Smart Grid Communication Research Articles

Data protection enhancement in smart grid communication: An efficient multi-layer encrypting approach based on chaotic techniques and steganography

In this study, a multi-layer encryption system is proposed through which sensitive and important data in smart grids can be secured from unauthorized persons as well as cyber threats. The suggested system is analyzed using fundamental performance assessment metrics say as average processing times across ten runs, peak signal-to-noise ratio (PSNR), and root mean square error (RMSE). The encryption process involves hiding the data encrypted by a digital dictionary and the advanced encryption standard (AES) algorithm in an image. In this way, AES encryption suggests rapid processing with a short average time per each block; similarly, the decryption technique, which includes the dictionary and AES decryption also renders the results in a justified computational time nominating it as a practical approach. It is worth noting that the small key era and dictionary construction instances provoke innovations in the general efficiency of the encryption mechanism. The conducted study, based on recorded values for PSNR, RMSE, UACI, and NPCR, demonstrates that the proposed multi-layer encryption system, which incorporates dictionary encryption and AES, is a robust and a fast method to shield important information and attaining a balance between protection and computational time.

Joint Cooperative Computation and Communication for Demand-Side NOMA-MEC Systems With Relay Assistance in Smart Grid Communications

Joint Cooperative Computation and Communication for Demand-Side NOMA-MEC Systems With Relay Assistance in Smart Grid Communications

A review of integrated modeling and simulation of control and communication systems in Smart Grid

In order to provide effective, safe, and dependable grid operation, the use of information and communication technologies (ICT) for real-time monitoring and control of the Smart Grid (SG) has grown in recent years. With such technologies, our system evolved into a complex cyber-physical system (CPS) in which communications networks play an important role in the dynamic performance of SG. Therefore, it is imperative to perform integrated modeling and simulation (IMS) of control and communication systems to evaluate the SG CPS for new control strategies or select appropriate communication technologies for specific applications before implementing them on a larger scale. This paper provides a state-of-the-art literature review about co-simulation, one of the key methods to perform an IMS. The paper starts with a brief review of the SG communication infrastructure, communication, and SG simulators used for co-simulations to give the readers an understanding of the requirements and issues for modeling and simulating SG communication systems. Then, detailed literature about the co-simulation platform covers the individual simulators used, the key features, test case advantages, and the limitations of different co-simulation platforms. In the discussion section, comparative analyses of co-simulation platforms are provided. The review summarizes critical challenges and opportunities in co-simulation, emphasizing the potential of IMS for advancing SG design and operation.

A New Semi-Quantum Two-Way Authentication Protocol between Control Centers and Neighborhood Gateways in Smart Grids.

To address the potential threat to the power grid industry posed by quantum computers and ensure the security of bidirectional communication in smart grids, it is imperative to develop quantum-safe authentication protocols. This paper proposes a semi-quantum bidirectional authentication protocol between a control center (CC) and a neighboring gateway (NG). This method uses single photons to facilitate communication between the CC and the NG. Security analysis demonstrates that the protocol can effectively resist common attack methods, including double CNOT attacks, impersonation attacks, interception-measurement-retransmission attacks, and entanglement-measurement attacks. Comparisons with other protocols reveal that this protocol has significant advantages, making it more appealing and practical for real-world applications. Finally, by simulating the protocol on the IBM quantum simulator, this protocol not only validates the theoretical framework but also confirms the practical feasibility of the protocol.

Smart grid data compression and reconstruction by wavelet packet transform

A smart grid is a power network from generation to consumers and provides beneficial, steady, and safe electricity. It utilizes smart meters for billing, phasor measurement units to check the system's health., etc. As a result, it contains enormous volumes of real-time data that may be shared and stored by users, control centers, and services in a smart grid. It weakens the smart grid's communication networks. The size of the data in a smart grid will grow extremely in the future. As a result, it must reduce distortion in data compression and denoise while minimizing the demand on storage and communication networks. The goal of data compression and denoising should be to maximally conserve the useful data while accurately reflecting the state of the system and providing sufficient data regeneration at the receiving end. This paper has used lower-order different wavelets to represent a design to compress and reconstruct data at level three using wavelet Packet Transform. It works on the phasor measurement unit's current magnitude and voltage sag signals.•The proposed design has a better compression ratio.•Low reconstruction error.•This design is easy to access, systematic, profitable, and not time-consuming.

