Showing papers on "Electricity meter published in 2021"

Detection of False-Reading Attacks in Smart Grid Net-Metering System

Abstract: In the smart grid, malicious customers may compromise their smart meters (SMs) to report false readings to achieve financial gains illegally. This causes hefty financial losses to the utility and may degrade the grid performance because the reported readings are used for energy management. This paper is the first work that investigates this problem in the netmetering system, in which one SM is used to report the difference between the power consumed and the power generated. First, we prepare a benign dataset for the net-metering system by processing a real power consumption and generation dataset. Then, we propose a new set of attacks tailored for the netmetering system to create a malicious dataset. After that, we analyzed the data and found time correlations between the net meter readings and correlations between the readings and relevant data obtained from trustworthy sources such as solar irradiance and temperature. Based on the data analysis, we propose a general multi-data-source deep hybrid learning-based detector to identify the false-reading attacks. Our detector is trained on net meter readings of all customers besides data from trustworthy sources to enhance the detector performance by learning the correlations between them. The rationale here is that although an attacker can report false readings, he cannot manipulate the solar irradiance and temperature values because they are beyond his control. Extensive experiments have been conducted, and the results indicate that our detector can identify the false-reading attacks with a high detection rate of 98.59% and a low false alarm of 2.92%.

Detecting anomalous energy consumption using contextual analysis of smart meter data

Abstract: Energy consumption is dependent on temperature, humidity, occupancy, occupant type, building area etc. All these factors collectively define the context of an energy meter. Once the context is known, the meters within the same context can be grouped and their behaviour can be analyzed together. This paper presents four heuristics, including one novel heuristic, to identify abnormal energy consumption. Using these heuristics, data collected from fifty smart meters deployed inside hostels of IIIT-Delhi was investigated for abnormal energy consumption detection. The anomalies and possible causes were discussed with IIIT-Delhi campus administrator. Energy consumption per occupant for one of the meters was found four times when compared to rest of the meters. The results demonstrated that the proposed heuristics successfully found abnormal energy consumption behaviour.

Global sustainability, innovation and governance dynamics of national smart electricity meter transitions

Abstract: Smart electricity meters are a central feature of any future smart grid, and therefore represent a rapid and significant household energy transition, growing by our calculations from less than 23.5 million smart meters in 2010 to an estimated 729.1 million in 2019, a decadal growth rate of 3013%. What are the varying economic, governance, and energy and climate sustainability aspects associated with the diffusion of smart meters for electricity? What lessons can be learned from the ongoing rollouts of smart meters around the world? Based on an original dataset twice as comprehensive as the current state of the art, this study examines smart meter deployment across 41 national programs and 61 subnational programs that collectively target 1.49 billion installations involving 47 countries. In addition to rates of adoption and the relative influence of factors such as technology costs, we examine adoption requirements, modes of information provision, patterns of incumbency and management, behavioral changes and energy savings, emissions reductions, policies, and links to other low-carbon transitions such as energy efficiency or renewable energy. We identify numerous weak spots in the literature, notably the lack of harmonized datasets as well as inconsistent scope and quality within national cost-benefit analyses of smart meter programs. Most smart meters have a lifetime of only 20 years, leading to future challenges concerning repair, care, and waste. National-scale programs (notably China) account for a far larger number of installations than subnational ones, and national scale programs also install smart meters more affordably, i.e. with lower general costs. Finally, the transformative effect of smart meters may be oversold, and we find that smart electricity meters are a technology that is complementary, rather than disruptive or transformative, one that largely does not challenge the dominant practices and roles of electricity suppliers, firms, or network operators.

A Methodology for Power Quantities Calculation Applied to an FPGA-Based Smart-Energy Meter

Abstract: A complete description of a field-programmable gate array (FPGA)-based smart energy meter is presented in this article. By implementing the power quantities definitions of the IEEE 1459–2010 Standard, a novel power quality analyzer capable of performing remote monitoring of electric power systems operating under sinusoidal, nonsinusoidal, balanced, and/or unbalanced conditions was developed. In order to ensure portability, the digital signal processing algorithms implemented on the FPGA device were entirely coded in hardware description languages, and all equations of them are fully described to be applied to any digital signal processing environment. These algorithms are completely defined as functions of the grid fundamental frequency, and by adjusting the sampling frequency, the adaptability of all modules developed is ensured. Experimental results were obtained using the developed platform in a three-phase four-wire system operating under several conditions, which were defined by the presence of harmonic components imposed by nonlinear loads and supply voltages, as well as by setting bidirectional power flow in distributed generation scenarios by employing a photovoltaic system. Real-time and parallel processes are validated as well.

