Smart Grid Metering Research Articles

New Dual Algorithm to Placement the Data Aggregation Point for Smart Grid Meters

New Dual Algorithm to Placement the Data Aggregation Point for Smart Grid Meters

Quantum-resistance blockchain-assisted certificateless data authentication and key exchange scheme for the smart grid metering infrastructure

In the contemporary landscape of energy infrastructure, the “smart-grid metering infrastructure (SGMI)” emerges as a pivotal entity for efficiently monitoring and regulating electricity generation in response to client behavior. Within this context, SGMI addresses a spectrum of pertinent security and privacy concerns. This study systematically addresses the inherent research problems associated with SGMI and introduces a lattice-based blockchain-assisted certificateless data authentication and key exchange scheme. The primary aim of this scheme is to establish quantum resistance, conditional anonymity, dynamic participation, and the capacity for key updates and revocations, all of which are imperative facets for the robust implementation of mutual authentication within SGMI. Our scheme harnesses blockchain technology to mitigate the vulnerabilities associated with centralized administrative control, thus eliminating the risk of a single-point failure and distributed denial-of-service attacks. Furthermore, our proposed scheme is meticulously designed to accommodate the resource constraints of smart meters, characterized by lightweight operations. Rigorous formal security analysis is conducted within the framework of the quantum-accessible random oracle model, fortified by ’history-free reduction,’ substantiating its security credentials. Complementing this, simulation orchestration serves to underscore its superiority over existing methodologies, particularly in the realms of energy efficiency, data computation, communication, and the costs associated with private key storage.

PLC Communication using OOK/ASK Modulation for Automatic Meter Reading Systems for Smart Metering in Rural Smart Micro-Grids

Smart Grids are in performance an essential role in the current world. The current research efforts on these smart grids involve the advance in the turf of Smart Metering. The most costly, modest and straightforward to feast out abilities lie in Power Line Communications (PLC), which manufactured them useful in electric grids. Smart Metering in smart grid uses PLC technology in various architectures of LV grid. This paper proposes a scheme for a Smart Metering network with PLC expertise consuming on-off keying/amplitude-shift keying (OOK/ASK'S) Modulation. PLC with AMR schemes hand-me-down in energy conveyance system and recording, usages of illicit electricity by sleuthing because of the current network. More particularly in rural areas, the PLC with AMR Systems can minimize theft and illegal use electricity, which raises the power distribution authorities' revenue. Dissolute and Consistent meter analysis gathering with minor mistakes can be accomplished AMR Systems, which removes the requirement of physically construing meters. The anticipated system for current meters has remained in MATLAB/Simulink software.

Lightweight Authenticated Key Agreement for Smart Metering in Smart Grid

Nowadays, with the overconsumption of energy, researchers attempt to optimally manage energy consumption and prevent it from being wasted. One beneficial way to manage energy consumption is to integrate the energy grid with information technology, so that data can be exchanged between producers and consumers in a two-way communication network, which is called a smart grid. This data transfer must take place in a secure environment. However, many protocols have been designed to establish a secure channel to transfer data in the smart grid environment, each of which has some disadvantages that still keep the problem open for this field of research. Recently, Kumar <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> proposed a lightweight authentication and key agreement protocol based on elliptic curve cryptography (ECC). In this article, we show that the proposed protocol does not provide the anonymity of smart meters and is vulnerable to smart meter tracing attack. We also propose a new lightweight ECC-based authenticated key agreement protocol that is resistant against all known attacks including the attack presented in this article. Also, the proposed scheme is more efficient than the recent related scheme. We show that the proposed protocol is semantically secure and also we simulate our protocol using the AVISPA.

