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Smart metering and functionalities of smart meters in smart grid - a review
Abstract
Reducing the power supply-demand gap and increasing reliability of power supply are the challenges of current energy management. Implementation of smart grid, smart meters and smart metering can be a possible solution for power demand reduction, efficient power supply management, and optimization of management resource usages. Smart meters include sophisticated measurement and calculation hardware, software, calibration and communication capabilities. For interoperability within a smart grid infrastructure, smart meters are designed to perform functions, and store and communicate data according to certain standards. In this work we discuss smart meter and various elements of smart metering, current state of the technologies related to smart grid, smart meter, advanced metering infrastructure (AMI), and meter data flow in smart grid. We also discuss standards related to smart meter, meter data format and data transmission, functions of smart meter, and functionalities of smart meters, currently deployed by utilities around the world.
... The deployment of smart meters within smart grids [1] has ushered in a new era of energy management and distribution, promising enhanced efficiency, sustainability, and real-time monitoring [2,3]. Smart meters, as integral components of the evolving energy landscape, enable bidirectional communication between consumers and utility providers. ...
... We note that in the case where the user n attempts to find the solution locally at the level of their ESC, taking into account the implemented billing model, the strategies of the other users are fixed [3], and the only variables that change are user n's load scheduling vector x h n ∈ X n . Let L h = m∈N \{n} ...
... Attack range [0. 4,3]: This is a narrower attack range, which considers attacks with accuracy values between 0.4 and 3. The saved cost for this range is 119.01, ...
With the expansion of smart grids, maintenance and control costs have grown significantly. For this reason, some innovative strategies have been implemented to strengthen the control within the grid. Among these strategies, the implementation of distributed models coupled to intelligent billing systems is of high interest; it aims at achieving optimality in the system while maintaining billing fairness. Despite the advantages offered by smart grid’s paradigm, it still shows weaknesses in terms of theft and users’ fraudulence behavior detections. That is to say, the present paper focusses on three types of attacks, mainly existing in the literature, that malicious users can exploit to minimize their personal bills along with the development of related technique to troubleshot and solve such issues. Simulations and mathematical models are proposed to model these attacks, along with a mitigation strategy that has been developed.
... According to [7], a smart grid can be understood as an ecosystem where various types of renewable energy sources are connected, where smart homes and buildings are equipped with facilities capable of generating electricity for their consumption and sharing surplus energy with the concessionaire, or as a cyber-physical system capable of communicating with the structure of the energy flow, providing intelligence and automated control to the system itself, allowing for a bidirectional flow of energy and data [16,17]. The smart grid uses advanced measurement infrastructure (AMI), which is made up of three basic components: ...
... • Smart metering devices on the end user (smart meters); • Bidirectional communication path between the end user and the utility, where we find the data hubs; • Automated software and operation center for data processing [16]. ...
... In Figure 1, a simplified structure of an AMI can be seen, where we can see the MDMS that is responsible for collecting the data that enter the operation center from the concentrators. For the processing and storing of these data, analytical tools that allow for different sections of the operation and management system are used to interact with the concentrators and to collect the necessary data, thus constituting the heart of an AMI [16]. In the lower left part of Figure 1, highlighted in red, we can also see the action point of the proposed methodology that will work with the meters' database. ...
The implementation of smart grids introduces complexities where data quality issues, particularly outliers, pose significant challenges to accurate data analysis. This work develops an integrated methodology for the detection and correction of outliers in energy demand data, based on Artificial Neural Network autoencoders. The proposed approach is submitted across multiple scenarios using real-world data from a substation, where the influence of the variation in the number of outliers present in the database is evaluated, as well as the variation in their amplitudes on the functioning of the algorithms. The results provide an overview of the operation as well as demonstrate the effectiveness of the proposed methodology that manages to improve some indices achieved by previous works, reaching accuracy and F-score superior to 99% and 97%, respectively, for the detection algorithm, as well as a square root mean squared error (RMSE) and a mean absolute percentage error (MAPE) of less than 0.2 MW and 2%, respectively.
... Las principales funciones que debe cumplir un SM según [50] son: ...
... La utilización de SM proporciona beneficios para los usuarios, las empresas distribuidoras y el medio ambiente, entre las más importantes se encuentran [48], [50]: ...
... A pesar de la gran cantidad de beneficios que se obtendrían con una SG, aún existen obstáculos que deben de superarse para su implementación, los más relevantes según [46], [47], [50] son: ...
In recent years, the incorporation of renewable energies and the connection and disconnection of large loads, among others, have caused the quality of energy to decrease, which is why the study of disturbances in energy quality has become relevant due to the negative effects that they cause to users, such as increased consumption and decreased useful life of devices connected to the electricity grid. The study of platforms that can run real-time detection and classification algorithms for this type of event is relevant; optimization of the algorithms so that low-resource devices are capable of running them in the shortest possible time is important.
This thesis describes the process for creating an algorithm for real-time classification of six types of power quality disturbances based on a discrete wavelet transform and support vector machine implemented on a Raspberry Pi4. Simulated tests were performed in which eight sampling frequencies, 106 mother wavelets, three time windows and four noise levels were tested. The training of the classifiers was carried out based on statistical properties, with a total of 30 and 25 characteristics for signals with and without noise, respectively. The algorithm was tested on three single-board computers for a comparison of execution times.
