Smart Electricity Meters Research Articles

Designing an Energy Meter Using Arduino Uno

The continuous increase in the demand for electricity delivery services and the loss of electrical energy due to illegal consumption consider one of the important matters that need continuous monitoring of the transmission and distribution of electrical energy. This paper aims to design a smart electrical energy meter by using the Arduino UNO board that measures the voltage(V) and current(I) of an inductive load (resistance, coil) and calculating the frequency (f), effective power (P), power factor (PF) for this load at different values of the load and frequency. The proposed meter was designed by programming Arduino board and connecting Arduino with other electronic components to be the circle of the meter. The proposed meter was simulated and tested using Proteus software and the results obtained were good. The results showed a match between the meter reading of the values of the voltage, current, power factor, effective power, and frequency and the results obtained mathematically. The proposed meter can be developed to be able to connect to the communication networks so it can send the measured data periodically to the collection centers.

ACTUALIZATION OF SPECIFIC ELECTRIC LOADS PRESCHOOL EDUCATIONAL AND EDUCATIONAL INSTITUTIONS

To calculate the load of preschool educational and general education institutions, the specific values ​​of electrical loads are used, presented in SP 256.1325800.2016 “Electrical equipment of residential and public buildings. Rules of design and erection”. Research by the Roselectromontazh Association regarding the analysis of half-hour profiles of preschool and general education institutions showed a discrepancy between the declared capacity for technological connection and the actually measured one. The actual measured power turned out to be more than 2 times less than that calculated according to regulatory documents, which indicates the need to update the calculated specific electrical loads. This problem can be solved by using statistical methods to analyze the load profile of preschool educational and general education institutions, obtained from smart electricity meters. Due to the adopted Federal Law No. 522-FZ of December 27, 2018 “On Amending Certain Legislative Acts of the Russian Federation in Connection with the Development of Electric Energy (Power) Metering Systems in the Russian Federation”, the main transition to smart meters should be completed by 2023. Based on research in the Republic of Tatarstan, carried out over three years, a draft resolution was developed on amending the Resolution of the Cabinet of Ministers of the Republic of Tatarstan dated December 27, 2013 No. 1071 «On approval of republican standards for urban planning of the Republic of Tatarstan» in terms of calculating electrical loads for technological connection power receivers of preschool educational and general education institutions. The implementation of this decree will lead to a decrease in the cost of building an electric grid infrastructure, as well as to a decrease in electricity losses.

Research and Analysis on the Reliability of Smart Energy Mete

Analysis and study the reliability theory of smart electric energy meters, as well as reliability analysis indicators and fault distribution rules. Starting from the distribution law of fault data and reliability indicators of fault life, the reliability of electric energy meters is analyzed by collecting field maintenance data. The reliability model is used to study the failure modes, causes and effects of smart electric energy meters. The research and analysis of the reliability of the smart electric energy meter ensure the normal operation of the intelligent electric energy meter and improve the stability and reliability of the intelligent electric energy meter.

Research and Analysis on Evaluation Methods of Electrical Performance of Smart Energy Meters

Based on the technical specifications of smart meters, the electrical performance evaluation methods of single-phase smart meters are studied, and the accuracy, stability and safety of smart meters are analyzed and studied through specific data verification. Analysis the basic characteristics of the electrical performance of the smart energy meter, and evaluate the electrical performance based on the basic characteristics. Collect the specific working characteristic data of the intelligent electric energy meter, accurately measure the parameters of the intelligent electric energy meter, and analysis the electrical performance. Analysis the influence of the harmonic components of the power system on the measurement of the electric energy meter, study the power consumption of the smart electric energy meter, and the accuracy and stability of the operation.