A blockchain‐based resilient and secure framework for events monitoring and control in distributed renewable energy systems

AbstractThe rapid and green energy transition is essential to deal with the fast‐growing energy needs in both public and industrial sectors. This has paved the way to integrate distributed renewable energy resources () such as solar, hydro, wind, and geothermal into the power grid (). Wind and solar are free, zero‐carbon emission, and everlasting power sources that contribute 5% and 7% of global electricity generation, respectively. Therefore, the fast, secure, and reliable integration of these green is critical to achieve the instant energy demands. Smart grid due to inherited characteristics such as intelligent sensing, computing, and communication technologies can effectively integrate the . However, the existing smart grid communication architecture faces various cyberattacks, resulting in poor integration, monitoring, and control of . In this respect, blockchain technology can provide fast, secure, and efficient end‐to‐end communication between in the smart grid. In this study, the authors propose a blockchain‐based resilient and secure scheme called for wireless sensor networks ‐based events monitoring and control in . Experimental studies and performance analyses are carried out to predict the efficiency of the proposed scheme by considering numerous standard metrics. The extensive numerical results demonstrated that the proposed scheme is significant in terms of secure, resilient, and reliable information transmission for in .

An Enhanced Authentication and Key Agreement Protocol for Smart Grid Communication

An Enhanced Authentication and Key Agreement Protocol for Smart Grid Communication

An efficient neighbor nodes trust tagging model for optimized route detection in smart grids with secure data transmission

Smart Grids are the control and transmission networks of the future; they allow suppliers and customers to interact in real time to optimize and intelligently manage resources. Although wireless mesh network technology can facilitate these smart functionalities, it is important to address the vulnerabilities and cyber-attack risks that are inherent to it. Smart Grid's reliance on the Internet amplifies security concerns. A number of methods have been proposed to address this issue; while some have made promises, they all need substantial amounts of computational resources. With this technology, channels based on trust can be set up. The security of the system is built utilizing a family relationship-based method, which makes use of measures that may be used to gauge a node's originality. Additionally, the power consumption and signal strength of the node are taken into account. The complexity and extent of the network need the development of new types of smart grid communication. Finding a way to detect and thwart major assaults on routing protocols is another design challenge. Smart grids rely on these protocols in its data system for efficient interchange of renewable energy. A unique secure energy routing mechanism is developed in this proposed model for secure data communication. In the proposed model, a new method for Neighbor Nodes Trust Tagging Model for Optimized Route Detection (NNTT-ORD) is proposed for establishing secure route for data communication in smart grids. The proposed model is compared with the existing model and the results represent that the proposed model route provides a secure environment for data transmission.

An improved lightweight and privacy preserving authentication scheme for smart grid communication

Smart grid is an efficient and reliable technical framework for controlling computers and automation equipment, and how to ensure the communication security in smart grid is an important issue. Cryptographic authentication scheme is a feasible solution, and the existing authentication schemes for smart grid seek to ensure better performance. Some existing authentication schemes lack comprehensive security considerations and have security or privacy vulnerabilities, which makes them vulnerable to specific attacks. The paper reviews a recent scheme ISG-SLAS (Yu and Park, 2022) and analyzes its potential insecure aspects in detail, including unable to resist ESL attack, cannot provide un-traceability and etc. To this end, the paper designs an improved authentication scheme for smart grid based on symmetric cryptography. Through informal security analyses and formal security analyses with real-or-random (ROR) model and Scyther platform, the security of the proposed scheme is demonstrated. From the perspective of performance, the proposed scheme is compared with ten advanced authentication schemes for smart grid, and the results show that the proposed scheme excels other recent schemes in computational overhead, communication overhead and storage overhead, reduced by 10.1%, 30.8% and 36.1% of ISG-SLAS and 58.9%, 64.1% and 24.3% of the average value of all alternatives respectively.

Generative artificial intelligence for distributed learning to enhance smart grid communication

Machine learning models are the backbone of smart grid optimization, but their effectiveness hinges on access to vast amounts of training data. However, smart grids face critical communication bottlenecks due to the ever-increasing volume of data from distributed sensors. This paper introduces a novel approach leveraging Generative Artificial Intelligence (GenAI), specifically a type of pre-trained Foundation Model (FM) architecture suitable for time series data due to its efficiency and privacy-preserving properties. These GenAI models are distributed to agents, or data holders, empowering them to fine-tune the foundation model with their local datasets. By fine-tuning the foundation model, the updated model can produce synthetic data that mirrors real-world grid conditions. The server aggregates fine-tuned model from all agents and then generates synthetic data which considers all data collected in the grid. This synthetic data can be used to train global machine learning models for specific tasks like anomaly detection and energy optimization. Then, the trained task models are distributed to agents in the grid to leverage them. The paper highlights the advantages of GenAI for smart grid communication, including reduced communication burden, enhanced privacy through anonymized data transmission, and improved efficiency and scalability. By enabling a distributed and intelligent communication architecture, GenAI introduces a novel way for a more secure, efficient, and sustainable energy future.