In real-time tests, Piccolo C2000 LaunchPad was used for data acquisition, Raspberry Pi4 for the execution of the classification algorithm and BK Precision 4064 generator for the creation of waveforms, classified signals were chosen randomly and results were displayed on console.
In simulation, success percentages between 91.88 and 100% were obtained, real-time tests showed a success rate greater than 92 % with the time windows of 100 and 200 ms, performing the classification in a total time of less than 102 and 203 ms, respectively.
... Realtime monitoring and fault detection capabilities improve the responsiveness of power systems to anomalies, ensuring reliable and safe operations. Advanced IoT technologies, such as smart meters and sensors, provide detailed insights into energy consumption, facilitating dynamic pricing models and efficient energy use [10][11][12]. ...
... They support dynamic pricing, real-time monitoring, and accurate billing. Smart meters, which incorporate advanced hardware and software for measurement, communication, and data management, are essential for efficient power management and optimization within the smart grid [10]. Similarly, smart distribution systems leverage sensors, automated controls, and real-time data analytics to optimize electricity distribution. ...
... They not only provide detailed insights into energy consumption, but also enable utilities to implement dynamic pricing models, which can lead to more efficient energy use and cost savings for consumers. The two-way communication capability allows for remote disconnects and reconnects, outage notifications, and detailed power quality monitoring, which are essential for maintaining grid reliability and improving customer satisfaction [10]. ...
The integration of the Internet of Things (IoT) with renewable energy technologies is revolutionizing modern power systems by enhancing efficiency, reliability, and sustainability. This paper examines the role of the IoT in optimizing the integration and management of renewable energy sources, such as solar and wind power, into the electrical grid. The IoT enables real-time monitoring, data analysis, and automation, facilitating advanced load management, demand response, and energy storage solutions. Key advancements in IoT technologies, including smart grids and energy management systems, are discussed, highlighting their impact on improving grid stability and promoting the use of renewable energy. The paper also finds some challenges such as data security, privacy, and the need for standardized communication protocols. Furthermore, it finds how the IoT optimizes electric vehicle performance through advanced battery management, real-time energy consumption monitoring, and improved interaction with the electrical grid. Future research directions emphasize the potential of the IoT to further enhance renewable energy integration through artificial intelligence and machine learning, driving the transition towards a more sustainable and resilient energy future.
... However, the current smart meters are still not smart enough. They are incapable of conducting on-device intelligent data analytics but can only transmit collected data to a data management system [10], which can result in potential privacy leakage, heavy transmission burdens, and low efficiency in demandside management. Enabling on-device intelligence for smart meters without additional investment in computational facilities is an economical way to facilitate consumers managing flexible resources more autonomously and efficiently. ...
... As a shared component for the main model w s and the auxiliary model w c , the update of feature extractor w e will change the results of ℓ s and ℓ c . Thus, the parameters optimization of w e is expected to minimizes the objective loss in both (9) and (10). However, the w e serves as a decision variable only in (10). ...
... Thus, the parameters optimization of w e is expected to minimizes the objective loss in both (9) and (10). However, the w e serves as a decision variable only in (10). In other words, the w e is optimized based on the loss ℓ c in (10) and independent to the loss ℓ s in (9). ...
The ubiquitous smart meters are expected to be a central feature of future smart grids by enabling the collection of massive fine-grained consumption data to support demand-side flexibility. However, the current smart meters are still not smart enough. They can only perform basic data collection and communication functionalities but fail to carry out any on-device intelligent data analytics due to hardware constraints in terms of memory, computation, and communication capacity. Moreover, privacy concerns have hindered the utilization of data from distributed smart meters. Here, we present an end-edge-cloud federated split learning framework to enable collaborative model training on resource-constrained smart meters with the assistance of edge and cloud servers in a resource-efficient and privacy-enhancing manner. The proposed method is validated on a hardware platform to conduct building and household load forecasting on smart meters with only 192KB of static random-access memory (SRAM). We show that the proposed method can reduce the memory footprint by 95.5%, the training time by 94.8%, and the communication burden by 50% under the distributed learning framework, and achieve comparable or even superior forecasting accuracy compared to resource-unlimited methods.
... Outage management systems (OMS), Consumer information systems (CIS), Geographic information systems (GIS), and distribution management systems are the most common operation and management systems (DMS). Figure 2 depicts the interaction of several parts of a smart grid with an MDMS [14]. ...
... Meter Data Management System (MDMS)[14] ...
Advanced metering infrastructure (AMI) is an integrated system of smart meters, communications networks, and data management systems that enable the secure, effective, and dependable distribution of power while also delivering enhanced capabilities to energy consumers. The system also can measure power usage, connect, and disconnect service, detect tampering, identify and isolate outages, and monitor voltage automatically and remotely, which were previously unavailable or required user intervention. This article focuses on AMI and effectively integrating renewable energy sources (RES). However, the study also recommends smart metering for renewables such as solar photovoltaic (PV), hydropower, anaerobic digestion (ad) metering, and renewable energy storage, in which AIM thoroughly supervises the energy utilized by users' appliances. With the prediction of new ancillary services connected with contestability, related regulation, the sufficiency of consumer protection, and safety issues, the magnitude of renewable energy sources in the AMI is an almost unprecedented problem for consumers. The present energy management problems include reducing the power supply-demand gap and boosting power supply dependability. Implementing AMI with distributed renewable energy resources might be a viable strategy for lowering power consumption, improving power supply management, and maximizing management resource use.