Multi-agent System for Management of Data from Electrical Smart Meters

The smart meter can process sensor data in a residential grid. These sensors transmit different parameters or measurement data (index, power, temperature, fluctuation of voltage and electricity, etc.) to the smart meter. All of these measurement data can come in different ways at the smart meter. The sensors transmit each measurement data to the smart meter. In addition, the collection of this data to a central system is a significant concern to ensure data integrity and protect the privacy of residents. The complexity of these data management also lies in their volume, frequency, and scheduling. This work presents a scheduling and a collection mechanism in private power consumption data between both sensors and smart meters on one hand and between smart meters and the central data collection system on other hand. We have found several approaches to intelligent meter data management in scientific researches. We propose another approach in response to this concern for the scheduling and collection of measurement data to a central system from residential areas of sensors’ network connected to smart meters. This work is also an example of a link between data collection and data scheduling in intelligent information management,ransmission, and protection. We also propose a modeling of the measurement objects of smart grid and highlight the changes made to these objects throughout the process of data processing. It should be noted that this smart grid system consists of three main active systems namely sensors, smart meters and central system. In addition to these three systems, there are other systems that communicate with the smart meters and the central system. We have identified three implementation models for the smart metering system. We also present an intelligent architecture based on multi-agent systems for the smart grid. Most current electricity management systems are not adapted to the new challenges imposed by social and economic development in Africa. The objectives of this study are to initiate the design of a smart grid system for the management of electricity data.

Scalable identification and control of residential heat pumps: A minimal hardware approach

While model predictive control (MPC) is a widely studied tool for integrating residential heat pumps with the smart grid, modeling difficulties and hardware requirements are significant barriers to adoption. In response, we present a nonintrusive plug-and-play methodology for model identification and model predictive control using only two increasingly popular smart-home devices: a smart thermostat and smart electricity meter, which makes the overall approach highly scalable. However, this minimal hardware approach requires new methods to overcome modeling challenges due to the lack of data diversity. A data-driven heat pump power model is identified without the need for submetering by using energy disaggregation. By incorporating the heat pump control data from the smart thermostat, we provide implicit load classification data to the model, substantially simplifying the signal decomposition task. Building and heat pump model parameters are then identified by a novel algorithm that combats overfitting caused by limited state excitation. Finally, we show the advantage of this scalable approach in an aggregate model predictive controller enabled by the communication ability provided by the smart thermostat. Results show that this aggregate control approach can provide improved grid services, such as reduced peak demand, while at the same time reducing energy consumption and improving thermal comfort. The proposed method has the potential to greatly lower the barrier for residential energy aggregation.

Enhancing reliability of electricity supply of city electric networks cities of Dushanbe

The article is devoted to the actual problem of how to improve the reliability of the urban electric network. Based on the statistical analysis of the breakdown of electrical equipment in urban distribution networks in Dushanbe for the periods of 2017-2018 and for the reasons of damage leading to these emergency outages, the factors that affect the distribution of damage leading to emergency outages are identified. Taking into account the identified factors, a power consumption forecasting system is proposed that takes into account the local conditions of the city of Dushanbe. it allows us to suggest a way to control the operating parameters of the electric network, thereby increasing the reliability of the city's electric network in Dushanbe based on the recommendation of power consumption standards. Implementation of the control of the proposed method for improving the reliability of power supply to the urban electric network is proposed on the basis of the functionality of modern smart electricity metering using the control algorithm. To implement the control algorithm, schematic design for receiving and transmitting information from smart power metering to the data collection centre is proposed.

A GSM MODULE-BASED SMART ELECTRIC METER READER

The traditional and estimated billing system of electric energy consumed in most part of Sub-Saharan Africa has become a lingering issue to the electricity consumers. This has therefore necessitated the advent of smart electric meters. In this work, we propose a smart electric meter reader that provides an efficient and economically viable technique for measuring the consumption of electricity. This proposed method tends to solve many issues of the traditional reading system, such as reading efficiency, accuracy, and the elimination of human interface. Our proposed method, consisting of a GSM module, is used to wirelessly communicate the smart meter readings to the electricity provider and the consumer in form of a text message. The results obtained from the evaluation of this work show that our proposed method has improved the accuracy of the meter reading process for proper accountability.

Reliability Evaluation of Li / SOCl2 Battery for Smart Electricity Meter Based on Remaining Capacity

The life and reliability of the battery are the keys to ensuring smart electricity meters function properly during a power outage. This paper aims to study the capacity prediction and reliability evaluation methods of lithium thionyl chloride batteries for smart electricity meters based on capacity degradation model. The mechanism of capacity attenuation of backup lithium battery of smart electricity meters is introduced. An accelerated aging test method is proposed to study the influence of storage time, working condition, and temperature on capacity degradation. A semi data-driven model is used to describe the capacity degradation. According to the mathematical model, battery life under different storage conditions in the working environment of smart meters can be calculated.