Selection of features based on electric power quantities for non-intrusive load monitoring

Abstract: Non-intrusive load monitoring (NILM) is a process of determining the operating states and the energy consumption of single electric devices using a single energy meter providing aggregate load measurements. Due to the large spread of power electronic-based and nonlinear devices connected to the network, the time signals of both voltage and current are typically non-sinusoidal. The effectiveness of a NILM algorithm strongly depends on determining a set of discriminative features. In this paper, voltage and current signals were combined to define, according to the definitions provided in Standard IEEE 1459, different power quantities, that can be used to distinguish different types of appliance. Multi-layer perceptron (MLP) classifiers were trained to solve the appliance detection problem as a multi-class event classification problem, varying the electric features in input. This allowed to select an optimal set of features guarantying good classification performance in identifying typical electric loads.

Design and Implementation of LoRaWAN-Based Smart Meter System for Rural Electrification

Abstract: The urge to manage daily energy consumption has now become a worldwide priority. The Internet of Things (IoT)-based smart meter has been widely used to monitor energy consumption in many households. LoRaWAN connectivity is confirmed to be one of the most reliable connectivity to be used as a network system for IoT use cases. It can fulfill the needs of low power, long-range, efficient, and affordable IoT technology in utility energy monitoring. LoRaWAN-based smart electric meters are designed in rural areas for monitoring and managing electric energy consumption. The smart electric meter system consists of smart kWh meters, LoRa gateway, network system, and dashboard for energy usage monitoring. The system design process consists of feature design, architecture design, data flow design, LoRa gateway site planning, and platform setup. The implementation can be concluded that LoRa can be used for smart electric meters in rural areas. A gateway can reach a maximum distance of 1.58 km, with an RSSI of -99.40 dBm ±4.56 dBm. LoRa gateway availability can reach 100% by implementing gateway protection systems. The LoRaWAN-based smart electricity meter has also proven to be costoptimized, efficiently reducing monthly costs to 92.12%.

IoT based Energy Meter with Smart Monitoring of Home Appliances

Abstract: Today technology has changed across the world in a way human interact with the physical world. Internet of Things has paved the way for us allowing us to insert technology into day to day physical objects. In this paper an Energy Meter with Smart Monitoring of Home Appliances based on the Internet of Things is built. This paper proposes a system which eliminates manpower by self-regulating meter readings and bill generation reducing the flaws which are one of the major cause for energy-related corruption. The demand for transparency in the domain of energy estimation has emerged as there isn't a verification facility. Arduino Mega 2560 is used as the central controlling unit in this system. For energy meter, the ZMPT101B voltage sensor and ACS712 current sensor are interfaced with a microcontroller. The readings of voltage, current, the power consumed, no. of units and the corresponding price are calculated and are displayed over the 16*2 LCD Display module. An Infra-red based flame sensor is used as a fire safety measure. Monitoring of home appliances is done by using an 8 channel relay module to which loads are connected and operated over voice commands using Google Assistant with IFTTT (If this then that) platform which is interfaced with IoT based Blynk app on mobile. A DHT11 sensor is used for monitoring the temperature and humidity inside the house. All the readings obtained from the sensor is sent over the ESP8266 Wi-Fi module to Thingspeak cloud storage.

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

Abstract: 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.

Error detection and correction to enhance the data rate of smart metering systems using Modbus-RTU

Abstract: This work presents a system and method to improve transmission quality in smart meter networks that use Modbus-RTU. Energy management systems in industries, buildings and urban infrastructure use smart meters interconnected in a network. These systems can demand a great quantity of interconnected devices, which sets down increasing requirements to communication networks in terms of transmission quality and speed. At the plant level, Modbus-RTU is the de facto protocol for the interconnection of electric meters. However, since it was created more than 4 decades ago, this protocol imposes constraints to transmission speed, maximum number of interconnected devices and error detection mechanisms. This proposal is applicable to Modbus-RTU meter networks that need to increase data transmission speed to be integrated into smart metering systems but face problems due to the increase in transmission errors caused by noise and electromagnetic interference in the field bus. The effectiveness of the proposed method to increase the data rate while maintaining reliability is studied, and simulation and experimental results are presented.

