Assessing the criticality of interdependent power and gas systems using complex networks and load flow techniques

Beyza Bravo, Jesús (Universidad de Zaragoza) ; Ruiz Paredes, Héctor Francisco ; García Paricio, Eduardo (Universidad de Zaragoza) ; Yusta Loyo, José María (Universidad de Zaragoza)

Resumen: Gas and electricity transmission systems are increasingly interconnected, and an attack on certain assets can cause serious energy supply disruptions, as stated in recommendation (EU) 2019/553 on cybersecurity in the energy sector, recently approved by the European Commission. This study aims to assess the vulnerability of coupled natural gas and electricity infrastructures and proposes a method based on graph theory that incorporates the effects of interdependencies between networks. This study is built in a joint framework, where two different attack strategies are applied to the integrated systems: (1) disruptions to facilities with most links and (2) disruptions to the most important facilities in terms of flow. The vulnerability is measured after each network attack by quantifying the unmet load (UL) through a power flow analysis and calculating the topological damage of the systems with the geodesic vulnerability (v) index. The proposed simulation framework is applied to a case study that consists of the IEEE 118-bus test system and a 25-node high-pressure natural gas network, where both are coupled through seven gas-fired power plants (GFPPs) and three electric compressors (ECs). The methodology is useful for estimating vulnerability in both systems in a coupled manner, studying the propagation of interdependencies in the two networks and showing the applicability of the v index as a substitute for the UL index.

Idioma: Inglés

DOI: 10.1016/j.physa.2019.123169

Año: 2020

Publicado en: Physica A: Statistical Mechanics and its Applications 540 (2020), 123169 [15 pp.]
ISSN: 0378-4371

Factor impacto JCR: 3.263 (2020)

Categ. JCR: PHYSICS, MULTIDISCIPLINARY rank: 28 / 84 = 0.333 (2020) - Q2 - T2

Factor impacto SCIMAGO: 0.64 - Statistics and Probability (Q2) - Condensed Matter Physics (Q2)

Financiación: info:eu-repo/grantAgreement/ES/MINECO/ENE2016-77172-R

Tipo y forma: Article (PostPrint)

Área (Departamento): Área Ingeniería Eléctrica (Dpto. Ingeniería Eléctrica)