Leveraging 5G Network Capabilities for Smart Grid Communication

This paper presents a comprehensive investigation into the architecture and components of 5G networks, focusing on their suitability for smart grid applications. With the increasing complexity and demands of modern energy infrastructure, there is a growing need for reliable and low-latency communication systems to support critical smart grid operations. This paper explores key features of 5G networks, including network slicing, massive MIMO (Multiple Input Multiple Output), and low-latency communication protocols like URLLC (Ultra-Reliable Low Latency Communication), and examines how these features can be harnessed to address the unique requirements of smart grid environments. Through a detailed analysis of each component, this paper sheds light on the design considerations, deployment strategies, and performance implications of leveraging 5G technology for smart grid communication. Furthermore, practical insights, challenges, and future research areas are discussed to guide the development of next-generation smart grid solutions.

StegoBackoff: Creating a Covert Channel in Smart Grids Using the Backoff Procedure of IEEE 802.11 Networks

A smart grid constitutes an electrical infrastructure that integrates communication technologies to optimize electricity production, distribution, and consumption. Within the smart grid, IEEE 802.11 networks play a crucial role in facilitating communication between smart meters and data collectors, operating within a shared transmission medium. However, a notable challenge arises due to the lack of certainty regarding the genuine identity of data recipients. In response, we present a solution—a novel covert channel leveraging the IEEE 802.11 backoff procedure—to transmit data that requires special protection. Implemented using the ns-3 simulator, our covert channel achieved a throughput of 140,000 bps when single covert station realized transmission in the wireless channel, and 880 bps in a populated environment characterized by high traffic volumes. This performance metric shows that our mechanism is better than other covert channels, where the performance in saturated conditions usually does not exceed several hundred bps. This covert channel represents a new approach to fortifying data integrity and privacy within smart grid communication.

Integration of LiFi, BPL, and Fiber Optic Technologies in Smart Grid Backbone Networks: A Proposal for Exploiting the LiFi LED Street Lighting Networks of Power Utilities and Smart Cities

This paper presents a proposal for extending an existing terabit-class backbone network architecture to enable the use of LiFi technology by power utilities and smart cities. The proposed architecture provides a practical means of integrating three smart grid communication technologies—fiber optics, BPL networks and LiFi LED street lighting networks—across the transmission and distribution power grids of smart cities. In addition to expanding the backbone communications network architecture, the paper provides a comprehensive overview of LiFi technology and analyzes the concept of LiFi LED street lighting networks in a smart city. The analytical investigation of the operation and performance of LiFi LED street lighting networks focuses on the following aspects: (i) typical LED street lighting configurations and default configuration parameter values encountered in smart sustainable cities; (ii) the applied LiFi channel model and corresponding default model parameters; (iii) SNR computations and LiFi channel classifications for a variety of scenarios; and (iv) available LiFi LED street lighting network architectures for integrating LiFi LED street lighting networks with the backbone network. The paper also discusses the potential benefits of LiFi LED street lighting networks for power utilities, smart cities and individuals.

Toward Wireless Smart Grid Communications: An Evaluation of Protocol Latencies in an Open-Source 5G Testbed

Fifth-generation networks promise wide availability of wireless communication with inherent security features. The 5G standards also outline access for different applications requiring low latency, machine-to-machine communication, or mobile broadband. These networks can be advantageous to numerous applications that require widespread and diverse communications. One such application is found in smart grids. Smart grid networks, and Operational Technology (OT) networks in general, utilize a variety of communication protocols for low-latency control, data monitoring, and reporting at every level. Transitioning these network communications from wired Wide Area Networks (WANs) to wireless communication through 5G can provide additional benefits to their security and network configurability. However, introducing these wireless capabilities may also result in a degradation of network latency. In this paper, we propose utilizing 5G for smart grid communications, and we evaluate the latency impacts of encapsulating GOOSE, Modbus, and DNP3 for transmission over a 5G network. The OpenAirInterface open-source library is utilized to deploy an in-lab 5G Core Network and gNB for testing with off-the-shelf User Equipment (UE). This creates an effective 5G test platform for experimenting with different OT protocols such as GOOSE. The results are validated by measuring two different Intelligent Electronic Devices’ contact closure times for each network configuration. These tests are also conducted for varying packet sizes in order to isolate different sources of network latency. Our study outlines the latency impact of communication over 5G for time-critical and non-critical applications regarding their transition toward private 5G-based OT network implementations. The conducted experiments illustrate that in the case of GOOSE packets, simple encapsulation may exceed the protocol’s time-critical nature, and, therefore, additional measures must be taken to ensure a viable transition of GOOSE to 5G services. However, non-critical applications are shown to be viable for migration to 5G.

