Understanding events for wide-area situational awareness

Basu, Chumki; Agrawal, Ankit; Hazra, Jagabondhu; Kumar, Ashok; Seetharam, Deva P.; Beland, J.; Guillon, Sébastien; Kamwa, Innocent; Lafond, C.

doi:10.1109/isgt.2014.6816408

Cited by 11 publications

(4 citation statements)

References 11 publications

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“…WASA has been realized by the combination of sophisticated technologies such as IoT into situational awareness, which enables the expansion of system monitoring at any time and from any location [146]. This paradigm aims to enable low latency and high throughput monitoring, archiving, reporting, and querying of the state of the power grid [147]. Additionally, WASA can aid power providers in responding quickly to network events, reducing the likelihood of catastrophic failures such as large-scale blackouts.…”

Section: Wide-area Situational Awarenessmentioning

confidence: 99%

Edge Intelligence in Smart Grids: A Survey on Architectures, Offloading Models, Cyber Security Measures, and Challenges

Molokomme

Onumanyi

Abu‐Mahfouz

2022

JSAN

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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 concerns. 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.

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Section: Wide-area Situational Awarenessmentioning

confidence: 99%

Edge Intelligence in Smart Grids: A Survey on Architectures, Offloading Models, Cyber Security Measures, and Challenges

Molokomme

Onumanyi

Abu‐Mahfouz

2022

JSAN

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“…It becomes practical to use phasor measurements to detect voltage instability in power system. Comparing with the conventional model-based approaches, PMU technology improves the computational speed for wide-area situational awareness [2]. Before PMUs are widely deployed in the system, the TE based methods, e.g., VIP method estimates the voltage stability margin by using local measurements at one location [12].…”

Section: Chapter 1 Introductionmentioning

confidence: 99%

Online Voltage Stability Monitoring and Control Using Limited Synchrophasor Measurements

Zhu

Liu

2020

2020 IEEE Power &Amp; Energy Society Innovative Smart Grid Technologies Conference (ISGT)

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“…In [9] the authors proposed an ontology-based framework for event understanding and representation in smart grids. The presented approach enables the extraction of high-level information from PMU data and evaluating semantic rules for the detection of basic events such as voltage level over a service area.…”

Section: B Ontology Approaches For Power System Networkmentioning

confidence: 99%

“…It enables powerful capabilities in controlling the level of details on information and automatically extracting, enhancing and analysing large amount of data. Several approaches with different applications of ontology were seen in power system domain that include system modelling, multi-type data management [2]- [4], big data analysis [5], [6], fault diagnosis [7], [8] and network security [9], [10].…”

Section: B Ontology Approaches For Power System Networkmentioning

confidence: 99%

Ontology-based approach for malicious behaviour detection in synchrophasor networks

Albalushi

Khan

McLaughlin

et al. 2017

2017 IEEE Power &Amp; Energy Society General Meeting

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Understanding events for wide-area situational awareness

Cited by 11 publications

References 11 publications

Edge Intelligence in Smart Grids: A Survey on Architectures, Offloading Models, Cyber Security Measures, and Challenges

Edge Intelligence in Smart Grids: A Survey on Architectures, Offloading Models, Cyber Security Measures, and Challenges

Online Voltage Stability Monitoring and Control Using Limited Synchrophasor Measurements

Ontology-based approach for malicious behaviour detection in synchrophasor networks

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