LAPSE:2023.19490
Published Article
LAPSE:2023.19490
Energy System Monitoring Based on Fuzzy Cognitive Modeling and Dynamic Clustering
March 9, 2023
Abstract
A feature of energy systems (ESs) is the diversity of objects, as well as the variety and manifold of the interconnections between them. A method for monitoring ESs clusters is proposed based on the combined use of a fuzzy cognitive approach and dynamic clustering. A fuzzy cognitive approach allows one to represent the interdependencies between ESs objects in the form of fuzzy impact relations, the analysis results of which are used to substantiate indicators for fuzzy clustering of ESs objects and to analyze the stability of clusters and ESs. Dynamic clustering methods are used to monitor the cluster structure of ESs, namely, to assess the drift of cluster centers, to determine the disappearance or emergence of new clusters, and to unite or separate clusters of ESs.
A feature of energy systems (ESs) is the diversity of objects, as well as the variety and manifold of the interconnections between them. A method for monitoring ESs clusters is proposed based on the combined use of a fuzzy cognitive approach and dynamic clustering. A fuzzy cognitive approach allows one to represent the interdependencies between ESs objects in the form of fuzzy impact relations, the analysis results of which are used to substantiate indicators for fuzzy clustering of ESs objects and to analyze the stability of clusters and ESs. Dynamic clustering methods are used to monitor the cluster structure of ESs, namely, to assess the drift of cluster centers, to determine the disappearance or emergence of new clusters, and to unite or separate clusters of ESs.
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Keywords
dynamic clustering, energy system, fuzzy cognitive model, monitoring
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Suggested Citation
Borisov V, Dli M, Vasiliev A, Fedulov Y, Kirillova E, Kulyasov N. Energy System Monitoring Based on Fuzzy Cognitive Modeling and Dynamic Clustering. (2023). LAPSE:2023.19490
Author Affiliations
Borisov V: Department of Computer Engineering, National Research University “Moscow Power Engineering Institute” (Smolensk Branch), 214013 Smolensk, Russia
Dli M: Department of Information Technology in Economics and Management, National Research University “Moscow Power Engineering Institute” (Smolensk Branch), 214013 Smolensk, Russia
Vasiliev A: Rector, Moscow University for Industry and Finance “Synergy”, 129090 Moscow, Russia
Fedulov Y: Department of Computer Engineering, National Research University “Moscow Power Engineering Institute” (Smolensk Branch), 214013 Smolensk, Russia
Kirillova E: Department of Information Technology in Economics and Management, National Research University “Moscow Power Engineering Institute” (Smolensk Branch), 214013 Smolensk, Russia
Kulyasov N: Higher School of Tariff Regulation, Plekhanov Russian University of Economics, 117997 Moscow, Russia
Dli M: Department of Information Technology in Economics and Management, National Research University “Moscow Power Engineering Institute” (Smolensk Branch), 214013 Smolensk, Russia
Vasiliev A: Rector, Moscow University for Industry and Finance “Synergy”, 129090 Moscow, Russia
Fedulov Y: Department of Computer Engineering, National Research University “Moscow Power Engineering Institute” (Smolensk Branch), 214013 Smolensk, Russia
Kirillova E: Department of Information Technology in Economics and Management, National Research University “Moscow Power Engineering Institute” (Smolensk Branch), 214013 Smolensk, Russia
Kulyasov N: Higher School of Tariff Regulation, Plekhanov Russian University of Economics, 117997 Moscow, Russia
Journal Name
Energies
Volume
14
Issue
18
First Page
5848
Year
2021
Publication Date
2021-09-15
ISSN
1996-1073
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Original Submission
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PII: en14185848, Publication Type: Journal Article
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Published Article
LAPSE:2023.19490
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https://doi.org/10.3390/en14185848
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Mar 9, 2023
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