Electricity Consumption Forecasting Using Machine Learning

Abstract: Intelligent energy management is a significant space of interest to fulfill the rising energy need for which a few nations are sending smart meters. By there is a need to better imagine the high-volume of information caught by savvy meters to give a way to successfully accumulate different scientific experiences which can help in better understanding the energy use designs. This work presents an approach of using machine learning models like support vector machine, extreme gradient boost and light gradient boosting machine for long term load forecast. the past power utilization to foresee the future power utilization. These models were tried on the openly accessible London Smart Energy Meter dataset. All these models were trained in order to evaluate their performances against the root mean square error. The correlation is performed between energy and weather datasets to see the impact on the power load forecast.

Ultra-broadband contactless imaging power meter.

Abstract: Knowledge of the spatial and temporal distribution of heat flux is of great interest for the quantification of heat sources. In this work, we describe the development of a new ultra-broadband contactless imaging power meter based on electromagnetic to infrared technology. This new sensor and the mathematical processing of images enable the reconstruction of both spatial and amplitude distributions through a wide spectral range of sources. The full modeling of the thermoconverter based on 3D formalism of thermal quadrupoles is presented first before deriving a reduced model more suitable for quick and robust inverse processing. The inverse method makes it possible to simultaneously identify the heat losses and the spatial and temporal source distribution for the first time, to the best of our knowledge. Finally, measurements of multispectral sources are presented and discussed, with an emphasis on the spatial and temporal resolution, accuracy and capabilities of the power meter.

IoT Based Smart Energy Metering System for Monitoring the Domestic Load Using PLC and SCADA

Abstract: The effort to obtain electricity utility meter readings and identify illegal use of electricity seems to be a very difficult and time consuming job in many other developing countries that needs a lot of effort and time. The Internet of Things energy meter reading and tracking device offers an accessible and cost effective way to transmit the energy data used by the user wirelessly and information networks to detect the unauthorized use of electricity. This proposed work aims to measure the electricity consumption of the electrical appliances in the house hold and it automatically generates the bill using smart meters. In addition this system can easily detect and screening the energy theft. The entire smart meters sensors have been equipped and controlled with PLC and monitored by the SCADA. The observed data will be taken from the digital energy meter and unite the system to a Wireless communication device and then passes the data to the Internet and Server. The detection of power theft will be obtained by using a sensor, it will work when any illegal usage of electricity. There is any chances of theft detection from the customer utility grid, it will automatically disconnected and enables supply again for the customer. The proposed system can handle of constantly tracking and notifying the energy supplier and the customer about the amount of units consumed. Energy usage is directly calculated and the bill is posted on the Internet through the Internet of Things network. The requirements of manual labor can be reduced by this automation.

Energy metering integrated circuit behavior beyond standards requirements

Abstract: During the last few years, the accuracy of static electricity meters (SEM) has been questioned. Significant metering deviations with respect to a reference meter have been observed at customer premises, and laboratory experimental tests results support such findings. The root cause of such errors remains unknown, as there are multiple elements that could affect the accuracy of electricity meters. Furthermore, standard compliant meters exposed to distorted signals may produce negligible, positive or negative relative error depending on the instrument design. Distorted current signals with fast amplitude transitions have produced the highest error in SEMs reported in the literature. In this paper, the accuracy of an energy metering Integrated Circuit (IC) is evaluated beyond the limits of the standards requirements employing a selection of distorted signals from the standards, real-world captured signals and a set of waveforms designed to test the IC under fast changing currents conditions, which are representative of the waveforms resulting from power electronic devices. The experimental results reveal an accuracy boundary imposed by Gibb’s phenomenon for fast changing current signals and a strong relationship between the IC’s measurement error and two key parameters of the measured waveform: signal slope and phase angle. This paper therefore provides a methodology for the comprehensive analysis of SEMs in future power systems which are dominated with power electronic-controlled electrical demand and contributes to the search for the root cause of error in SEMs exposed to distorted waveforms.

