Smart Meter Network Research Articles

Smart Utilities IoT-Based Data Collection Scheduling

The Internet of Things is an ecosystem that connects billions of smart devices, meters, and sensors. These devices and sensors collect and share data for use and evaluation by organizations in different industry sectors. Humans may use the IoT to live and work more intelligently and gain total control over their lives. Consequently, IoT can be used to connect devices and integrate them with new digital technologies for customers. On the other hand, smart utility companies in the electric, gas, and water sectors need to deliver services more efficiently and analyze their operations in a way that can help optimize performance, detect growing problems in real time, and initiate fixes to avoid unplanned service interruptions. Building actual smart metering networks is costly and time-consuming. Therefore, in this paper, a new Smart Utilities Traffic Scheduling Algorithm (SUTSA) is proposed. To minimize the system complexity, the model is based on narrowband power line communication, in which a wired hidden network sends data across power lines. A simulation is performed using OPNET Modeler 14.5 to evaluate the proposed model. The results proved that the proposed model is highly scalable and achieves full network-bandwidth utilization in different situations based on different application requirements.

Adaptation of powerline communications-based smart metering deployments with IoT cloud platform

<span lang="EN-US">The necessity of energy management and optimization through smart devices has an essential role in sustainable energy. Smart grid features and cutting-edge technologies are progressively integrated into traditional electricity networks. One of these features is the interference between power line communications and IoT. The introduction and deployment of these grids are mainly focused on the development of the field of smart metering. A new proposed module for smart meter design within the existing infrastructure grid system using power line communication (PLC) is presented. The system will include a transmitter with a microcontroller (MCU) and numerous sensors, as well as communication channels that include PLC and an in-house powerline network, and a receiver with an MCU. The suggested system interacts with the IoT system, characterized by a free web interface showing the data directly in real-time. Based on real-world experience, this paper develops guidelines for various aspects of PLC Smart Metering network deployment via the cloud environment. The practical result of packet losses is about 0, 1, or 2 characters of received data, and the time difference between transmitter and receiver is about 5000 milliseconds for a fixed transmission line.</span>

A Comprehensive Review on Wired and Wireless Communication Technologies and Challenges in Smart Residential Buildings

Background: The smart grid communication network is constructed with three tiers namely, Home Area Networks (HANs), Neighborhood Area Networks (NANs) and Wide Area Networks (WANs). These networks function with various communication protocols like table protocol, on-demand protocol, Wi-Fi, Zigbee, Z-Wave, Wi-MAX, GSM, LTE, Cognitive Radio Networks. The network interconnection is heterogonous and all appliances have to communicate through the IP gateways. A large amount of data is collected from various sensors placed in different locations. The analytics on large data- “big data” is essential because these data were used to organize and plan an efficient control and management of the smart home including secured data exchange in different sectors. Objective: This paper investigates broadly on data rate, channel bandwidth, power consumption, and a coverage range of both wired and wireless communication technologies used in residential buildings. Besides, a literature survey on optimization algorithms with various constraints to manage home appliances through scheduling is included. The paper also discusses the communication standards along with security and privacy requirements for smart metering networks. Conclusion: Discussion on IEEE standards for both wired and wireless communication protocols. Gives direction to identify the suitable communication technique through mathematical model for computing the communication channel bandwidth. Comparison of various optimization algorithms with multiple constraints in HEMS to achieve the minimum electricity cost and user comfort (with and without Renewable Energy Sources). From the investigation on both wired and wireless networks, the wireless communication networks (Zig-Bee & Wi-Fi) are mostly preferred to use in HAN because of more reliability and low cost. Zigbee is the most appropriate technology used for data transmission between the individual appliances and smart meters. Wi-Fi is a suitable technology for controlling and monitoring appliances because of its high data rate.

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.

Intelligent metering systems designed to achieve energy efficiency of the production process

The intelligent electricity metering system is designed to collect data from electricity meters in an automatic mode (i.e. without the direct participation of the electricity consumer and other persons). Intelligent energy metering systems rely on a network of smart meters and have a number of new features: bidirectional interaction with meters; automated processing and storage of large amounts of data; flexible and user-friendly interface; active involvement of consumers in the process of energy management

Pass/Fail Quality Assessment in Last Mile Smart Metering Networks Based on PRIME Interface.

