Key performance aspects of an LTE FDD based Smart Grid communications network

Machine learning (ML)-based intrusion detection system (IDS) approaches have been significantly applied and advanced the state-of-the-art system security and defense mechanisms. In smart grid computing environments, security threats have been significantly increased as shared networks are commonly used, along with the associated vulnerabilities. However, compared to other network environments, ML-based IDS research in a smart grid is relatively unexplored, although the smart grid environment is facing serious security threats due to its unique environmental vulnerabilities. In this article, we conducted an extensive survey on ML-based IDS in smart grids based on the following key aspects: (1) The applications of the ML-based IDS in transmission and distribution side power components of a smart power grid by addressing its security vulnerabilities; (2) dataset generation process and its usage in applying ML-based IDSs in the smart grid; (3) a wide range of ML-based IDSs used by the surveyed papers in the smart grid environment; (4) metrics, complexity analysis, and evaluation testbeds of the IDSs applied in the smart grid; and (5) lessons learned, insights, and future research directions.

A smart grid is an intelligent power grid. In recent years, the smart grid environment and its applications are incorporated into a variety of areas. The smart grid environment, however, can expose much more information than the old environments. In the environment, smart devices can be media in the exposure of various and specific pieces of information as well as energy consumption. This poses a huge risk in that it, combined with other pieces of information, may expose much more information. The current smart grid environment raises a need to develop anonymous signature and authentication techniques to prevent privacy breaches. Trying to meet this need, the principal investigator conducted research for three years. This paper discusses both the research trends investigated by him and the limitations of the development research and future research in need. Smart grid security requires the development of encrypted anonymous authentication that is applicable to power plant security, including nuclear power plants as well as expandable test beds.

Smart grids are smart grids because they don't only transport electricity but also information that will become an active part of the electricity supply system. Smart grid evolution has, thus, a lot to gain through the exploitation of emerging Future Internet networking technologies for the efficient collection and management of the acquired information. The capabilities for interconnection of numerous intelligent networking devices, the advanced monitoring and control of dynamic networking infrastructures and the efficient handling of large volumes of data are research areas that have direct applicability into the smart grid design and operation. This article presents our insights for the design of a novel and open overlay networking architecture for leveraging end-to-end interconnection of physical or virtual objects, for achieving decentralized data management, and for providing distributed services in smart grid environments. The proposed architecture follows a layered-approach and extends or adapts a set of existing overlay and IP protocols. In addition, a smart grid business-oriented scenario is briefly presented in order to explain how future technologies may be used to fulfill contemporary society needs.

Synthetically analyze the power distribution communication network technology in the smart power grid link. It mainly includes the summary of the smart distribution network, electric power communication backbone network and then layer communication requirements, the network mode and the application mode of WLAN technology in the distribution network, EPON network technology, micropower wireless technology, PTN technology and power broadband wireless systems. State the demand of the smart power distribution business and put forward technical guidance for the smart power distribution communication network scheme. In view of the complex distribution network architecture, more nodes and scattered, complex business types data business needs, put forward the integrated solutions of optical fiber communication as the backbone access, wireless bandwidth, passive optical communication as the coverage, the short distance wireless communication as the main terminal access. It provides a reference for the communication plan of distribution side.

Smart Grid is the trend of next generation power distribution and network management that enable a two -- way interactive communication and operation between consumers and suppliers, so as to achieve intelligent resource management and optimization. The wireless mesh network technology is a promising infrastructure solution to support these smart functionalities, while it has some inherent vulnerabilities and cyber-attack risks to be addressed. As Smart Grid is heavily relying on the underlie communication networks, which makes their security and dependability issues critical to the entire smart grid technology. Several studies have been conducted in the field of Smart Grid security, but few works were focused on the dependability and its associated resource analysis of the control center networks. In this paper, we have investigated the dependability modeling and also resource allocation in redundant communication networks by adopting two mathematical approaches, Reliability Block Diagrams (RBD) and Stochastic Petri Nets (SPNs), to analyze the dependability of control center networks in Smart Grid environment. We have applied our proposed modeling approach in an extensive case study to evaluate the availability of smart gird networks with different redundancy mechanisms. A combination of dependability models and reliability importance are used to analyze the network availability according to the most important components. We also show the variation of network availability in accordance with Mean Time to Failure (MTTF) in different network architectures.

