Communication Network Standards for Smart Grid Infrastructures

Demertzis, Konstantinos; Τσίκνας, Κωνσταντίνος; Taketzis, Dimitrios; Skoutas, Dimitrios N.; Skianis, Charalabos; Iliadis, Lazaros; Zoiros, Kyriakos E.

doi:10.3390/network1020009

Cited by 15 publications

(5 citation statements)

References 74 publications

(136 reference statements)

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“…Notably, smart grid standards may conflict one another, as many differences in functionality have been developed in different countries or geographic areas. For example, although the main standards for AMI are IEC/TR 62051, IEC 61968, IEC 61969 and AEIC Guidelines v. 3.0, China and the USA are implementing GB/Z 20965, and ANSI/ASHRAE 135-2008/ISO 16484-5/BACnet, respectively [176]. As a result, a consistent set of cross-cutting requirements among st the standards are difficult to define for facilitat ing the flow of classified information [177].…”

Section: G Standardsmentioning

confidence: 99%

“…For example, the IEC 61850 standard, which was initially introduced as a standard for substation communication, provides device interoperability between manufacturers. In recent years, this standard has been used for a variety of devices, such as smart meters, virtual power plants and vehicle-to-grid (V2G) [178].…”

Section: ) Interoperability Between Systems In the Smart Gridmentioning

confidence: 99%

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Current and Future Communication Solutions for Smart Grids: A Review

et al. 2022

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A smart grid provides a bidirectional flow of electricity and information whilst ensuring wellbalanced electricity supply and demand. The key enabler for the smart grid is its robust communication infrastructure. Choosing the best communication technology for the smart grid is crucial as it involves a mixture of critical and non-critical traffic. This study provides a comprehensive review on smart grid communication and its possible solutions for a reliable two-way communication toward supporting diversified power grid applications. Existing networking methods along with their advantages and weaknesses are highlighted for future research directions. The communication network architecture in the smart grid, with details on each networking technology, switching methods and medium for data communication, is critically reviewed to identify the existing research gaps. A discussion on issues and challenges encountered in smart grid communication for current implementation is highlighted together with the recommendations for further improvement. Overall, the highlighted issues and recommendations from this study are useful to researchers, technology providers and industries to develop new communication technologies for the smart grid that will provide reliable, robust, and suitable two-way communication in the future.

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Section: G Standardsmentioning

confidence: 99%

Section: ) Interoperability Between Systems In the Smart Gridmentioning

confidence: 99%

Current and Future Communication Solutions for Smart Grids: A Review

et al. 2022

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“…Different domains associated with smart grid are shown in Figure 7. [158]). The smart grid system was proposed by Arnold et al [159], which promises frameworks and road-maps for an efficient and intelligent approach to managing energy supply and consumption.…”

Section: F Smart Grid Forensicsmentioning

confidence: 99%

Application of Artificial Intelligence to Network Forensics: Survey, Challenges and Future Directions

et al. 2022

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Network forensics focuses on the identification and investigation of internal and external network attacks, the reverse engineering of network protocols, and the uninstrumented investigation of networked devices. It lies at the intersection of digital forensics, incident response and network security. Network attacks exploit software and hardware vulnerabilities and communication protocols. The scope of a network forensic investigation can range from Internet-wide down to a single device's network traffic. Network analysis tools (NATs) aid security professionals and law enforcement in the capturing, identification and analysis of network traffic. However, in most instances, the sheer volume of data to be analyzed is enormous and, despite some built-in NAT automation, the investigation of network traffic is often an arduous process. Furthermore, significant expert time remains wasted in the investigation of a high frequency of false positive alerting from automated systems. To address this globally impacting problem, artificial intelligence based approaches are becoming increasingly employed to automatically detect attacks and increase network traffic classification accuracy. This paper provides a comprehensive survey of the state-of-the-art in network forensics and the application of expert systems, machine learning, deep learning, and ensemble/hybrid approaches to a range of application areas in the field. These include network traffic analysis, intrusion detection systems, Internetof-Things devices, cloud forensics, DNS tunneling, smart grid forensics, and vehicle forensics. In addition, the current challenges and future research directions for each of the aforementioned application areas is discussed.

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“…Securing essential energy network infrastructure is closely tied to preventing the exploitation of wired and wireless communication protocols extensively used in smart grids [13]. The vulnerabilities of these protocols can result in the compromise of critical devices and applications, the denial or non-availability of essential services, and even the extensive or total denial of services, significantly expanding the range of threats to which energy infrastructure is vulnerable [14,15].…”

Section: Literature Reviewmentioning

confidence: 99%

An Ensemble Transfer Learning Spiking Immune System for Adaptive Smart Grid Protection

et al. 2022

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The rate of technical innovation, system interconnection, and advanced communications undoubtedly boost distributed energy networks’ efficiency. However, when an additional attack surface is made available, the possibility of an increase in attacks is an unavoidable result. The energy ecosystem’s significant variety draws attackers with various goals, making any critical infrastructure a threat, regardless of scale. Outdated technology and other antiquated countermeasures that worked years ago cannot address the complexity of current threats. As a result, robust artificial intelligence cyber-defense solutions are more important than ever. Based on the above challenge, this paper proposes an ensemble transfer learning spiking immune system for adaptive smart grid protection. It is an innovative Artificial Immune System (AIS) that uses a swarm of Evolving Izhikevich Neural Networks (EINN) in an Ensemble architecture, which optimally integrates Transfer Learning methodologies. The effectiveness of the proposed innovative system is demonstrated experimentally in multiple complex scenarios that optimally simulate the modern energy environment. The most significant findings of this work are that the transfer learning architecture’s shared learning rate significantly adds to the speed of generalization and convergence approach. In addition, the ensemble combination improves the accuracy of the model because the overall behavior of the numerous models is less noisy than a comparable individual single model. Finally, the Izhikevich Spiking Neural Network used here, due to its dynamic configuration, can reproduce different spikes and triggering behaviors of neurons, which models precisely the problem of digital security of energy infrastructures, as proved experimentally.

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Communication Network Standards for Smart Grid Infrastructures

Cited by 15 publications

References 74 publications

Current and Future Communication Solutions for Smart Grids: A Review

Current and Future Communication Solutions for Smart Grids: A Review

Application of Artificial Intelligence to Network Forensics: Survey, Challenges and Future Directions

An Ensemble Transfer Learning Spiking Immune System for Adaptive Smart Grid Protection

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