The pass/fail form is one of the presentation methods of quality assessment results. The authors, as part of a research team, participated in the process of creating the PRIME interface analyzer. The PRIME interface is a standardized interface—considered as communication technology for smart metering wired networks, which are specific kinds of sensor networks. The frame error ratio (FER) assessment and its presentation in the pass/fail form was one of the problems that needed to be solves in the PRIME analyzer project. In this paper, the authors present their method of a unified FER assessment, which was implemented in the PRIME analyzer, as one of its many functionalities. The need for FER unification is the result of using different modulation types and an optional forward error correction mechanism in the PRIME interface. Having one unified FER and a threshold value makes it possible to present measurement results in the pass/fail form. For FER unification, the characteristics of FER vs. signal-to-noise ratio, for all modulations implemented in PRIME, were used in the proposed algorithm (and some are presented in this paper). In communication systems, the FER value is used to forecast the quality of a link or service, but using PLC technology, forecasting is highly uncertain due to the main noise. The presentation of the measurement results in the pass/fail form is important because it allows unskilled staff to make many laborious measurements in last mile smart metering networks.

Reducing the Intrusiveness of Energy and Water End-Use Disaggregation via Social Media and Users Interactions

Water end-use disaggregation from smart-metered water consumption data is key to design water demand management strategies. Yet, despite large investments for smart metering networks, few water utilities are actually exploiting the potential of end-use-based consumer profiling. This is mostly due to the intrusiveness of existing disaggregation algorithms, which require intensive and time consuming human interaction for extracting appliance-specific information and estimating the end-use patterns. We propose to explore the potential for social media in facilitating the interactions between water utilities and water users in order to collect consumption diaries. The evaluation of the value of this user-generated information is performed by using the collected diaries as input for a disaggregation algorithm, which is shown to attain acceptable performance in reproducing the end-use patterns.

A Possible Smart Metering System Evolution for Rural and Remote Areas Employing Unmanned Aerial Vehicles and Internet of Things in Smart Grids.

The way of generating and distributing energy throughout the electrical grid to all users is evolving. The concept of Smart Grid (SG) took place to enhance the management of the electrical grid infrastructure and its functionalities from the traditional system to an improved one. To measure the energy consumption of the users is one of these functionalities that, in some countries, has already evolved from a periodical manual consumption reading to a more frequent and automatic one, leading to the concept of Smart Metering (SM). Technology improvement could be applied to the SM systems to allow, on one hand, a more efficient way to collect the energy consumption data of each user, and, on the other hand, a better distribution of the available energy through the infrastructure. Widespread communication solutions based on existing telecommunication infrastructures instead of using ad-hoc ones can be exploited for this purpose. In this paper, we recall the basic elements and the evolution of the SM network architecture focusing on how it could further improve in the near future. We report the main technologies and protocols which can be exploited for the data exchange throughout the infrastructure and the pros and cons of each solution. Finally, we propose an innovative solution as a possible evolution of the SM system. This solution is based on a set of Internet of Things (IoT) communication technologies called Low Power Wide Area Network (LPWAN) which could be employed to improve the performance of the currently used technologies and provide additional functionalities. We also propose the employment of Unmanned Aerial Vehicles (UAVs) to periodically collect energy consumption data, with evident advantages especially if employed in rural and remote areas. We show some preliminary performance results which allow assessing the feasibility of the proposed approach.

Information security in WSN applied to smart metering networks based on cryptographic techniques

The principle assaults on a Wireless Sensor Network (WSN) essentially influence the uprightness and accessibility of the data gathered, for example, Deni-al of Service, Blackhole, Wormhole, and assault on the data being transmitted. Privacy is not an important security objective because the data caught by the sensors are typically not delicate or mystery from individuals. A remote sensor organizes applied to shrewd metering frameworks might be adequately powerful as far as robotization and adjustment of the information that is gathered, however, if the system doesn’t have satisfactory security, both the client and the organization offering the support might be influenced by assaults on the respectability and accessibility of the data transmitted. This research proposes the use of MESH encryption techniques and Star topology to find the best combination that meets the requirements of a Smart Metering System.

