to complete functions such as task management, data review, and line data analysis. The design and development of the intelligent meter reading system enhances the accuracy and real-time performance of meter reading and reduces manual workload.

Smart Energy Meter Reading and Billing System using GSM Modem

In this paper we are focusing on automatic billing and metering, The GSM Short Message Service (SMS) and Arduino connection gives the metre reading system several predefined automatic capabilities.The energy consumption and electricity bill and loads will be providing through GSM module to the customer and to the concern electricity department. An alert message will be send to the customer and vigilance squad when the consumption unit reading reaches beyond the specific threshold. And loads on and off through gsm This paper contains energy consumption details in terms of power units and power units will be displayed on the LCD and will be notified to the customer via SMS and customer will also be able to recharge with the help of GSM module as well as microcontroller.

Development of an IoT-based water and power monitoring system for residential building

This study provides information between tenants and landlords on the use of the Internet of Things for power and water monitoring systems. It is one way to make reading meters and water meters easier to access using the available internet connection. The developed application using the android studio software is installed on a smartphone/tablet and verified to fully working on android versions from 4.1 (jellybean) to android 9.0 (pie). Tests were carried out in a household where the prototype was installed in a residential apartment. The data collected was monitored in the application and viewed by tenants and landlords. The results from the mean comparison of the power and volume readings measured by the wattmeter and water meter claim that the readings from the conventional meters and designed prototype have no significant difference using the Mann-Whitney U test. Evaluations were conducted showing that the device and the developed application using IoT is reliable, accurate, functional and user-friendly to use by tenants and landlords.

Heterogeneous field network for power distribution grid based on HPLC and RF adaptive communications technology

In order to improve the connection rate and transmission efficiency of field network for power distribution grid, a dual-mode heterogeneous field network with high-speed power line broadband carrier and micro-power radio frequency wireless communication capabilities was designed. First, the topological structure of the field network, the networking process of the central node and the free nodes and the dynamic maintenance mechanism of the network were discussed in detail. Secondly, the routing measurement mechanism for creating a hybrid routing table and the improved layer limit shortest path routing algorithm were presented. On this basis, each node in the network could choose the optimal communication media at any given moment to create communication links with the adaptive data transfer speed according to the real-time hybrid routing table. Finally, the dual-mode heterogeneous field network was applied to the electricity consumption information collection system and tested in the laboratory and jobsite. The test results show that the dual-mode field network was more effective than the single-mode field network in shortening the reading meter time and increasing networking success rate.

Design and implementation of HPLC Communication module in Smart Grid

In allusion to the problems of lower speed, weak anti-interference ability based on narrow band PLC (Power Line Communications) technology, a kind of HPLC (High-speed Power Line Communications) module used in ubiquitous power intelligent electricity acquisition system is designed. The HPLC module takings the SOC chip SC3105 as the master control chip transmit user datum between a concentrator and meters in high speed. Using abundant interrupts and timers, the system software fast processes accurate service messages and network management messages. The memory management mechanism of the system software recovers memory fragments and improves the use efficiency of memory, so as to keeping system stable. The test results show the module has over 1Mbps communication speed, 100% reading meter success rate, shorter reading meter time, and excellent communication performance in city power grids and village power grids, which solves the problems of narrow band PLC technology.

An intelligent robot for indoor substation inspection

PurposeTo ensure the safety of electric power supply, it is necessary to inspect substation equipment. With the dramatic increase in the number of substations, especially indoor substations, intelligent robot inspection has become an important development direction. This paper aims to describe the design of a trackless robot with a robotic arm, which is capable of navigating autonomously and inspecting the equipment in a narrow and complex indoor substation.Design/methodology/approachA robust four-wheel platform powered by electric motors is used to carry the robot. By fusing multiple-sensor data and visual markers, the robot achieves autonomous movement based on simultaneous localization and mapping. In addition, to accurately obtain the reading of meters located at height or in a narrow space, the robot is equipped with a newly designed visual servo robotic arm.FindingsIn practical application, the robot satisfies the requirements of substation inspection, improves work efficiency, saves costs and achieves good results. The robot is also approved by the relevant departments of the State Grid Corporation of China.Practical implicationsAfter stable operation in a substation for a period of one year, the robot shows high efficiency and stability, meeting the requirements of indoor substation inspection. Meanwhile, the robot greatly promoted the realization of indoor and outdoor integrated substation automatic inspection, and is expected to be further applied in other industrial inspection sites, including mine, tunnel and nuclear power plant.Originality/valueDue to the complex indoor environment, most of the existing inspection robots are only used outdoors, and there are no good trackless inspection robots for use indoors. The proposed robot is a trackless intelligent inspection robot for use in indoor substations. The robot features a number of important modules, including an autonomous localization and navigation module and a visual servo manipulator module, which can be used in narrow spaces or at height.

Chaos-based steganography technique to secure information and integrity preservation of smart grid readings using wavelet

In recent years, smart grids have attracted much attention due to their digital properties. Smart grids play a vital role in transmitting the collected readings of meter and other sensitive information of customers through the public network. Therefore, the confidentiality of consumers’ information and integrity protection of periodically collected readings are required for better assessment. This paper presents a novel technique of steganography based on wavelet and Hénon chaotic map to achieve integrity and authentication. Periodically collected readings are used as a cover object for hiding information of smart meter and consumer. The discrete wavelet transform is used to decompose readings into sub-band coefficients and used as a cover object. Sensitive information is converted into cipher using Hénon chaotic map. Stego readings are constructed with negligible distortion in original readings after concealing bits into a cover object by applying double-precision floating-point format. Percentage residual difference (PRD) test has been performed between stego and original readings as well as reconstructed readings. PRD test values have been observed to be very less than other existing algorithms. Experimental results illustrate that the proposed algorithm is reliable, robust and highly sensitive to its initial key, and retrieval of information at receiver’s end is not labyrinthine.

Joint Admittance Perturbation and Meter Protection for Mitigating Stealthy FDI Attacks Against Power System State Estimation

Power system state estimation is subject to false data injection (FDI) attacks, because of the integration of advanced computation and communication techniques in power systems. By coordinately tampering the readings of meters, FDI attacks can bypass bad data detectors and stealthily mislead the results of state estimation. In this paper, we propose a joint admittance perturbation and meter protection (JAPMP) strategy to enhance the resilience of state estimation under stealthy FDI attacks, i.e., recover system states from compromised measurements. State recovery conditions in JAPMP are derived, which indicate that the integration of admittance perturbation and meter protection can significantly improve the recoverability of system states. Based on the state recovery conditions, a JAPMP optimization problem is formulated and solved by decomposing the joint optimization problem into two subproblems. Then, a heuristic algorithm is designed, which can greatly reduce the computational complexity in solving the combinatorial problem. Based on the simulation results on a 6-bus, the IEEE 14-bus, the IEEE 57-bus and the IEEE 118-bus test systems, the protection cost and performance of state recovery under stealthy FDI attacks are evaluated.