This paper proposes a method of assessing some aspects of the resilience of distribution networks with particular reference to the heatwave phenomena using a probabilistic approach. Combining the characteristics of the network with the probability of failure of the electrical grid components most affected by the heatwaves (e.g., the medium voltage cable joints) and the weather forecasts in a given territory, maps of risk of failure, or dually of the resilience of the network, can be developed by means of a Geographic Information System (GIS) environment. The approach exploits knowledge graph technology, linking different kinds of data, information, and models to an ontology to support the integrated processing and visualization of relevant information for decision-making. This contribution is part of the activities of the project 'Network 4 Energy Sustainable Transition - NEST,' funded under the National Recovery and Resilience Plan (NRRP).

Mapping Resilience of Distribution Networks Against Heatwaves

Pollino M.;Villani M. L.
2024-01-01

Abstract

This paper proposes a method of assessing some aspects of the resilience of distribution networks with particular reference to the heatwave phenomena using a probabilistic approach. Combining the characteristics of the network with the probability of failure of the electrical grid components most affected by the heatwaves (e.g., the medium voltage cable joints) and the weather forecasts in a given territory, maps of risk of failure, or dually of the resilience of the network, can be developed by means of a Geographic Information System (GIS) environment. The approach exploits knowledge graph technology, linking different kinds of data, information, and models to an ontology to support the integrated processing and visualization of relevant information for decision-making. This contribution is part of the activities of the project 'Network 4 Energy Sustainable Transition - NEST,' funded under the National Recovery and Resilience Plan (NRRP).
2024
distribution networks
GIS
heatwaves
knowledge graph
resilience
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12079/84887
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