MDRP: An Energy-Efficient Multi-Disjoint Routing protocol in WSNs for Smart Grids

Abstract Rapid increase in sensor electronics has expanded the call for sensor networks in IoT-based devices. Smart grid is a part of IoT framework, which can be used to screen and manage traffic congestion, electricity influxes, extreme weather, and so on. This is done through a network of transmission lines, smart sensors, and smart meters. It is required to distribute and accumulate information remotely on timely basis from different stages of the grid. The periodic data from the smart meters are transferred to MDMS through WSN’s. In WSN’s, depletion of energy due to unequal load on the sensors is a serious issue, which is to be addressed as it affects the operations of the entire network. To assist these traffic requirements and to boost the network lifetime, asynchronous work sleep cycle approach can be used to create node connections. In this article, an energy-efficient adaptive fuzzy-based multi-disjoint routing protocol in WSN’s for smart grids abbreviated as (MDRP) is proposed, where the next hop node is decided through fuzzy logic. Once the subsequent node is decided, a spanning tree is constructed with the sink node as its root, which calculates the optimal path cost, to transmit the collected data. Furthermore, the simulation results show that the proposed MDRP performs better in terms of network lifetime, packet delivery ratio, total energy consumption, etc.

An Actor-Critic Deep Reinforcement Learning Approach for Transmission Scheduling in Cognitive Internet of Things Systems

The cognitive Internet of Things (CIoT) has attracted much interest recently in wireless networks due to its wide applications in smart cities, intelligent transportation systems, and smart metering networks. However, how to smartly schedule the packet transmission in CIoT systems is still a key challenge, that is, how to design a smart agent to realize the intelligent decision making and effective interoperability. In this paper, we model the system state transformation as a Markov decision process, and an actor-critic deep reinforcement learning algorithm based on a fuzzy normalized radial basis function neural network (called AC-FNRBF) is proposed to efficiently solve the intelligent transmission scheduling problem in CIoT systems under high-dimensional variables. The proposed AC-FNRBF algorithm can better approximate both the action function of the actor and the state–action value function of the critic without requiring the system prior knowledge, and a new reward function is established to maximize the system benefit, which jointly takes the transmission packet rate, the system throughput, the power consumption, and the transmission delay into account. Moreover, the AC-FNRBF has the ability to adjust its learning structure and parameters in dynamic environments. Simulation results verify that the proposed algorithm achieves higher transmission packet rate and system throughput with lower power consumption and transmission delay, compared with other existing reinforcement learning algorithms.

Frame-Type-Aware Static Time Slotted Channel Hopping Scheduling Scheme for Large-Scale Smart Metering Networks

Time-slotted channel hopping (TSCH) medium access control is a promising technology for the construction of reliable large-scale smart metering networks. However, the existing TSCH scheduling methods do not meet the requirements of large-scale smart metering applications. In particular, link throughput limits exist, which yield packet latency and buffer overflows. In this paper, we propose a static TSCH scheduling scheme that permits all nodes in the TSCH network to transmit or receive frames in any slot. To reduce network control message collisions, we define the broadcast slots and unicast slots individually. To assess the performance of the proposed TSCH scheduling scheme, an evaluation is performed in a real-world testbed. The proposed scheduling scheme achieves a high packet delivery ratio (PDR), even in large-scale and densely deployed networks. In most scenarios, the reliability required by smart metering services is achieved. In a 100-node network, in particular, the proposed scheduling method achieves a PDR exceeding 99%, even when 350-byte packets are collected every 60 s. The scheme and results reported in this study have potential application as guidelines for implementation of large-scale TSCH-based smart metering networks.

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.