... Todos esses recursos serão disponibilizados através de uma plataforma IoT, tornando o dispositivo inteligente, capaz de coletar dados e processar as informações coletadas. (OLIVEIRA, 2017) O objetivo é analisar as medidas de tensão e corrente, comparando-as com um equipamento de referência. A carga utilizada foi um conjunto de lâmpadas incandescentes com ajuste de potência. ...
... Medidores de energia inteligentes são ferramentas poderosas que mudam fundamentalmente a operação de sistemas elétricos. (BARAI,et al.,2015) Um dos diferenciais do protótipo desenvolvido foi a utilização da bobina de Rogowski. Este é um transdutor com núcleo de ar enrolado em formato toroidal que é utilizado para medir correntes elétricas que oscilam ao longo do tempo, baseada nas leis de Ampére e Faraday. ...
Pretende-se apresentar os resultados intermediários, de uma solução completa, para um nó de rede de sensores para medição de energia em nível de máquina. Esse nó apresentará, de forma quantitativa, características como consumo, funcionamento correto e dados de qualidade de energia por máquina. Todos esses recursos serão disponibilizados através de uma plataforma IoT, tornando o dispositivo inteligente, capaz de coletar dados e processar as informações coletadas. (OLIVEIRA, 2017)
O objetivo é analisar as medidas de tensão e corrente, comparando-as com um equipamento de referência. A carga utilizada foi um conjunto de lâmpadas incandescentes com ajuste de potência. O dispositivo foi baseado em um circuito de condicionamento analógico, um Arduino para o processamento dos dados e um ESP8266, como módulo WiFi para transmissão de dados para uma aplicação gratuita na nuvem. Medidores de energia inteligentes são ferramentas poderosas que mudam fundamentalmente a operação de sistemas elétricos. (BARAI,et al.,2015)
Um dos diferenciais do protótipo desenvolvido foi a utilização da bobina de Rogowski. Este é um transdutor com núcleo de ar enrolado em formato toroidal que é utilizado para medir correntes elétricas que oscilam ao longo do tempo, baseada nas leis de Ampére e Faraday. (SAMIMI, et al., 2015) Foi escolhido esse transdutor pois ele possui uma ampla faixa de medições e não requer abertura do circuito para realizá-las. A medição de tensão, por sua vez, foi feita através de um divisor resistivo.
... The motivation of this work is to exploit the availability of SMs for achieving reliability and latency criteria for V2N URLLC. SMs are prevalent in utility networks and are regularly used to collect data regarding the consumption of electrical energy [8]. However, during operational cycles, SMs have abundant free time slots when the assigned electromagnetic spectrum to SM remains underutilized. ...
With the rapid advancement of smart city infrastructure, vehicle-to-network (V2N) communication has emerged as a crucial technology to enable intelligent transportation systems (ITS). The investigation of new methods to improve V2N communications is sparked by the growing need for high-speed and dependable communications in vehicular networks. To achieve ultra-reliable low latency communication (URLLC) for V2N scenarios, we propose a smart meter (SM)-based cognitive network (CN) architecture for V2N communications. Our scheme makes use of SMs’ available underutilized time resources to let them serve as distributed access points (APs) for V2N communications to increase reliability and decrease latency. We propose and investigate two algorithms for efficiently associating vehicles with the appropriate SMs. Extensive simulations are carried out for comprehensive performance evaluation of our proposed architecture and algorithms under diverse system scenarios. Performance is investigated with particular emphasis on communication latency and reliability, which are also compared with the conventional base station (BS)-based V2N architecture for further validation. The results highlight the value of incorporating SMs into the current infrastructure and open the door for future ITSs to utilize more effective and dependable V2N communications.
... However, a correct implementation of this technology requires the development of technology of smart meters, point-to-point communication systems, and calculation automation computer systems to maximize efficiency in electrical distribution (Bansal & Singh, 2016;Barai et al., 2015;Kabalci, 2016;Sharma & Saini, 2015;Zheng et al., 2013). ...
The paper studies the optimization of interurban smart grid design by minimizing energy losses along the transmission lines. The optimized layout of the smart grid considers the location of the energy sources and consumption centers and the paths of the distribution lines. The optimization design includes the hourly distribution of the power sources and the hourly profile of the energy consumption. We developed a modeling study of the operation of a smart grid for specific operating conditions in a real case using historical data on electric energy consumption, solar, wind, and hydraulic energy resource. The study aims the development an algorithm that minimizes electric energy losses; this algorithm is based on the hourly distribution of energy generation and electric energy consumption but applies to other time intervals like days or seconds. The modelling results in a reduction of energy losses of 11.8%. This value corresponds to the selected configuration for this study; however, the methodology can be applied to any other grid configuration.
... In recent years, digitalization has become an important development direction in the power industry. Smart meters [2] and digital switchgear [3] have enhanced the level of distribution services. However, in the field of uninterrupted operation in the distribution network, the operating environment is highly complex. ...