Interactive search algorithm of artificial intelligence for household classification on smart electricity meter data

Interactive search algorithm of artificial intelligence for household classification on smart electricity meter data

Optimization Of The Measurement Precision Consistency Of Single-Phase Smart Electricity Meters In Full Temperature Range

With the development of smart power grids, smart electricity meters are widely applied to industrial production and the life. For interests of the power supply and consumption parties, electricity meters are required to have high quality, precision and consistency. As temperatures vary considerably in south and north of China and electricity meters work in complex temperature environments, studies on the effects of temperature on power metering are of significant importance. In this paper, an optimization method considering the effects of temperature is proposed for the consistency of electricity meters. The precision consistency of electricity meters is optimized in full temperature range through means such as electrothermal coupling simulation, orthogonal test, cost calculation, etc., and the design scheme of electricity meters with maximum cost performance can be delivered for their manufacturers.

High-voltage smart electricity metering of 110 kV digital electric networks

Were considered the technical solutions sufficient for the development of smart systems for automatic information and measurement metering of electrical energy and monitoring of overhead power transmission lines of the 110-220 kV electrical grids, considering the integration of the data flow into Scada-systems of digital substation workplaces in all the accordance with the standard protocols of IEC 61850. The device allows you to control the quality of transmitted electricity, remotely monitor the condition of the line, thereby increasing the reliability of power supply and power flows in the power system, reducing the cost of operational teams for their inspection.

Smart Metering Interoperability Issues and Solutions: Taking Inspiration from Other Ecosystems and Sectors

Interoperability in the context of smart electricity metering is high on the European policy agenda but its essence has been challenging to capture. In this paper, we look at experiences in other ecosystems (electromobility and buildings), other sectors (healthcare and public administration) and at the national level (the Netherlands and the UK). We show that the definition of interoperability depends on the context, that there are common solutions to different issues across sectors and that cross-sectoral factors must be increasingly considered. We recommend adopting a broader view in smart metering that goes beyond the interoperability of devices, considering solutions that have worked in other sectors and exploiting synergies across sectors. Our analysis of experiences provides a comparison that can help to move the debate at the EU level forward.

Model and Algorithm of Electricity Consumption Management for Household Consumers in the Republic of Tajikistan

The article is devoted to solving the problem of increasing the energy efficiency of urban electrical networks based on identifying factors affecting power consumption. According to the established patterns, a forecasting model has been developed, on the basis of which seasonal schedules of electricity consumption by household consumers are proposed. To monitor and control the operating parameters of the urban electrical network, taking into account the functionality of smart electricity meters, a control algorithm is proposed based on the proposed seasonal power consumption schedules by household consumers and a schematic implementation using smart electricity meters.

Selection of IoT-based technology for electric smart meter on PLN Disjaya

With so many platforms or protocols developed by several organizations or institutions, such as LoRa, NB-IoT and SigFox that have their own advantages and limitations. While it takes a large and long-term investment to deliver IoT technology. Apart from that, losses caused by the use of conventional meters on electricity customers cause a decrease in income by electricity supply companies. In this study aims to choose the internet-based technology of things for electricity smart meters in the PLN Disjaya region between three LoRa, NB-IoT and Sigfox technologies. This research is doing network design, coverage analysis, capacity analysis and network utilization, cost benefit calculation and analysis, data rate speed and proprietary. From the analysis results obtained SigFox superior in terms of coverage, capacity and network utilization, cost benefits (NPV, IRR, Payback Period, BCR, ROI), LoRa superior in terms of proprietary and NB-IoT superior in terms of data rate speed.

