000095735 001__ 95735
000095735 005__ 20210902121612.0
000095735 0247_ $$2doi$$a10.1016/j.physa.2019.123169
000095735 0248_ $$2sideral$$a113775
000095735 037__ $$aART-2020-113775
000095735 041__ $$aeng
000095735 100__ $$0(orcid)0000-0003-3992-4393$$aBeyza Bravo, Jesús$$uUniversidad de Zaragoza
000095735 245__ $$aAssessing the criticality of interdependent power and gas systems using complex networks and load flow techniques
000095735 260__ $$c2020
000095735 5060_ $$aAccess copy available to the general public$$fUnrestricted
000095735 5203_ $$aGas 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.
000095735 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/ENE2016-77172-R
000095735 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000095735 590__ $$a3.263$$b2020
000095735 591__ $$aPHYSICS, MULTIDISCIPLINARY$$b28 / 85 = 0.329$$c2020$$dQ2$$eT1
000095735 592__ $$a0.64$$b2020
000095735 593__ $$aStatistics and Probability$$c2020$$dQ2
000095735 593__ $$aCondensed Matter Physics$$c2020$$dQ2
000095735 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000095735 700__ $$aRuiz Paredes, Héctor Francisco
000095735 700__ $$0(orcid)0000-0003-2457-0422$$aGarcía Paricio, Eduardo$$uUniversidad de Zaragoza
000095735 700__ $$0(orcid)0000-0003-3174-9703$$aYusta Loyo, José María$$uUniversidad de Zaragoza
000095735 7102_ $$15009$$2535$$aUniversidad de Zaragoza$$bDpto. Ingeniería Eléctrica$$cÁrea Ingeniería Eléctrica
000095735 773__ $$g540 (2020), 123169  [15 pp.]$$pPhysica, A$$tPhysica A: Statistical Mechanics and its Applications$$x0378-4371
000095735 8564_ $$s3452144$$uhttps://zaguan.unizar.es/record/95735/files/texto_completo.pdf$$yPostprint
000095735 8564_ $$s369277$$uhttps://zaguan.unizar.es/record/95735/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
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000095735 951__ $$a2021-09-02-08:41:34
000095735 980__ $$aARTICLE