The open blockchain-aided multi-agent symbiotic cyber–physical systems

Cyber–physical systems combine physical objects or systems with integrated computational facilities and data storage. From that perspective, Smart Grids are a mixture of physical actuators, sensors, physical communication networks; and cyber computational and communication protocols and algorithms. In our work, we propose to extend the applicability of decentralized blockchain consensus protocols to the broad field of Cyber–Physical systems. Our contribution includes a proposal of a new family of cyber–physical systems, an in-depth discussion of new possibilities and inherent shortcomings. The proposed coupling of the data storage mechanisms, communication and consensus protocols, allows for deployment of self-sustaining cyber–physical environments in which all the mission-critical aspects in both the cyber and physical layer are effectively incentivized, coordinated and maintained. This includes the essential data storage, data exchange, but also the production, transmission and distribution of energy. To the best of our knowledge, it is the first such a comprehensive undertaking toward symbiotic cyber–physical systems and environments. The proposed family of systems is decentralized and does not imply the necessity of reliance on trusted third parties. We propose and discuss an architecture which incorporates physical, blockchain-enabled sensors and actuators capable of monitoring and altering parameters of the underlying physical layer. We analyze a particular instance of a blockchain-aided CPS’, where we are concerned with the power grid at both the micro and macro-grid level. At the macro-grid level we explore the possibility of utilizing blockchain-enabled physical actuators. These theoretical actuators are able to introduce savings by a near real-time routing of energy and enable for tracking of power losses thanks to decentralized accountability. At the micro-grid level we propose a network of blockchain-enabled smart meters to coordinate real-time auction-based energy trade. To glue together the elements of such an open, trustless, decentralized system, we discuss an intrinsic communication protocol capable of rewarding intermediaries of a data exchange for each transmitted byte. We tackle the feasibility, security and accountability challenges which we have faced and which will need to be considered by future architects of the new, exciting family of cyber–physical systems.

Radio Resource Management in Machine-to-Machine Communications—A Survey

In futuristic wireless communications, a massive number of devices need to access networks with diverse quality of service (QoS) requirements. It is estimated that the number of connected devices will exceed 20 billions in 2020, and machine-to-machine (M2M) devices will account for nearly half of total connected devices. However, existing cellular systems and wireless standards, designed primarily for human-to-human (H2H) communications focusing on reducing access latency, increasing data rate, and system throughput, are not well suited for M2M communications that require massive connections, diverse QoS requirements, and low energy consumption. Radio resource management (RRM) in conventional H2H communications aims at improving spectrum efficiency and energy efficiency. Similarly, RRM also plays a vital role in M2M communications. In this paper, we make a comprehensive survey on state-of-the-art research activities on RRM in M2M communications. First, we discuss the issues on RRM for machine-type communications in LTE/LTE-A cellular networks including access control, radio resource allocation, power management, and the latest 3GPP standards supporting M2M communications. Acknowledging the fact that a single technology can not support all M2M applications, we discuss RRM issues for unlicensed band radio access technologies in M2M capillary networks, including IEEE 802.11ah, Bluetooth low energy, ZigBee, and smart metering networks. We also survey M2M RRM methods in heterogeneous networks consisting of cellular networks, capillary networks, and ultra dense networks. Finally, we review recent standard activities and discuss the open issues and research challenges.

Optical environmental sensing in wireless smart meter network

In recent years, the traditional power grid is undergoing a profound revolution due to the advent and development of smart grid. Many hard and challenging issues of the traditional grid such as high maintenance costs, poor scalability, low efficiency, and stability can be effectively handled and solve in the wireless smart grid (WSG) by utilizing the modern wireless sensor technology. In a WSG, data are collected by sensors at first and then transmitted to the base station through the wireless network. The control centre is responsible for taking actions based on this received data. Traditional sensors are failing to provide accurate and reliable data in WSG, and optical fiber based sensor are emerging as an obvious choice due to the advancement of optical fiber sensing technology, accuracy, and reliability. This paper presents a WSG platform integrated with optic fiber-based sensors for real-time monitoring. To demonstrate the validity of the concept, fresh water sensing of refractive index (RI) was first experimented with an optical fiber sensor. The sensing mechanism functions with the reflectance at the fiber’s interface where reflected spectra’s intensity is registered corresponding to the change of RI in the ambient environment. The achieved sensitivity of the fabricated fiber sensor is 29.3 dB/RIU within the 1.33–1.46 RI range. An interface between the measured optical spectra and the WSG is proposed and demonstrated, and the data acquired is transmitted through a network of wireless smart meters.