The digitization of uninterrupted operation in the distribution network is of great significance for improving people’s quality of life and promoting economic development. As an important means of achieving digitization, point cloud technology is crucial to the intelligent transformation of distribution network. To this end, the authors embedded the improved RSA (residual spatial attention) module and modified the loss function of network, proposing a deep learning network called RSA-PT for the semantic segmentation of a distribution network scene point cloud. According to the requirements of uninterrupted operation in the distribution network, the authors segmented the point cloud into the following ten classes: high-voltage line, low-voltage line, groundline, tower, ground, road, house, tree, obstacle, and car. Model and attention mechanism comparison experiments, as well as ablation studies, were conducted on the distribution network scene point cloud dataset. The experimental results showed that RSA-PT achieved mIoU (mean intersection over union), mA (mean accuracy), and OA (overall accuracy) indicators of 90.55%, 94.20%, and 97.20%, respectively. Furthermore, the mIoU of RSA-PT exceeded the baseline model by 6.63%. Our work could provide a technical foundation for the digital analysis of conditions for uninterrupted operation in distribution networks.
... Moreover, several studies have concentrated on communication in smart grids and smart metering networks. The authors in [18] and [19] explained a smart grid, introduced its components, and presented the communication methods used, highlighting their advantages and shortcomings. It also surveyed smart grid integration, classified communication technologies, and outlined hardware and software security requirements. ...
Electric load forecasting is essential for power management and stability in smart grids. This is mainly achieved via advanced metering infrastructure, where smart meters (SMs) record household energy data. Traditional machine learning (ML) methods are often employed for load forecasting but require data sharing which raises data privacy concerns. Federated learning (FL) can address this issue by running distributed ML models at local SMs without data exchange. However, current FL-based approaches struggle to achieve efficient load forecasting due to imbalanced data distribution across heterogeneous SMs. This paper presents a novel personalized federated learning (PFL) method for high-quality load forecasting in metering networks. A meta-learning-based strategy is developed to address data heterogeneity at local SMs in the collaborative training of local load forecasting models. Moreover, to minimize the load forecasting delays in our PFL model, we study a new latency optimization problem based on optimal resource allocation at SMs. A theoretical convergence analysis is also conducted to provide insights into FL design for federated load forecasting. Extensive simulations from real-world datasets show that our method outperforms existing approaches in terms of better load forecasting and reduced operational latency costs.
... With the development of smart grids, the application of smart electricity meters is becoming more and more widespread, and has become one of the important forces driving the intelligent development of power systems [1]. The coverage rate of smart electric energy meters in developed countries around the world is already very high, and the coverage rate of smart meters in the State Grid of China has reached 99.03% [2]. The widespread application of smart electricity meters has brought higher efficiency and better services, as well as new challenges. ...
At present, the error calibration of electricity meters in operation generally adopts an off-site method; that is, the electricity meter is taken out of operation and then calibrated in the laboratory. Off-site calibration, while beneficial, may not fully capture the operational error of the electricity meter due to potential differences in environmental conditions. An on-site calibration device for electricity meters based on pulse detection is designed, which obtains the error of the electricity meter under calibration by comparing the energy pulses of the standard electricity meter with those of the electricity meter under calibration. High-precision voltage and current sampling channels are designed, with a voltage measurement error of less than 0.02% and a current measurement error of less than 0.03%. In response to the non-synchronous sampling problem caused by frequency fluctuations in the on-site verification environment, a fast optimal frequency estimation algorithm is applied to accurately calculate the signal frequency within two cycles. The sampling time interval is adjusted to achieve lock-frequency synchronous sampling, and ensure the accurate calculation of electrical parameters. In order to reduce the complexity of the device circuit structure and equipment cost, a standard electric energy pulses generation method based on digital integration-to-frequency is proposed, which uses software to generate electric energy pulses, with a maximum output frequency of up to 10 kHz. Tests conducted in the laboratory on the developed on-site calibration device for electricity meters show that its accuracy is better than the 0.05 accuracy class, meeting the application requirements for on-site verification of electricity energy meters.
... These are advanced energy meters that monitor and record the consumption of electricity in real time as they are equipped with communication capabilities that allow two-way communication between the utility company and the meter (Barai, Krishnan, & Venkatesh, 2015). Smart meters are not part of blockchain technology but can be integrated with features of blockchain technology to create innovative solutions in the energy industry. ...
This systematic review of literature bears the objective of exploring the potential of transformative novel blockchain technology, its regulation, and the substantive impact it bears on renewable energy firms' competitive advantage. The study provides a minutiae of the current trends in research, their implications, and blockchain implementation and innovation between 2019 to 2024. The methodology comprised a comprehensive search of scholarly databases, selection, and analysis of the relevant research studies. The findings revealed that Blockchain is essential based on its transparency, traceability, data privacy, and decentralization features which enhance trust, transparency, and traceability across the supply chain. Furthermore, blockchain technology is relevant in the renewable energy sector in Kenya ranging from p2p trading platforms, digitization by IoT, E-mobility, and decentralized trading platforms. The distributed ledger technology is a promising disruption for a wide area of service and product management in the energy sector ranging from the producers, transmitters, regulators, and distributors involved. The review concludes with future research recommendations and the practical implications for the industry players and the regulators.
... IoT technologies such as smart meters have been in use in smart grids in the US and in EU countries for monitoring and transmitting real-time electricity consumption to consumers as well as utility companies [78]. Also, in Germany and Denmark, IoT technologies are used to improve the efficiency of the electricity distribution systems [79], while in the US and Australia, they are used to regulate the power demand and alert consumers to the peak periods to minimize electricity usage [73]. ...