Analysis of energy consumption using RNN-LSTM and ARIMA Model

Given the increase of smart electricity meters and the wide adoption of electricity generation technologies such as solar panels, there is a wealth of data available on the usage of electricity. This data represents a multivariate time series of variables related to power, which could in turn be used to model and even forecast future electricity usage. The Household Power Consumption dataset is a multivariate time series dataset which describes the electricity consumption over four years for a single household. They were tested to predict for a specific house and block of houses over a given period of time. Throughout the past couple of decades energy demand has increased exponentially. This increase loads the electricity distributors heavily. So forecasting future demand for electricity use would give the dealer an upper hand. Predicting the consumption of energy requires several parameters. This paper proposes two methods with one using a Recurrent Neural Network (RNN) and another using a Long Short Term Memory (LSTM) network, considering only the previous consumption of electricity to estimate potential consumption of electricity. To assess the applicability of the RNN and the LSTM network to predict the electricity consumption.

Технологическое видеонаблюдение как инструмент защиты интеллектуального прибора учета электроэнергии от сторонних лиц

The article touches upon the problems of interference in the electricity metering system and different types of electricity loss underestimation. It has been stated that in modern conditions the only effective way to identify and prevent violations is to install a remote electricity meter at the borderline of balance and operational responsibilities. РиМ 384.02 smart electricity meter is considered as an example. A picture of the device is presented and its main positive characteristics are listed. It has been proposed to introduce the twenty-four-hour video surveillance and video recording system into an expensive smart electricity meter in order to maintain the integrity and operability of the device. Video stream processing by means of machine vision and machine learning has been proposed. The economic feasibility of digitalization of the technological video surveillance system is being substantiated. The need of optimization of the electrical networks, the improvement of electricity metering system and of introducing the new information technologies in energy sales has been substantiated

Common fault Analysis and Countermeasures of key Components of intelligent electricity meter

In recent years, with the State Grid Corporation's vigorous construction of smart grids, smart meters have been rapidly promoted in the power system. After several years of online operation, the operating reliability of smart meters has also stabilized. However, in the process of widespread use of smart electric energy meters, the quality problems of clock chips, batteries and other components have also been exposed. This article takes the component failures encountered in the detection and operation of the smart electric energy meter as an example, analyzes the causes of the failures based on the four typical abnormal phenomena, and then conducts the opening detection for the above reasons and determines the nature of the failure based on the test conclusions. Finally, a corresponding fault management platform is established through the collection of electric energy meter fault data, which realizes all-round management and control of the fault handling process and selection of the qualifications of smart meter suppliers, thereby ensuring the quality of components and improving the operation of smart electric meters reliability.

Privacy‐cost trade‐offs in smart electricity metering systems

Trade-offs between privacy and cost are studied for a smart grid consumer, whose electricity consumption is monitored in almost real time by the utility provider (UP) through smart meter (SM) readings. It is assumed that an electrical battery is available to the consumer, which can be utilised both to achieve privacy and to reduce the energy cost by demand shaping. Privacy is measured via the mean squared distance between the SM readings and a target load profile, while time-of-use pricing is considered to compute the cost incurred. The consumer can also sell electricity back to the UP to further improve the privacy-cost trade-off. Two privacy-preserving energy management policies (EMPs) are proposed, which differ in the way the target load profile is characterised. A more practical EMP, which optimises the energy management less frequently, is also considered. Numerical results are presented to compare the privacy-cost trade-off of these EMPs, considering various privacy indicators.

How to Foster the Adoption of Electricity Smart Meters? A Longitudinal Field Study of Residential Consumers

The objective of this research was to explore correlates and predictors that play a role in the process of adopting and withdrawing from using a smart metering information platform (SMP). The SMP supports energy monitoring behaviors of the electricity consumers. The literature review shows, however, that not every customer is ready to the same extent to adopt novel solutions. Adoption requires going through stages of readiness to monitor energy consumption in a household. In a longitudinal field experiment on Polish residential consumers, we aimed to see whether messages congruent with the stage of readiness in which participants declared to be at a given moment will be more effective in prompting participants to progress to the next stage than a general message or a passive control condition. We also tested the effect of attitude and knowledge about energy monitoring on phase changes. Our study reveals that what affects the phase change is the participation in the study. The longer the participants were engaged in the usage of SMP, the more willing they were to monitor their energy consumption in the future. This result sheds light on the future educational and marketing efforts of the authorities and energy suppliers.