135 research outputs found
Statistical Estimation Framework for State Awareness in Microgrids Based on IoT Data Streams
This paper presents an event-triggered statistical estimation strategy and a data collection architecture for situational awareness (SA) in microgrids. An estimation agent structure based on the event-triggered Kalman filter is proposed and implemented for state estimation layer of the SA using long range wide area network (LoRAWAN) protocol. A setup has been developed which provides enormous data collection capabilities from smart meters in order to realize an adequate level of SA in microgrids. Thingsboard Internet of things (IoT) platform is used for the SA visualization with a customized dashboard. It is shown that by using the developed estimation strategy, an adequate level of SA can be achieved with a minimum installation and communication cost to have an accurate average state estimation of the microgrid
IoT-based digital twin for energy cyber-physical systems: design and implementation
With the emergence of distributed energy resources (DERs), with their associated communication and control complexities, there is a need for an efficient platform that can digest all the incoming data and ensure the reliable operation of the power system. The digital twin (DT) is a new concept that can unleash tremendous opportunities and can be used at the different control and security levels of power systems. This paper provides a methodology for the modelling of the implementation of energy cyber-physical systems (ECPSs) that can be used for multiple applications. Two DT types are introduced to cover the high-bandwidth and the low-bandwidth applications that need centric oversight decision making. The concept of the digital twin is validated and tested using Amazon Web Services (AWS) as a cloud host that can incorporate physical and data models as well as being able to receive live measurements from the different actual power and control entities. The experimental results demonstrate the feasibility of the real-time implementation of the DT for the ECPS based on internet of things (IoT) and cloud computing technologies. The normalized mean-square error for the low-bandwidth DT case was 3.7%. In the case of a high-bandwidth DT, the proposed method showed superior performance in reconstructing the voltage estimates, with 98.2% accuracy from only the controllersâ states
A novel distributed privacy-preserving control and data collection method for IoT-centric microgrids
Abstract The privacy of electricity consumers has become one of the most critical subjects in designing smart meters and their proliferation. In this work, a multilayer architecture has been proposed for anonymous data collection from smart meters, which provides: (1) The anonymity of information for thirdâparty data consumers; (2) Secure communication to utility provider network for billing purposes; (3) Online control of data sharing for endâusers; (4) Low communication costs based on available Internet of things (IoT) communication protocols. The core elements of this architecture are, first, the digital twin equivalent of the cyberâphysical system and, second, the Tangle distributed ledger network with IOTA cryptocurrency. In this architecture, digital twin models are updated in realâtime by information received from trusted nodes of the Tangle distributed network anonymously. A smallâscale laboratory prototype based on this architecture has been developed using the dSPACE SCALEXIO realâtime simulator and openâsource software tools to prove the feasibility of the proposed solution. The numerical results confirm that after a few seconds of anomaly detection, the microgrid was fully stabilized around its operating point with less than 5% deviation during the transition time
Software Defined Networks based Smart Grid Communication: A Comprehensive Survey
The current power grid is no longer a feasible solution due to
ever-increasing user demand of electricity, old infrastructure, and reliability
issues and thus require transformation to a better grid a.k.a., smart grid
(SG). The key features that distinguish SG from the conventional electrical
power grid are its capability to perform two-way communication, demand side
management, and real time pricing. Despite all these advantages that SG will
bring, there are certain issues which are specific to SG communication system.
For instance, network management of current SG systems is complex, time
consuming, and done manually. Moreover, SG communication (SGC) system is built
on different vendor specific devices and protocols. Therefore, the current SG
systems are not protocol independent, thus leading to interoperability issue.
Software defined network (SDN) has been proposed to monitor and manage the
communication networks globally. This article serves as a comprehensive survey
on SDN-based SGC. In this article, we first discuss taxonomy of advantages of
SDNbased SGC.We then discuss SDN-based SGC architectures, along with case
studies. Our article provides an in-depth discussion on routing schemes for
SDN-based SGC. We also provide detailed survey of security and privacy schemes
applied to SDN-based SGC. We furthermore present challenges, open issues, and
future research directions related to SDN-based SGC.Comment: Accepte
A review of cyber-ranges and test-beds:current and future trends
Cyber situational awareness has been proven to be of value in forming a comprehensive understanding of threats and vulnerabilities within organisations, as the degree of exposure is governed by the prevailing levels of cyber-hygiene and established processes. A more accurate assessment of the security provision informs on the most vulnerable environments that necessitate more diligent management. The rapid proliferation in the automation of cyber-attacks is reducing the gap between information and operational technologies and the need to review the current levels of robustness against new sophisticated cyber-attacks, trends, technologies and mitigation countermeasures has become pressing. A deeper characterisation is also the basis with which to predict future vulnerabilities in turn guiding the most appropriate deployment technologies. Thus, refreshing established practices and the scope of the training to support the decision making of users and operators. The foundation of the training provision is the use of Cyber-Ranges (CRs) and Test-Beds (TBs), platforms/tools that help inculcate a deeper understanding of the evolution of an attack and the methodology to deploy the most impactful countermeasures to arrest breaches. In this paper, an evaluation of documented CR and TB platforms is evaluated. CRs and TBs are segmented by type, technology, threat scenarios, applications and the scope of attainable training. To enrich the analysis of documented CR and TB research and cap the study, a taxonomy is developed to provide a broader comprehension of the future of CRs and TBs. The taxonomy elaborates on the CRs/TBs dimensions, as well as, highlighting a diminishing differentiation between application areas
Edge intelligence in smart grids : a survey on architectures, offloading models, cyber security measures, and challenges
The rapid development of new information and communication technologies (ICTs) and
the deployment of advanced Internet of Things (IoT)-based devices has led to the study and implementation of edge computing technologies in smart grid (SG) systems. In addition, substantial work
has been expended in the literature to incorporate artificial intelligence (AI) techniques into edge
computing, resulting in the promising concept of edge intelligence (EI). Consequently, in this article,
we provide an overview of the current state-of-the-art in terms of EI-based SG adoption from a range
of angles, including architectures, computation offloading, and cybersecurity c oncerns. The basic
objectives of this article are fourfold. To begin, we discuss EI and SGs separately. Then we highlight
contemporary concepts closely related to edge computing, fundamental characteristics, and essential
enabling technologies from an EI perspective. Additionally, we discuss how the use of AI has aided
in optimizing the performance of edge computing. We have emphasized the important enabling
technologies and applications of SGs from the perspective of EI-based SGs. Second, we explore both
general edge computing and architectures based on EI from the perspective of SGs. Thirdly, two basic
questions about computation offloading are discussed: what is computation offloading and why do
we need it? Additionally, we divided the primary articles into two categories based on the number of
users included in the model, either a single user or a multiple user instance. Finally, we review the
cybersecurity threats with edge computing and the methods used to mitigate them in SGs. Therefore,
this survey comes to the conclusion that most of the viable architectures for EI in smart grids often
consist of three layers: device, edge, and cloud. In addition, it is crucial that computation offloading
techniques must be framed as optimization problems and addressed effectively in order to increase
system performance. This article typically intends to serve as a primer for emerging and interested
scholars concerned with the study of EI in SGs.The Council for Scientific and Industrial Research (CSIR).https://www.mdpi.com/journal/jsanElectrical, Electronic and Computer Engineerin
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