A network approach in the study of cascading effects critical infrastructures

• Дата: 2024
• Автори: Хоменко, О. М., Сенченко, В. Р., Коваль, О. В.
• Формат: Стаття
• Мова: Ukrainian
• Опубліковано: Інститут проблем реєстрації інформації НАН України 2024
• Теми: critical infrastructure; cascade failure; Domino effect; graph theory; Bayesian network; Petri net; Markov chain; ontology
• Онлайн доступ: http://drsp.ipri.kiev.ua/article/view/316908
• Назва журналу: Data Recording, Storage & Processing

A cascading failure of critical infrastructure can lead to serious consequences in various areas of human activity, so it is important to detect and take preventive measures in time to reduce the consequences of the cascade. The article presents an analysis of the capabilities of the network approach in building and researching a cascade model based on graph theory. This provides an understanding of the complex interdependencies that exist in real systems. With the help of metrics that determine the quality of the graph model, it is possible to determine the centrality and importance of the nodes of the model, to evaluate the characteristics of objects, to calculate the probabilities of transitions and the occurrence of critical events, to study different scenarios of the development of the cascade and the consequences of the impact. Electric power industry is considered as a field of application. The use of graph theory and network analysis allows us to present the energy network as a complex interconnected network of nodes and finite constraints, which have semantic content in the form of: power line, transformer substation, impedance, etc. The study considers the application of various network approaches - Bayesian network, Petri network, Markov chain and presents the results of a comparative analysis of their capabilities in the study of the behavior of systems during a cascade. The analysis of these methods with reference to the fields of application allows to more perfectly adapt these methods to specific needs, as well as to form requirements for software tools for modeling and monitoring the negative consequences of cascading effects. Tabl.: 1. Fig.: 9. Refs: 51 titles.