Design and Implementation of Smart Energy Meter using LoRa-WAN and IoT Applications

Abstract: In the day to day life in the present world where we are using vast technology, power is the most important term to deal for any Digital system to work, so it is as important to calculate the power we are consuming for our needs as anything over may drain one, so to know the power consumed from anywhere here we are dealing with smart energy meter using LoRa-WAN and IoT Applications, LoRa stands for Long Range, the name itself states that it deals with long range communication with the low power consumption working on batteries for years, In the IoT applications the range of the communication is the most important factor, as in IoT most of the Wi-Fi based systems needs to have many access points to cover the large area hence there is increment in the expenses for the system to integrate, by adding the unit of LoRa to the described design we can enhance the system to long range to several locations within that prescribed range as a LoRa can handle many nodes, the main theme of the LoRa is to promote the Bi-directional communication, all the data collected is stored in the Gateway and sent to the cloud server where you can access the data from anywhere through the mobile phone or PC and device, by installing the demanding version of software on your Gadget. AS we can see that in our real time we are using 4G network where transmitted bits or more, in the concept of LoRa the transmitted bits or less, by which we can overcome the disadvantage of the 4G/GSM networks, as of now as there is a huge loss to the telecommunication industries due to this they are switching to the LoRa.

Development and Implementation of the Smart Energy Monitoring System Based on IoT

Abstract: This paper is designed to measure energy consumption in home and buildings and to generate its bill automatically. It is accomplished by utilizing a smart energy meter with the Internet of things (IoT) technology, which will permit the user to successfully observe the energy meter calibrations and verify the electricity bill via the online. Our projected scheme utilizes Arduino to track utilized energy and to send out the units along the cost charged over the Internet. The Liquid Crystal Display (LCD) module is interfaced with Arduino, and the measured voltage, current, power, and the corresponding bill are displayed to the consumers. Arduino also sends data to the Adafruit cloud using the Wi-Fi module NodeMCU ESP-12. This smart meter will permit both the consumer and electricity supplier to ensure the energy usage quickly among the cost charged online. Power cost analysis of a month for a smart home is done in a separate section. Finally, the hardware is implemented with various loads, and results are displayed via LCD.

An Efficient Interpolation Method Through Trends Prediction in Smart Power Grid

Abstract: Due to the popularity of smart electric meter, electricity data is fast generated and abundantly transmitted through hierarchical servers in smart power grid domain. The missing record during transmission will influence subsequent analyses. However, it is not trivial to improve the quality of such continuous sensory data, because both interpolate accuracy and processing latency are hard to guarantee in practice through traditional means. We propose a data interpolation method for electricity data of smart meters in hierarchical edge environment. The missing records would be interpolated by predictive values through support vector regression in edge environment. In extensive experiments on real data, accuracy of data interpolation is guaranteed above 90% with executive time less than 20 milliseconds.

Real-time energy data compression strategy for reducing data traffic based on smart grid AMI networks

Abstract: In the future, the Internet of things (IoT) may provide huge volumes of data. Smart grids are a class of IoT electricity distribution systems that can control bidirectional energy flows between consumers and service providers (Barman et al. “IOT Based Smart Energy Meter for Efficient Energy Utilization in Smart Grid”, 978-1-5386-4769-1 1831.00, 2018 IEEE). A typical smart grid features an advanced metering infrastructure (AMI), which automatically collects meter data from widely distributed sensors. A utility company that intends to use AMI must deploy smart meters, data concentrator units, and a meter data management system (MDMS). Concentrators collect ubiquitous messages from smart meters and transmit aggregated data to their MDMS. Although ubiquitous messages may enhance the efficiency of some electricity grids, any excessive volume of messages causes data congestion. This research considers the Reference Energy Disaggregation Data Set. Our proposed algorithm can compress meter data efficiently. Our contributions are as follows: First, thus far, numerous researchers have attempted to address smart grid problems with AMI systems, and here, we provide a relatively complete review of these attempts. Second, this paper presents a strategy to analyze this problem and propose a compression algorithm to compress meter data. This proposed algorithm combines several existing compression algorithms and operates from 2 to 10% more efficiently than previously published algorithms.

