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.
Highlights
Energy systems (ESs) are complex systems characterized by the heterogeneity of subsystems and objects, as well as the variety and diversity of interconnections and interdependencies between them
CoTnhcleuasritoinclse proposes an original formulation of the monitoring ESs problem
A fuzzy cognitive approach allows one to represent various interdependencies between ESs objects in the form of fuzzy impact relations, provides the possibility of using fuzzy causal algebra for preliminary analysis of ESs
Summary
Energy systems (ESs) are complex systems characterized by the heterogeneity of subsystems and objects, as well as the variety and diversity of interconnections and interdependencies between them. In terms of increasing ESs objects interdependence and complexity, united by different interrelations into clusters, the actual tasks of stability analysis and monitoring the dynamics of changes in such clusters cannot be well performed using standard methods These problems are caused by a large number of heterogeneous indicators, the uncertainty of systemic and external factors, and the vagueness of information. In [19], a method for analyzing fuzzy impact relations on the basis of a fuzzy cognitive approach is considered, and a set of indicators for identifying system clusters is substantiated The analysis of the ESs clusters’ stability consists in the analysis of the results of the transitive closure of fuzzy impact relations between the objects of each of the identified ESs clusters. The choice of indicators for identifying ESs clusters; Preliminary clustering of objects and identification of ESs clusters; Preliminary analysis of the ESs clusters’ stability
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