Hybrid Cryptography Algorithm with Precomputation for Advanced Metering Infrastructure Networks

Two-way communication has been identified as the smart grid flagship feature that enables the smart grid to attain its outcomes over the legacy power grid. Integrating communication networks into the power grid will motivate malicious attackers to target information exchange. Therefore, achieving secure and authentic communication in the smart grid networks is an indispensable requirement. In this paper, we propose a sophisticated hybrid encryption scheme that incorporates public and symmetric key encryptions to secure smart metering network. Elliptic Curve Integrated Encryption Scheme (ECIES) and Advanced Encryption Scheme (AES) are chosen as the building blocks for the proposed scheme. In order to optimize the computation overhead of ECIES, a precomputation procedure is presented to provide faster encryption/decryption. The proposed technique provides data integrity, confidentiality and authenticity as well as it resists against false data injection and message reply attacks. Simulation results show that the proposed approach surpasses some of the existing schemes in terms of computation, communication and storage overhead.

Analysis of the Regulatory Requirements for the Smart Grid in Chile

In this article are analyzed and discussed what should be the rules that must be applied in Chile to deploy the smart grid. It examines what kinds of standards can be applied in various systems of the mains: in the generation, transmission and distribution are the characteristics of the rules for the transmission of data. It analyzes the characteristics of the network of smart meters, and there are regulations that must be met.

Increasing the Effective Range of Smart Meter Home Area Network

In this letter, we present a potential novel solution to increase the transmission range of the home energy network of electricity smart meters. Conventionally, smart meters use low-power radio technologies and suffer from high signal attenuation as the signal is propagated through multiple radio-absorbing walls in a property. This limits the range of the radio link between the meter and connected devices, such as communications hubs, smart appliances, and in-hand displays. The potential solution presented in this letter uses the observation that at high microwave frequencies, the ac mains distribution cables can act as a low-loss ``leaky feeder'' cable so enabling signal to be distributed to each room more efficiently than directly via through the air. This letter reports on the testing of this concept for the first time in five properties of various construction types. The results demonstrate a good validity of the proposed method.

A Hybrid Signature-based Iterative Disaggregation algorithm for Non-Intrusive Load Monitoring

Information on residential power consumption patterns disaggregated at the single-appliance level is an essential requirement for energy utilities and managers to design customized energy demand management strategies. Non-Intrusive Load Monitoring (NILM) techniques provide this information by decomposing the aggregated electric load measured at the household level by a single-point smart meter into the individual contribution of each end-use. Despite being defined non-intrusive, NILM methods often require an intrusive data sampling process for training purpose. This calibration intrusiveness hampers NILM methods large-scale applications. Other NILM challenges are the limited accuracy in reproducing the end-use consumption patterns and their trajectories in time, which are key to characterize consumers’ behaviors and appliances efficiency, and the poor performance when multiple appliances are simultaneously operated. In this paper we contribute a hybrid, computationally efficient, algorithm for NILM, called Hybrid Signature-based Iterative Disaggregation (HSID), based on the combination of Factorial Hidden Markov Models, which provide an initial approximation of the end-use trajectories, and Iterative Subsequence Dynamic Time Warping, which processes the end-use trajectories in order to match the typical power consumption pattern of each appliance. In order to deal with the challenges posed by intrusive training, a supervised version of the algorithm, requiring appliance-level measurements for calibration, and a semi-supervised version, retrieving appliance-level information from the aggregate smart-metered signal, are proposed. Both versions are demonstrated onto a real-world power consumption dataset comprising five different appliances potentially operated simultaneously. Results show that HSID is able to accurately disaggregate the power consumption measured from a single-point smart meter, thus providing a detailed characterization of the consumers’ behavior in terms of power consumption. Numerical results also demonstrate that HSID is robust with respect to noisy signals and scalable to dataset including a large set of appliances. Finally, the algorithm can be successfully used in non-intrusive experiments without requiring appliance-level measurements, ultimately opening up new opportunities to foster the deployment of large-scale smart metering networks, as well as the design and practical implementation of personalized demand management strategies.