Real-Time Locational Detection of Stealthy False Data Injection Attack in Smart Grid: Using Multivariate-Based Multi-Label Classification Approach

Recently, false data injection attacks (FDIAs) have been identified as a significant category of cyber-attacks targeting smart grids’ state estimation and monitoring systems. These cyber-attacks aim to mislead control system operations by compromising the readings of various smart grid meters. The real-time and precise locational identification of FDIAs is crucial for smart grid security and reliability. This paper proposes a multivariate-based multi-label locational detection (MMLD) mechanism to detect the presence and locations of FDIAs in real-time measurements with precise locational detection accuracy. The proposed architecture is a parallel structure that concatenates Long Short-Term Memory (LSTM) with Temporal Convolutional Neural Network (TCN). The proposed architecture is trained using Keras with Tensorflow libraries, and its performance is verified using an IEEE standard bus system in the MATPOWER package. Extensive testing has shown that the proposed approach effectively improves the presence-detection accuracy for locating stealthy FDIAs in small and large systems under various attack conditions. In addition, this work provides a customized loss function for handling the class imbalance problem. Simulation results reveal that our MMLD technique has a modest advantage in some aspects. First, our mechanism outperforms benchmark models because the problem is formulated as a multivariate-based multi-label classification problem. Second, it needs fewer iterations for training and reaching the optimal model. More specifically, our approach is less complex and more scalable than benchmark algorithms.

AN EFFICIENT ELECTRICITY THEFT DETECTION USING XG BOOST

Electricity theft is a significant occurrence that is happening about all nations from one side of the planet to the other. This adversely affects the nation's economy. Theft identification in the power sector is a difficult task for power distribution organizations overall, since this power theft prompts to monetary losses just as loss of electric energy. There are numerous ways by which power is stolen like controlling energy meters or tapping cables at the consumer's end, and so on. Since this robbery is going on in enormous amount, manual examination of such burglary is a hectic task. So, automatic detection of power theft is a vital need of the hour. This paper presents an electricity theft detection model using smart grid meter data dependent on Extreme Gradient Boosting (XGBoost) and OCR. Feature Selection is made used of in the model in order to pick the most relevant features from the dataset to that of our electricity theft detection model. XGBoost is remarkable as it utilizes a more regularized model formalization to have command over-fitting which results in better execution significantly quicker. OCR is employed in order to know what object led to electricity theft detection.

Design and Application Analysis of Intelligent Technology for Smart Grid Metering Based on HPLC

In order to solve the problem of slow transmission efficiency, small amount of information, short coverage distance, easy to be disturbed, and easy packet loss in the transmission process of traditional narrowband modules,based on HPLC, this paper designed and applied the intelligent technical scheme of smart grid measurement operation.

Evolutionary Aggregation Approach for Multihop Energy Metering in Smart Grid for Residential Energy Management

The communication infrastructure is an important part to provide the reliability for energy management in the smart grid environment. With the aim of reducing the infrastructure cost for residential energy management, this article introduces a more complex multihop wireless remote metering network model. A novel evolutionary aggregation algorithm (EAA) is proposed to obtain the minimum number and locations of the local data centers (powerful nodes) in a 2-hop wireless remote metering network which has an arbitrary number of smart meters (ordinary nodes) with arbitrary transmission ranges. In the novel 2-hop EAA, the article designs and implements two novel adaptive operations (the switch operation and the shuffle operation) to improve the algorithm performance. Then the article extends the 2-hop EAA method to a more generic n-hop EAA which could obtain the optimal result in an n-hop (n > 2) smart meter network. Comprehensive case studies and numerical statistical analyses demonstrate that the EAA could efficiently achieve the optimal results in an n-hop (n> = 2) smart meter network environment; and the novel switch and shuffle operations could efficiently improve the performance of the evolutionary algorithm. The connectivity of the smart meter network could be fulfilled with the minimum number of the powerful nodes, from which the infrastructure cost for residential energy network could be minimized.

A fair and distributed congestion control mechanism for smart grid neighborhood area networks

The need for significant improvements in the management and efficient use of electrical energy has led to the evolution from the traditional electrical infrastructures towards modern Smart Grid networks. Taking into account the critical importance of this type of networks, multiple research groups focus their work on issues related to the generation, transport and consumption of electrical energy. One of the key research points is the data communication network associated with the electricity transport infrastructure, and specifically the network that interconnects the devices in consumers’ homes, the so-called Neighborhood Area Networks (NANs). In this paper, a new fair and distributed congestion control mechanism for NANs is proposed, implemented and evaluated. The main goal of this mechanism is to provide fairness in the access to the network, thus avoiding that some network nodes monopolize the use of the channels due to their higher traffic generation rate, or to their geographical position. Besides, different priorities have been considered for the traffic flows transmitted by different applications. The goal here is to provide the needed Quality of Service (QoS) to all traffic flows, especially when the traffic load is high. The proposal is evaluated in the context of a wireless ad hoc network composed by a set of smart grid meter devices. Applying our proposed congestion control mechanism leads to performance improvements in terms of packet delivery ratio, network throughput fairness between different traffic sources, packet network transit time and QoS provision.