Smart Energy Metering For Cost And Power Reduction In House Hold Applications

Abstract: This project aims to provide a smart way of measuring the electricity consumption in energy meters using modern electronic gadgets where the communication must be established between the user and the energy meter (which follows modbus communication) for daily update of the consumption. To provide this communication, the unit data received from the energy meter is interfaced with the microcontroller (ARDUINO UNO) through Modbus function code technique. Additionally, RS485 TO TTL CONVERTER is used in the interface setup where it acts as a gateway between energy meter and arduino board where the values from the energy meter is converted into a suitable form understandable by the arduino uno board. The microcontroller provides two functions in which one of them involves measuring the units consumed by the user. Using arduino software application, the user can now read the values in their system which is being used by them. A service provider named twilio is used which is used to provide a message to the user when the user’s electricity consumption had crossed the threshold value.

GSM based Energy Meter Monitoring and Load Control Via SMS using Arduino

Abstract: The main objective of the project is to develop a GSM based energy meter reading system and load control through SMS. Electricity department sends employees to take meter reading every month, which is an expensive and time consuming job. The proposed project provides a convenient and efficient method to avoid this problem. The electricity department and the user can get the readings of the energy meter of consumers via SMS. The loads can also be controlled by the user of this system via SMS using this project. A microcontroller input is effectively interfaced to a digital energy meter that takes the reading from the energy meter and displays the same on an LCD. The reading of the energy meter is also sent to the control room by an SMS via SIM loaded GSM modem. This GSM modem can also receive commands from the cell phone to control the owner’s electrical loads. It uses a standard digital energy meter that delivers output pulses to the microcontroller to perform counting for necessary action. On receiving command it can switch ON/OFF the loads.

Single Phase Energy Smart Meter System Design and Implementation Using RFID and Based on IoT

Abstract: The measuring of the distributed energy system and billing are complicate and have many problems such as easily prone to tampering, inaccurate, and requires a large number of human operators. This paper proposed the design and implementation of modern and highly accurate single-phase smart energy meter using radio frequency identification (RFID) technology and based on the Internet of thing (IoT). The proposed system has three units, smart energy meter and control centre and recharging RFID card system, which contains a unit for generating a serial number for each card and storing these numbers in the control centre unit. The transmission of consumed energy and smart meter readings information is sent using Wi-Fi technology to the central control unit.

Electricity Monitoring And Auto Bill Generation Using IOT

Abstract: The main scope of this project is to create smart IoT based energy meter which is used track energy consumption via gsm module. We can send the data of the energy consumed to the mobile phone in the form of sms. We can get data of the energy consumption on time requirement basis consumption basis. Some of the issues of the existing systems are Every time we cannot check the meter and figure out the energy consumption manually. No alarming features if they consume excess energy than threshold limit. No transparency on unit charge while billing. In digital meters only the amount of energy consumed is displayed there is no past energy consumption history. In our project consumption of electricity can be monitored remotely. It could generate more accurate bills. We can also control the load (on/off) by sending a message also the bill will be generated after load is turned off. SMS can be sending to both the customer and the authorized electricity board, so that they can update the bill in online and we can pay via cashless transfer which will be useful in this hard times (lockdown).

A Novel IoT Based Smart Energy Meter with Backup Battery

Abstract: Energy consumption is currently on the ascendency due to increased demand by domestic and industrial consumers. The quest to ensure that consumers manage their consumption and the utility companies also monitor consumers to manage energy demand and production resulted in smart energy meters which are able to transmit data automatically at certain intervals being introduced. These Smart Meters are still fraught with challenges as consumers are unable to effectively monitor their consumption and the meters are also expensive to deploy. This research aims to present a novel IoT based Smart Energy Meter that will gather consumption data in real time and transmit it to a cloud data repository for storage and analysis. The novelty of this inexpensive system is the introduction of an ADM25SC Single Phase DIN-RAIL Watt-hour Energy Meter which sends power to the microcontroller and also the introduction of a backup battery that keeps the meter on for some time to transmit outage data during power outages. Data gathered from the proposed IoT based Smart Energy Meter for a period is compared against that of the same period from a Smart G meter, a widely used energy meter, and is found to be very close confirming the accuracy of the IoT based Smart Energy Meter.