This paper examines the complex interplay between environmental management (EM) and decarbonization, highlighting how these domains can be seamlessly integrated to create a comprehensive framework for sustainable futures in the energy sector. The framework emphasizes the adoption of green technologies, energy efficiency measures, and innovative carbon capture, utilization, and storage (CCUS) technologies and infrastructures. Central to this approach are circular economy principles, low-greenhouse gas (GHG) emissions production processes, and CCUS strategies. A conceptual model of the EM–decarbonization nexus, comprising six enablers, was developed and illustrated with practical examples from various countries and regions worldwide. The findings reveal significant progress in advancing EM and decarbonization efforts. However, additional support from governments and the private sector is imperative in areas such as research and development, equitable transfer of renewable energy technologies, infrastructure for energy transitions, energy storage systems, green financing mechanisms, public education and community outreach, public–private partnerships, international cooperation, active engagement in global organizations, and the deployment of digital solutions. By addressing these areas, a sustainable future for the energy sector can be realized.
... In recent years, academics and industry have made substantial contributions to the question of how to meet the demands of this new reality. A particular focus has been put on the reliability of the smart grid [12]. ...
A smart grid is an electricity transmission system that uses digital technology to control getting and dispatching electricity from all generation sources to satisfy end users' fluctuating electricity demands. It achieves this through deploying technologies such as technology and smart grids, which are pivotal in increasing the power supply's efficiency, reliability, and sustainability to the public. Decentralized Smart Grid Control (DSGC) is a system where the control and decision-making functions are distributed to different grid points instead of in one central place. This paradigm is critical for the fault resistance and efficiency of the grid because it enables the local regions to carry on by themselves, manage electric power flows, respond to changes, and integrate many kinds of energy sources successfully. The grid frequency is monitored via the DSGC to ensure dynamic grid stability estimation. All parties, from users to energy producers, may take advantage of the price of power tied to grid frequency. The DSGC, a vital component of this research, gathered information about clients' consumption and used several assumptions to predict the behavior of the consumers. It establishes a method to assess against current supply circumstances and the resultant recommended pricing information. This research proposes a long short-term memory (LSTM) model to analyze data gathered regarding smart grid characteristics and predict grid stability. The results show a strong capacity for the LSTM model, achieving an accuracy of 96.73% with a loss of just 7.44%. The model also achieves a precision of 96.70%, recall of 98.18%, and F1-score of 97.43%.
... рисунок 1). Сбор данных с ИС, обработка, хранение и доступ к ним обеспечивают в нашей стране интеллектуальные системы учета электроэнергии (ИСУ ЭЭ) [1], а за рубежом -Advanced Metering Infrastructure (AMI) [2]. I. КОММЕРЧЕСКИЙ УЧЕТ ЭЛЕКТРОЭНЕРГИИ: · учет электроэнергия и квар часы по профилям коммерческого учета по тарифным зонам с классом точности по активной мощности от 0,2S до 1, квар часов -0,5 до 2; · учет электроэнергия и квар часы по профилям технического учета; · учет электроэнергия и квар часы за сутки, месяц, год; Примечание: учет выполняется в 4 квадрантах (потребление из сети / выдача в сеть кВт часов / квар часов); ведется журнал событий отключения и включения. ...
A brief literature review has been prepared on the possible use of intelligent energy (power) metering systems (IEMS) created in Russia by electric grid companies and guaranteeing electricity suppliers to solve various problems in the electric power industry. The review is carried out for users of IEMS and contains information about key applications, methods and tools used in the world. In order to reduce the labor-intensive search for necessary applications by users IEMS, the bibliographic part of the re-view is made in the form of a table with the following columns: application, IEMS user name, links to publications in the list of references
... So that the SM to perform its purpose optimally, it has a series of essential functions [7], such as dynamic prices that inform the user of the price of the energy consumed, bidirectional communication to send data between users and the energy distribution company, remote service that allows companies to disconnect, connect, detect theft and detect power outages as well as send invoices and warnings of abnormal consumption to users, in addition an SM presents a local area network (HAN) functionality to interconnect submetering devices, displays, thermostats and load control devices. ...
The integration of smart electrical networks aims to better respond to faults, and distribute and control energy consumption, all of this would be difficult to achieve without the functions of smart meters that allow the sending of information between electricity companies' services and the consumer, which is why it is important to guarantee the reliability of the information that is shared. In this work, the validation of the EVM430-F6736 meter and the PZEM-004T sensor is carried out concerning conventional devices for measuring electrical variables such as multimeters and wattmeters. The results show the error percentages between the measurements of the different devices.
... Smart meters play a pivotal role in enabling efficient energy consumption planning by providing real-time data that facilitate informed decision making and optimization of energy usage. As a consequence, smart meter technologies have a dedicated research track in the literature [8][9][10][11]. In [12], the authors propose smart meters for electricity profiling, but the proposal is in the context of entire buildings. Even if studies show that smart meters play an important role in efficient energy management in contexts such as smart grids and energy management for buildings, the solution has the disadvantage of costs, as concluded in the study of [13]. ...