Smart Grid is undergoing a huge transformation with the rise of smart metering systems and integration of renewable sources of energy. Although privacy attacks on smart grid have received significant research interest, loss of availability due to cyber-attacks is an underexplored area. Availability can be impacted with numerous attack surfaces consisting of e.g., metering equipment, switches, communication network that can cause grid shutdown. In this paper, we develop novel, realistic mathematical models for studying the effects of loss of availability attacks within smart grid environments. In addition, we integrate our models as part of a permissioned Blockchain platform solution viz., SGChain that can help in recovering from such attacks by providing a secured transmission of customer utility usage amongst co-operating peers of grid operators. Building upon the concept of a demand-response (DR) signal, we enable a local grid operator to monitor the usage regularly via the Blockchain in order to calculate increasing or decreasing energy supply levels from distributors for subsequent time cycles. Through evaluation experiments, we study how meter data corruption attacks induce overconsumption of energy with three actual consumers over a period of 48 hours. The attacks and users are classified as low, medium and high levels to show the validity of our DR signal chaincode. Our results demonstrate that even under high impact attacks, our approach fosters self-regulation in smart grid environments for detection/mitigation of availability attacks, while also maintaining a stable grid energy state.

The conventional power grid has gone into transition and converted into what is called "smart grid The smart grid helps to bring reliability, monitoring, controllability, and efficiency. It provides a bidirectional flow of energy and communication. The major element of the smart grid is the communication networks. The smart grid system is comprised of different types of smart devices and heterogeneous networks. These communication networks are prone to many kinds of attacks such as Distributed Denial of Service (DDoS), Man In The Middle (MITM) and replay attacks. As a result, the smart grid is becoming a major target for cybercriminals. In this paper, the vulnerabilities and security issues exist in the smart grid are presented. Finally, the solutions for mitigating the attacks are discussed. It provides an overview of security issues present in the communication system in the smart grid. With this paper, readers can gain more understanding of security issues present in the smart grid communication systems, networks, and devices.

A new model of power system to identify critical elements for smart and bulk power transmission grid environment is presented in this paper. Proposed bidirectional power flow model under complex network framework can quantify the criticality of nodes whose removal would trigger cascading failure. The proposed model based centrality, which is an extension of nominal power flow based model, is able to find nodes whose removal exerts more stress on the system. Several measures of impact like path length increase, boosted connectivity loss, raised load loss and increase in number of overloaded lines justify the use of bidirectional power flow based model to evaluate the criticality in smart grid environment. Change in direction of power flow in various random lines of the test system has a very little effect on the rank of nodes in the critical list.

MQRP: Mobile sinks-based QoS-aware data gathering protocol for wireless sensor networks-based smart grid applications in the context of industry 4.0-based on internet of things

Cyber physical systems (CPSs) utilised in many of the critical infrastructures including the smart grid. The operational activities of smart grid's CPS use different industrial solution such as industrial control systems (ICS) for monitoring and controlling the physical architecture of smart grid. Therefore, it is quite essential to keep these industrial control systems secure and safe from potential hazards and cyber world as it may be harmful for human safety, strategic infrastructure of a country and also for the economy. The study gathered the scattered guidelines, best practices and policies available from various organisations such as National Institute of Standards and Technology (NIST), ISO, and North American Electric Reliability Corporation (NERC) for the purpose of developing safe and secure ICS security systems and also the knowledge about the issues involved in ICS security and protection. A conceptual framework is proposed and developed to address the shortcomings in-order to protect the ICS systems in a smart grid environment. The proposed framework was developed by reviewing related studies, standards and utilising IT security working experience. This framework will not only expand the horizon of knowledge but also provides pathway for the development of existing activities of CPS applications such as smart grid.