Design and use of a wireless temperature measurement network system integrating artificial intelligence and blockchain in electrical power engineering.

This work aims to investigate the potential fire hazard stemming from the overheating of power equipment. The advent of the artificial intelligence era has facilitated the fusion of blockchain and Internet of Things (IoT) technologies. This work delves into the technical standards for IoT equipment monitoring and smart grid communication, and the IoT environment of power grid equipment. This work introduces a temperature monitoring network tailored for IoT wireless power equipment suitable for the power environment, and conducts system debugging in the power laboratory. The findings affirm that the temperature out-of-limit alarm testing has met the required criteria, confirming the system's ability to issue timely warnings when temperatures breach a predefined threshold, effectively avoiding high-temperature misfires. This work fully harnesses the secure and user-friendly operation of smart blockchain and the wireless sensing technology of the IoT to realize online monitoring and remote temperature measurement of the power system. It can effectively prevent equipment from overheating and damage, and promote the development of equipment condition monitoring technology in electric power engineering.

Improved IChOA-Based Reinforcement Learning for Secrecy Rate Optimization in Smart Grid Communications

Improved IChOA-Based Reinforcement Learning for Secrecy Rate Optimization in Smart Grid Communications

Performance Analysis of Smart Grid Communication Networks Using Co-Simulation

Performance Analysis of Smart Grid Communication Networks Using Co-Simulation

Generative Artificial Intelligence for Distributed Learning to Enhance Smart Grid Communication

Generative Artificial Intelligence for Distributed Learning to Enhance Smart Grid Communication

BCLM: a novel chaotic map for designing cryptography-based security mechanism for IEEE C37.118.2 PMU communication in smart grid

Abstract Today, creating a smart grid that is resistant to cyberattacks is a subject of utmost significance. One of the components of the smart grid that is most susceptible to a cyber-attack is the phasor measuring unit (PMU). The reason is that PMU employs IEEE C37.118.2 communication standards, which specify the structure and sequencing of data packets but offer no security measures. Users must implement the security techniques to ensure the protection of PMU data. Additionally, PMU communicates via a public wide-area network, raising the risk to security. In addition, PMU is a crucial component of the smart grid, enabling different crucial choices for the reliable functioning of the smart grid to be made using its data. This research suggests a chaos-based data encryption solution to close the knowledge gap and reduce the confidentiality assault on PMU data. For this, a brand-new boost converter logarithmic map (BCLM), a one-dimensional (1D) chaotic map, has been presented. The research demonstrates how the suggested chaotic map has better chaotic qualities than conventional chaotic maps. The pseudorandom generator is the chaotic BCLM system. The PMU data are encrypted using the random sequence produced by the BCLM chaotic system. The suggested chaotic map is not computationally demanding, making it simple to implement in a PMU device with limited resources.

Performance Comparison of Directed Acyclic Graph-Based Distributed Ledgers and Blockchain Platforms

Since the introduction of the first cryptocurrency, Bitcoin, in 2008, the gain in popularity of distributed ledger technologies (DLTs) has led to an increasing demand and, consequently, a larger number of network participants in general. Scaling blockchain-based solutions to cope with several thousand transactions per second or with a growing number of nodes has always been a desirable goal for most developers. Enabling these performance metrics can lead to further acceptance of DLTs and even faster systems in general. With the introduction of directed acyclic graphs (DAGs) as the underlying data structure to store the transactions within the distributed ledger, major performance gains have been achieved. In this article, we review the most prominent directed acyclic graph platforms and evaluate their key performance indicators in terms of transaction throughput and network latency. The evaluation aims to show whether the theoretically improved scalability of DAGs also applies in practice. For this, we set up multiple test networks for each DAG and blockchain framework and conducted broad performance measurements to have a mutual basis for comparison between the different solutions. Using the transactions per second numbers of each technology, we created a side-by-side evaluation that allows for a direct scalability estimation of the systems. Our findings support the fact that, due to their internal, more parallelly oriented data structure, DAG-based solutions offer significantly higher transaction throughput in comparison to blockchain-based platforms. Although, due to their relatively early maturity state, fully DAG-based platforms need to further evolve in their feature set to reach the same level of programmability and spread as modern blockchain platforms. With our findings at hand, developers of modern digital storage systems are able to reasonably determine whether to use a DAG-based distributed ledger technology solution in their production environment, i.e., replacing a database system with a DAG platform. Furthermore, we provide two real-world application scenarios, one being smart grid communication and the other originating from trusted supply chain management, that benefit from the introduction of DAG-based technologies.