This paper presents a novel approach for electricity consumption profiling in households through the fusion of usage data for individual smart devices. The novelty of the approach consists of leveraging the data representing the usage of individual appliances rather than using direct measurements of energy consumption. Our methodology focuses on merging signals representing the interaction of the user with the device to compute patterns in the total energy consumption per household. Subsequently, we apply data mining techniques—specifically, unsupervised clustering—to analyze the resulting time-series data representing daily energy consumption. Through this approach, we aim to identify and characterize patterns in energy usage within households, enabling insights for energy optimization strategies and resource allocation. This information can be further used in practical tasks, such as flattening energy consumption. The proposed approach offers an alternative to the direct measurement of energy usage, considering the potential for sensor failure or malfunction. This underscores the importance of implementing a complementary method for verifying and validating energy consumption data.
... Enhancing energy efficiency, lowering total energy consumption, and lessening environmental effect might result from modernising the electrical industry (Lin & Ankrah, 2019). There is extant literature on renewable energy (Nyasapoh et al., 2022;Gyamfi et al., 2015;Moriarty & Honnery, 2012), 2 modern metering devices (Gawlak &Sępek, 2018 andRajpoot et al., 2014) and smart meters (Barai et al., 2015). ...
The study assesses the influence of smart energy meters on Ghana's power supply management, consumer energy consumption, and utility company operations, and develops a national implementation strategy.
The specific objectives are;
1. To identify the impact of smart energy meters on power supply management and consumer energy consumption behaviour in Ghana.
2. To identify the advantages and challenges Ghanaian utility companies face in reducing power theft and technical losses using smart energy meters.
3. To develop and assess the effect of a national implementation strategy for smart energy meters in Ghana.
... These systems are designed with the aim of improving the effectiveness, dependability, and safety of electric power generation, transmission, and distribution. The most relevant aspects [3]- [6] of this type of system are described in Fig. 1. ...
The primary contributions of this paper include the systematic organization of existing research and an in-depth analysis of significant milestones in the field of CPPS, leading to the development of a taxonomy for categorizing various drivers. Furthermore, this paper elucidates current strategies for defining clear terms, models, methodologies, and attributes essential to cybersecurity policies within CPPS. The incorporation of relevant standards employed in the CPPS domain is also a paramount aspect of this review. In addition to these contributions, the paper identifies areas warranting further research and highlights emerging trends within CPPS, aiming to offer valuable insights to industry practitioners and to catalyze future research endeavors.
The implementation of smart metering infrastructure may be a possible solution to reduce electricity demand, manage electricity supply efficiently. This article reviews the ways in which smart metering infrastructure can overcome the various problems of the smart grid. It provides a better understanding of the technical challenges, economic opportunities and environmental implications associated with smart grids. As such, it helps to identify gaps in current research and areas requiring future investigation, thus helping to steer research and development efforts towards more efficient and innovative solutions. It highlights the latest advances and emerging trends, while providing an overview of current technologies and methods such as smart meters, data concentrators, the data management system and the communication system. We also examine standards for smart metering, substation automation, demand response, distributed resources, and large-scale control and monitoring, to ensure interoperability, security and reliability of energy management systems.
The ubiquitous smart meters are expected to be a central feature of future smart grids because they enable the collection of massive amounts of fine-grained consumption data to support demand-side flexibility. However, current smart meters are not smart enough. They can only perform basic data collection and communication functions and cannot carry out on-device intelligent data analytics due to hardware constraints in terms of memory, computation, and communication capacity. Moreover, privacy concerns have hindered the utilization of data from distributed smart meters. Here, we present an end-edge-cloud federated split learning framework to enable collaborative model training on resource-constrained smart meters with the assistance of edge and cloud servers in a resource-efficient and privacy-enhancing manner. The proposed method is validated on a hardware platform to conduct building and household load forecasting on smart meters that only have 192 KB of static random-access memory (SRAM). We show that the proposed method can reduce the memory footprint by 95.5%, the training time by 94.8%, and the communication burden by 50% under the distributed learning framework and can achieve comparable or superior forecasting accuracy to that of conventional methods trained on high-capacity servers.
Smart Grid has emerged as a phenomenon in energy management by replacing traditional grids with cutting-edge technology. Central to this innovation are smart meters, which hold significant potential for transforming energy consumption, monitoring, and regulation. However, the success of smart meter implementation relies heavily on user engagement. This research delves into the perceptions, barriers, and concerns associated with smart meter usage, focusing on Sweden, where smart meter deployment is mandated by the government. Utilizing a two-step investigation comprising a literature review and interviews with new smart meter users, this study identifies key obstacles and apprehensions hindering acceptance and adoption. By employing the Social Construction of Technology (SCOT) theory as an interpretive lens, the analysis underscores the understanding of users as a relevant social group and the interpretive flexibility of a technology that, for its closure, requires further negotiation among the different relevant social groups. This approach sheds light on the challenges associated with the need for appraisal by users and the commitment to a specific technological choice by institutions. The findings offer insights for future research and practice to promote sustainable energy systems.
Keywords
Smart Grid, Smart Meter, User Perspective, SCOT Theory.
In this study, an energy meter simulation is designed with MATLAB/Simulink and active-reactive power, power factor and energy
consumption measurements are realized. The energy meter is crucial for producers and consumers to precisely measure the quantity of
electrical energy produced or consumed. This paper aims to establish a three-phase system that simulates the energy meter and assesses its
efficiency. The energy consumed under different loads has been measured to accomplish this goal. The study summarizes the simulation
findings, encompassing tabular and graphical representations. Hence, the dependability and precision of the simulated energy meter model
should be observed.