Economic and environmental aspects of Smart Grid technologies implementation in Ukraine

Interruptions in electricity supply may have a series of failures that can affect banking, telecommunications, traffic, and safety sectors. Due to the two-way interactive abilities, Smart Grid allows consumers to automatically redirect on failure, or shut down of the equipment. Smart Grid technologies are the costly ones; however, due to the mitigation of possible problems, they are economically sound. Smart grids can't operate without smart meters, which may easily transmit real-time power consumption data to energy data centers, helping the consumer to make effective decisions about how much energy to use and at what time of day. Smart Grid meters do allow the consumer to track and reduce energy consumption bills during peak hours and increase the corresponding consumption during minimum hours. At a higher level of management (e.g., on the level of separate region or country), the Smart Grid distribution system operators have the opportunity to increase the reliability of power supply primarily by detecting or preventing emergencies. Ukraine's energy system is currently outdated and cannot withstand current loads. High levels of wear of the main and auxiliary equipment of the power system and uneven load distribution in the network often lead to emergencies and power outages. The Smart Grid achievements and energy sustainability are also related to the energy trilemma, which consists of key core dimensions– Energy Security, Energy Equity, and Environmental Sustainability. To be competitive in the world energy market, the country has to organize efficiently the cooperation of public/private actors, governments, economic and social agents, environmental issues, and individual consumer behaviors. Ukraine gained 61 positions out of 128 countries in a list in 2019 on the energy trilemma index. In general, Ukraine has a higher than average energy security position and lower than average energy equity, and environmental sustainability positions. Given the fact that the number of renewable energy sources is measured in hundreds and thousands, network management is complicated and requires a Smart Grid rapid response. Keywords: economic development, Smart Grid, electricity supply, economic and environmental efficiency.

A survey on smart grid technologies and applications

The Smart Grid is an advanced digital two-way power flow power system capable of self-healing, adaptive, resilient and sustainable with foresight for prediction under different uncertainties. In this paper, a survey on various Smart Grid enabling technologies, Smart Grid metering and communication, cloud computing in Smart Grid and Smart Grid applications are explored in detail. Opportunities and future of Smart Grid is also described in this paper. For Smart grid enabling technologies Smart meters, smart sensors, vehicle to grid, plug in hybrid electric vehicle technology, sensor and actuator networks are explored. Advanced metering infrastructure, intelligent electronic devices, phasor measurement units, wide area measurement systems, local area network, home access network, neighborhood area network, wide area networks and cloud computing are explored for Smart Grid metering and communication. Home and building automation, smart substation, feeder automation is explored for smart grid applications. Associations of initial studies for the next step in smart grid applications will provide an economic benefit for the authorities in the long term, and will help to establish standards to be compatible with every application so that all smart grid applications can be coordinated under the control of the same authorities. Therefore, this study is expected to be an important guiding source for researchers and engineers studying the smart grid. It also helps transmission and distribution system operators to follow the right path as they are transforming their classical grids to smart grids.

Optimization Scheduling of Electric Energy Meter Automatic Testing System

Recent years, the wide application of intelligent energy metering in smart grid leads to the increasing demand for intelligent energy meters. Automated, industrialized large-scale verification systems are widely constructed in important local power supply companies to increase the intelligent energy meter verification ability. The optimization scheduling of verification system utilizing the advanced optimization scheduling method is a necessity to improve verification efficiency. With this regard, considering the block of multi-function verification device caused by unqualified verification result, a model based on the robust optimization method is proposed to minimize the total verification time and improve the verification work efficiency. Deterministic transformation is illustrated to solve the model. The accuracy and effectiveness of the proposed optimization model are verified in simulation results and actual operation.