High-data-rate mobile multimedia applications can greatly increase energy consumption, leading to an emerging trend of addressing the “energy efficiency” aspect of mobile networks. Cognitive mobile networks with small cells are important techniques for meeting the high-data-rate requirements and improving the energy efficiency of mobile multimedia communications. However, most existing works do not consider the power grid, which provides electricity to mobile networks. Currently, the power grid is experiencing a significant shift from the traditional grid to the smart grid. In the smart grid environment, only considering energy efficiency may not be sufficient since the dynamics of the smart grid will have significant impacts on mobile networks. In this paper, we study green cognitive mobile networks with small cells in the smart grid environment. Unlike most existing studies on cognitive networks, where only the radio spectrum is sensed, our cognitive networks sense not only the radio spectrum environment but also the smart grid environment, based on which power allocation and interference management for multimedia communications are performed. We formulate the problems of electricity price decision, energy-efficient power allocation, and interference management as a three-stage Stackelberg game. A homogeneous Bertrand game with asymmetric costs is used to model price decisions made by the electricity retailers. A backward induction method is used to analyze the proposed Stackelberg game. Simulation results show that our proposed scheme can significantly reduce operational expenditure and CO2 emissions in cognitive mobile networks with small cells for multimedia communications.

Novel smart grids applications for energy management and traceability in heritage cities: Case study for city of Cuenca, Ecuador

Smart grid is an essential part of the world's changing energy landscape. The uptake of smart grid by utilities is however hampered by the perceived complexity and large capital investment required to implement resilient Information Communication Technology (ICT) and networks that can support self-healing smart grids. Furthermore, failure to meet stringent smart grid communication reliability requirements can have disastrous consequences for grid owners and users. Many of the challenges utilities face with their smart grid ICT network development plans can be attributed to a reliance on conventional designs centred on expanding network hardware infrastructure in vast grid networks. What is needed to overcome these challenges is alternative ways of designing smart grid communication networks, using software defined approaches. This paper proposes a framework that supports software defined designs by combining the principles of the Internet of Things (IoT) paradigm and Machine-to-Machine (M2M) communication. Using the frameworks of software defined systems and virtualisation, our proposed architecture aims to provide a more flexible and affordable approach to developing and maintaining grid communication networks while offering a high level of network reliability, required for various smart grid applications. An evaluation of the implementation of this architecture in a design, based on a real city distribution grid, shows that a software defined communication network is easy to implement when using virtual machines running on existing computer infrastructure and that it is capable of supporting the network functions required for improving communication reliability. We conclude that this approach can potentially promote the adoption of smart grid by utilities while offering new innovative ways for smart grid developers to improve their grid designs.

A smart grid connects components of power systems and communication networks through complex and interdependent relationships. The heterogeneous nature of these systems and interdependencies between their elements make them vulnerable to cyber attacks. Hence, reliable approaches should be used to secure the smart grid. In this paper, we propose a novel cyberattack failure propagation model in a smart grid environment. Our Realistic Failure Propagation (RFP) model addresses the system's heterogeneity by assigning different roles to its components. We define rules and interdependencies for failure propagation and propose a new process to study the behavior of cascading failures. The RFP model implements power flow analysis to ensure that all transmission lines work under their capacity and remove lines that exceed the capacity.

Smart grid significantly improves the functions of conventional power networks, but it also makes them more susceptible to attacks of different types. Using smart grid’s vulnerabilities, attackers may compromise the integrity and confidentiality of networks, and obtain access to them as a result. Intrusion Detection System (IDS) constitutes an important means to provide safe and reliable services in a smart grid environment. This paper proposes an intrusion detection model under smart grid environment that is widely distributed in the three-tier architecture of power grid system. The model introduces Random Forest (RF) into machine learning and Particle Swarm Optimization (PSO) into evolutionary computation. To improve the accuracy of the model, this paper taps into the adaptive strategy for continued adjustment concerning the flight attitude of particles, and uses multiple mutation methods to prevent the occurrence of local optimum. The AMPSO algorithm proposed in this paper performs well in benchmarking function tests, thereby providing effective guarantee for the improvement of RF classifier. According to simulation experiments based on test sets of NPL-KDD, the intrusion detection model proposed in this paper is highly effective and practical.