The transformation of traditional electric power systems into smart grids has allowed for improved monitoring and control capabilities. However, this evolution has also brought about new challenges in the form of malware and vulnerabilities, creating significant security concerns. To address this issue, sensors are being deployed to the grid, leading to a large influx of data that needs to be analyzed for accurate results. Machine learning algorithms are being utilized to process this data and extract important information. This paper explores the application of various machine learning algorithms in smart grids, with a specific focus on their use in cybersecurity. We identify different types of cyber threats affecting smart grids and examine defense strategies to counter these threats. Through this study, we provide insights into the potential of machine learning in addressing the cybersecurity challenges in smart grids.
Monitoring the energy consumptions of the massive electrical appliances in buildings has attracted great attentions for smart, green and sustainable living. Traditional approaches generally require large-scale smart sensor/meter networks, and thus suffer from the high deployment, maintenance and data collection costs. In this paper, we propose methodologies and algorithms to optimize the smart meter deployments to track the on/off states of the massive electrical appliances by using the minimal number of smart meters. Particularly, based on the tree structure of the power distribution networks we show the deployment of m meters will decompose the power distribution network into a forest of m mono-meter trees. Each mono-meter tree has depth 1, with one meter at the root and a set of appliances at the leaves. A mono-meter tree is clear if the meter at the root can decode the on/off states of its leaves without error. Based on it, the smart meter deployment optimization problem is to optimize the meter deployment locations, so as to minimize the number of required meters while keeping all the mono-meter trees being clear. We prove this problem is NP-hard, and propose a greedy algorithm to approach it by utilizing the bounds of degree and the maximum power of the load tree. We show the greedy algorithm has at most 2 approximation ratio. Finally,we assess our approach in different structure power networks by simulations. The simulation results suggest a reasonable good performance of our proposed smart meter deployment strategy.
The demand for energy is increasing as a result of the growth in both population and industrial development. To improve the energy efficiency, consumers need to be more aware of their energy consumption. In recent years, utilities have started developing new electric energy meters which are known as smart meters. A smart meter is a digital energy meter that measures the consumption of electrical energy and provides other additional information as compared to the traditional energy meter. The aim is to provide the consumer and supplier an easy way to monitor the energy. Smart meters are considered a key component of the smart grid as these will allow more interactivity between the consumers and the provider. Smart meters will enable two-way and real-time communication between the consumers and the provider. Considering the increase of electricity demand in Saudi Arabia, smart meters can decrease the overall energy consumption. This paper presents the development of a GSM and ZigBee based smart meter. This meter can measure the energy and send the information to the service provider, who can store this information and notify the consumer through SMS messages or through the internet.
This research paper works on Smart Meter system through networking. This paper will provide the overview about smart networking for Smart House system. This method is very advance and reliable. It will manage whole power consumption and communication between the systems. A Smart House consists of smart appliances due to installation of smart cards, which act as communication icon between Smart Meter and appliances. Number of such Smart Houses are connected with a Town Server. This Town Server is able to control power, provided by service provider and power generated by Regenerative sources. The connection between Smart Meter and Town Server is via local PSTN and also with Power Line. Now further on, Town Server is bidirectionally connected to another T.S via power line for power transmission and via PSTN. And also connected with Main Server through PSTN. All the Smart Houses are controlled by Town Server. Town Server also takes reading from meter of each moment record it and sent it to Main Server after each hour and also manage power within its area of control or manage power from other towns for its Smart House. Main Server takes data from each Town Server after every hour and compile a bill up to that reading. This Main Server is directly controlled by service provider. The main advantage of such networking system is, in any case of disturbance to the Main Server, system remains on working, as all the power management, recording and its communication are keep on going by Town Servers.
For ten years, the utility industry has been using optical port communications, defined by ANSI C12.18, and telephone modem communications, defined by ANSI C12.21, to get metering data, defined by ANSI C12.19, from the field to the back office. While the two communication protocol standards have been employed to great success, missing was a standard method for using true ldquonetworkrdquo communications for exchanging this data. Recent work has completed ANSI C12.22, a standard for interfacing to data communication networks, as well as updating the optical port and modem communications standards. This set of standards offers the industry an open and comprehensive ldquoprotocol suiterdquo to transport the newly revised data standard, ANSI C12.19. This paper focuses on how utilities can best benefit from deploying technologies that meet those standards, in particular the newly developed ANSI C12.22 networking standard, as they begin to build advanced metering infrastructures. In particular, utility requirements being refined by OpenAMI Task Force are matched against the offerings from the ANSI protocol suite.
Energy meters have gone through several changes with respect to design and functionality, but still, they are prone to tamper. Meter tampering in the broadest sense is an illegal method employed by consumers to gain entry, break in, or some cases break the meter to deplete key functionalities, with the goal of reducing or completely eliminating the cost of energy usage. All electronic meters have a digital processor, microcontroller, microprocessor, or mixed-signal IC that performs energy measurement. These devices, collectively referred to as processors, are very powerful and directly contribute to the robustness of any meter. Separate sensors for voltage and current will convert ac-mains voltage and current to a reduced and acceptable input for analog-to-digital converters (ADCs) processing in the digital domain. It is important to establish that the ac-mains voltage is always fixed, whereas ac current varies with loads being turned on/off. Reversed current tampering is easily resolved by firmware that indicates negative energy readings.