The Core for High-Precision Stochastic Smart Grid Meter Based on Low-Resolution Flash ADC

This paper describes a mixed-signal multibit stochastic flash analog-to-digital conversion (ADC) and a stochastic measurement instrument based on it, as an alternative for standard sampling ADC. It provides precise measurements based on high-speed low-resolution flash ADCs with added statistical process (dither noise) that compensates for low resolution. Stochastic instrument for measurement of average value of the product of two signals, based on this method, is analyzed for multibit case, with estimation of upper limit of standard and relative measurement uncertainty. Working prototypes of 2- and 4-bit stochastic instruments are presented and compared. Precision of this instrument is user controlled—the longer the period of measurement, the higher is the measurement precision. This enables measurements of electrical quantities in a smart grid (SG), such as electrical energy, with high precision over long time intervals, and root-mean-square (RMS) voltage and RMS current over shorter time periods but with lower precision. A preview of a stochastic SG meter design is given. The working prototype of the 4-bit instrument has 0.0080% expanded measurement uncertainty (with the confidence interval of 95% and the coverage factor $k = 2$ ).

Privacy-preserving metering in smart grid for billing, operational metering, and incentive-based schemes: A survey

We reviewed 53 papers related to privacy-preserving metering in smart grid published in the last 9 years. Attribution is the main cause for privacy issues in smart metering. Hence, we categorized studies based on measurements’ type: attributable or not. Utility Providers (UPs) use power measurements for two reasons: billing and maintaining operations. (A) Billing always requires attributable measurements. There are two main research problems for billing. (A-1) using coarse-grained measurements, which have minimal privacy concerns. (A-2) using fine-grained measurements, which have high privacy concerns. (B) Operational metering requires fine-grained measurements to maintain UPs’ operations. There are two main research problems for operational metering. (B-1) Protect users’ privacy when submitting non-attributable fine-grained measurements. Users might be reluctant to submit this type of measurements due to privacy concerns. Hence, UPs might offer incentive for users to shape their power usage (i.e. Incentive-based demand response (IDR)) or provide the fine-grained measurement (i.e. rewarding schemes). We refer to IDR and rewarding schemes as incentive-based schemes (they are sub-problems of the operational metering problem). They lead to the second research problem that addresses (B-2) protecting attributable fine-grained measurements used for operational metering.

Smart Grid Metering Networks: A Survey on Security, Privacy and Open Research Issues

Smart grid (SG) networks are newly upgraded networks of connected objects that greatly improve reliability, efficiency, and sustainability of the traditional energy infrastructure. In this respect, the smart metering infrastructure (SMI) plays an important role in controlling, monitoring, and managing multiple domains in the SG. Despite the salient features of SMI, security, and privacy issues have been under debate because of the large number of heterogeneous devices that are anticipated to be coordinated through public communication networks. This survey paper shows a brief overview of real cyber attack incidents in traditional energy networks and those targeting the smart metering network. Specifically, we present a threat taxonomy considering: 1) threats in system-level security; 2) threats and/or theft of services; and 3) threats to privacy. Based on the presented threats, we derive a set of security and privacy requirements for SG metering networks. Furthermore, we discuss various schemes that have been proposed to address these threats, considering the pros and cons of each. Finally, we investigate the open research issues to shed new light on future research directions in SG metering networks.

Efficient and Privacy-Preserving Data Aggregation and Dynamic Billing in Smart Grid Metering Networks

The smart grid enables convenient data collection between smart meters and operation centers via data concentrators. However, it presents security and privacy issues for the customer. For instance, a malicious data concentrator cannot only use consumption data for malicious purposes but also can reveal life patterns of the customers. Recently, several methods in different groups (e.g., secure data aggregation, etc.) have been proposed to collect the consumption usage in a privacy-preserving manner. Nevertheless, most of the schemes either introduce computational complexities in data aggregation or fail to support privacy-preserving billing against the internal adversaries (e.g., malicious data concentrators). In this paper, we propose an efficient and privacy-preserving data aggregation scheme that supports dynamic billing and provides security against internal adversaries in the smart grid. The proposed scheme actively includes the customer in the registration process, leading to end-to-end secure data aggregation, together with accurate and dynamic billing offering privacy protection. Compared with the related work, the scheme provides a balanced trade-off between security and efficacy (i.e., low communication and computation overhead while providing robust security).

