102230 20230519145342.0 doi 10.3390/en14072028 sideral 124413 ART-2021-124413 eng Beyza, Jesus Universidad de Zaragoza (orcid)0000-0003-3992-4393 Integrated risk assessment for robustness evaluation and resilience optimisation of power systems after cascading failures 2021 Access copy available to the general public Unrestricted Power systems face failures, attacks and natural disasters on a daily basis, making robustness and resilience an important topic. In an electrical network, robustness is a network’s ability to withstand and fully operate under the effects of failures, while resilience is the ability to rapidly recover from such disruptive events and adapt its structure to mitigate the impact of similar events in the future. This paper presents an integrated framework for jointly assessing these concepts using two complementary algorithms. The robustness model, which is based on a cascading failure algorithm, quantifies the degradation of the power network due to a cascading event, incorporating the circuit breaker protection mechanisms of the power lines. The resilience model is posed as a mixed-integer optimisation problem and uses the previous disintegration state to determine both the optimal dispatch and topology at each restoration stage. To demonstrate the applicability of the proposed framework, the IEEE 118-bus test network is used as a case study. Analyses of the impact of variations in both generation and load are provided for 10 simulation scenarios to illustrate different network operating conditions. The results indicate that a network’s recovery could be related to the overload capacity of the power lines. In other words, a power system with high overload capacity can withstand higher operational stresses, which is related to increased robustness and a faster recovery process. info:eu-repo/grantAgreement/ES/MICINN/PID2019-104711RB-100 info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 3.252 2021 ENERGY & FUELS 80 / 119 = 0.672 2021 Q3 T3 0.653 2021 Energy (miscellaneous) 2021 Q1 Energy Engineering and Power Technology 2021 Q1 Fuel Technology 2021 Q1 Control and Optimization 2021 Q1 Engineering (miscellaneous) 2021 Q1 5.0 2021 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Yusta, Jose M. Universidad de Zaragoza (orcid)0000-0003-3174-9703 5009 535 Universidad de Zaragoza Dpto. Ingeniería Eléctrica Área Ingeniería Eléctrica 14, 7 (2021), 2028 [18 pp.] ENERGIES Energies 1996-1073 3093235 http://zaguan.unizar.es/record/102230/files/texto_completo.pdf Versión publicada 2714516 http://zaguan.unizar.es/record/102230/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:102230 articulos driver 2023-05-18-13:16:37 ARTICLE