Assume that a set of Demand Response Switch (DRS) devices are deployed in smart meters for autonomous demand side management within one house. The DRS devices are able to sense and control the activity of each appliance. We propose a set of appliance scheduling algorithms to 1) minimize the peak power consumption under a fixed delay requirement, and 2) minimize the delay under a fixed peak demand constraint. For both problems, we first prove that they are NP-Hard. Then we propose a set of approximation algorithms with constant approximation ratios. We conduct extensive simulations using both real-life appliance energy consumption data trace and synthetic data to evaluate the performance of our algorithms. Extensive evaluations verify that the schedules obtained by our methods significantly reduce the peak demand or delay compared with naive greedy algorithm or randomized algorithm.
Smart meter is one of the most important devices used in the smart grid (SG). The smart meter is an advanced energy meter that obtains information from the end users' load devices and measures the energy consumption of the consumers and then provides added information to the utility company and/or system operator. Several sensors and control devices, supported by dedicated communication infrastructure, are utilized in a smart meter. This paper outlines some smart meter's aspects and functions of smart meter. In addition, it introduces two basic types of smart meter system's communication technologies: Radio Frequency (RF) and Power Line Carrier (PLC) and recent advances with regard to these two technologies. This paper also presents different policy and current status as well as future projects and objectives of SG development in several countries. Finally, the paper compares some main aspects about latest products of smart meter from different companies.
In this paper, we investigate the scalability of three communication architectures for advanced metering infrastructure (AMI) in smart grid. AMI in smart grid is a typical cyber-physical system (CPS) example, in which large amount of data from hundreds of thousands of smart meters are collected and processed through an AMI communication infrastructure. Scalability is one of the most important issues for the AMI deployment in smart grid. In this study, we introduce a new performance metric, accumulated bandwidthdistance product (ABDP), to represent the total communication resource usages. For each distributed communication architecture, we formulate an optimization problem and obtain the solutions for minimizing the total cost of the system that considers both the ABDP and the deployment cost of the meter data management system (MDMS). The simulation results indicate the significant benefits of the distributed communication architectures over the traditional centralized one. More importantly, we analyze the scalability of the total cost of the communication system (including MDMS) with regard to the traffic load on the smart meters for both the centralized and the distributed communication architectures. Through the closed form expressions obtained in our analysis, we demonstrate that the total cost for the centralized architecture scales linearly as O(λN), with N being the number of smart meters, and λ being the average traffic rate on a smart meter. In contrast, the total cost for the fully distributed communication architecture is O(λ2/3 N2/3), which is significantly lower.
With the wide array of home area network (HAN) options being presented as solutions to smart grid challenges for the home, it is time to compare and contrast their strengths and weaknesses. This white paper examines leading and emerging HAN technologies. The emergence of the smart grid is bringing more networking players into the field. The need for low consistent bandwidth usage differs enough from the traditional information technology world to open the door to new technologies. The predominant players currently consist of a blend of the old and new. Within the wired world Ethernet and HomePlug Green PHY are leading the way with an advantage to HomePlug because it doesn't require installing new wires. In the wireless the realm there are many more competitors but WiFi and ZigBee seem to have the most momentum.
Smart meter is an advanced energy meter that measures consumption of electrical energy providing additional information compared to a conventional energy meter. Integration of smart meters into electricity grid involves implementation of a variety of techniques and software, depending on the features that the situation demands. Design of a smart meter depends on the requirements of the utility company as well as the customer. This paper discusses various features and technologies that can be integrated with a smart meter. In fact, deployment of smart meters needs proper selection and implementation of a communication network satisfying the security standards of smart grid communication. This paper outlines various issues and challenges involved in design, deployment, utilization, and maintenance of the smart meter infrastructure. In addition, several applications and advantages of smart meter, in the view of future electricity market are discussed in detail. This paper explains the importance of introducing smart meters in developing countries. In addition, the status of smart metering in various countries is also illustrated.
Fault location is an important application among intelligent monitoring and outage management tasks used for realization of self healing networks, one of the most attractive features of smart grids. The data gathered from various intelligent electronic devices (IEDs) installed throughout the power system could be utilized for smart approaches to locating faults in both transmission and distribution systems. This paper discusses issues associated with improving accuracy of fault location methods in smart grids using an abundance of IED data. Two examples of how the gathered data from different IEDs is used to improve fault location accuracy in transmission and distribution systems are discussed in detail.
Automatic meter reading (AMR) is much more than replacing meter readers and getting customer bills out more accurately. It is a pivotal information source that used effectively can drive enterprise efficiencies within transmission and distribution (T&D) operations, asset management, customer service, and energy efficiency.
This case study summarizes the efforts undertaken at CP and L-A
Progress Energy Company over the past five years to improve distribution
reliability via detection of distribution faults and determination of
their location. The analysis methods used by CP and L have changed over
the years as improvements were made to the various tools used. The tools
used to analyze distribution faults included a feeder monitoring system
(FMS), an automated outage management system (OMS), a distribution SCADA
system (DSCADA), and several Excel spreadsheet applications. The latest
fault detection system involves an integration of FMS, OMS, and DSCADA
systems to provide distribution dispatchers with a graphical display of
possible locations for faults that have locked out feeder circuit
breakers
Improving Electric Reliability with Smart Meters
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