Lightweight privacy-preserving data aggregation scheme for smart grid metering infrastructure protection

The electric industry's planned shift to smart grid metering infrastructure raised several concerns especially about preserving the privacy. Various data perturbation and aggregation solutions are being developed to address these concerns. The drawback of these solutions is that a simple random noise scheme cannot protect privacy, and there is a need for more advanced perturbation techniques to increase hardware costs of smart metering devices. The proposed data aggregation scheme combines the power of perturbation techniques with crypto-systems in an efficient and lightweight way so that it becomes applicable for devices with limited hardware, such as smart meters. We investigated the privacy preserving capabilities of the proposed aggregation scheme with Holt-Winters and Seasonal Trend Decomposition using Loess prediction methods. The results indicate that the proposed scheme is resilient to both filtering and true value attacks.

Big data framework for analytics in smart grids

Smart meters are being deployed replacing conventional meters worldwide and to enable automated collection of energy consumption data. However, the massive amounts of data evolving from smart grid meters used for monitoring and control purposes need to be sufficiently managed to increase the efficiency, reliability and sustainability of the smart grid. Interestingly, the nature of smart grids can be considered as a big data challenge that requires advanced informatics techniques and cyber-infrastructure to deal with huge amounts of data and their analytics. For that, this unprecedented smart grid data require an effective platform that takes the smart grid a step forward in the big data era. This paper presents a framework that can be a start for innovative research and take smart grids a step forward. An implementation of the framework on a secure cloud-based platform is presented. Furthermore, the framework has been applied on two scenarios to visualize the energy, for a single-house and a smart grid that contains over 6000 smart meters. The application of the two scenarios to visualize the grid status and enable dynamic demand response, suggests that the framework is feasible in performing further smart grid data analytics.

Secure and privacy-oriented obfuscation scheme for smart metering in smart grid via dynamic aggregation and lightweight perturbation

Smart metering in smart grid system has raised several condemnations based on its security and privacy invasiveness. The major techniques adopted to mitigate the security and privacy invasions of smart metering are aggregation and perturbation. However, aggregating smart meters' measurements is not enough to secure or preserve the privacy of consumers in either spatial or temporal metering. More so, the existence of perfect perturbation technique which can efficiently reconstruct data during the reconstruction phase has been a major challenge in existing perturbation schemes. In this paper, a scheme that combines aggregation and perturbation to secure smart meters' measurements and preserve consumer privacy is proposed. The scheme dynamically changes the topology and direction of aggregation in neighbourhood area network during spatial and temporal aggregation. It efficiently combines perturbation and aggregation techniques. A novel perturbs generation method was proposed for the perturbation scheme with dynamic constraint-based topology generation method. The simulation results showed that the scheme not only prevented gleaning of the metering but made it difficult for the adversary to perform pre-target attack on any of the smart meters in the network.

Secure and privacy-oriented obfuscation scheme for smart metering in smart grid via dynamic aggregation and lightweight perturbation

Smart metering in smart grid system has raised several condemnations based on its security and privacy invasiveness. The major techniques adopted to mitigate the security and privacy invasions of smart metering are aggregation and perturbation. However, aggregating smart meters' measurements is not enough to secure or preserve the privacy of consumers in either spatial or temporal metering. More so, the existence of perfect perturbation technique which can efficiently reconstruct data during the reconstruction phase has been a major challenge in existing perturbation schemes. In this paper, a scheme that combines aggregation and perturbation to secure smart meters' measurements and preserve consumer privacy is proposed. The scheme dynamically changes the topology and direction of aggregation in neighbourhood area network during spatial and temporal aggregation. It efficiently combines perturbation and aggregation techniques. A novel perturbs generation method was proposed for the perturbation scheme with dynamic constraint-based topology generation method. The simulation results showed that the scheme not only prevented gleaning of the metering but made it difficult for the adversary to perform pre-target attack on any of the smart meters in the network.