Data-driven optimization for seismic-resilient power network planning

dc.article.number106628
dc.catalogadorjwg
dc.contributor.authorOneto Schiappacasse, Alfredo Ernesto
dc.contributor.authorLorca Gálvez, Álvaro Hugo
dc.contributor.authorFerrario, Elisa
dc.contributor.authorPoulos Campbell, Alan John
dc.contributor.authorLlera Martin, Juan Carlos de la
dc.contributor.authorNegrete Pincetic, Matías Alejandro
dc.date.accessioned2025-04-16T22:27:20Z
dc.date.available2025-04-16T22:27:20Z
dc.date.issued2024
dc.description.abstractMany regions of the planet are exposed to seismic hazards that can cause devastating consequences on power systems. Due to these systems’ crucial role, the evaluation and planning for their safe and reliable operation are paramount. This paper develops a novel data-driven optimization framework to assess the power network’s seismic resilience and plan cost-effective investments for its enhancement. Under a robust optimization scheme, an earthquake attacker–defender model finds the worst-case realization of random earthquake network contingencies within an uncertainty set defined with a large number of scenarios generated by state-of-the-art engineering methods. Moreover, data-driven stochastic-robust optimization is employed in a two-stage seismic-resilient power network planning model, leveraging multiple seismic sources’ distributional information. Transmission line expansions and siting and sizing of battery energy storage systems are decided in the first stage, while the second stage decides operational variables. Experiments on a 281-node Chilean power system provide insights for seismic-resilient planning and demonstrate the efficiency of the proposed approach.
dc.fechaingreso.objetodigital2025-04-16
dc.format.extent13 páginas
dc.fuente.origenORCID
dc.identifier.doi10.1016/j.cor.2024.106628
dc.identifier.eissn1873-765X
dc.identifier.issn0305-0548
dc.identifier.urihttps://doi.org/10.1016/j.cor.2024.106628
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/103346
dc.identifier.wosidWoS_ID: 001218201400001
dc.information.autorucEscuela de Ingeniería; Oneto Schiappacasse, Alfredo Ernesto; S/I; 245300
dc.information.autorucEscuela de Ingeniería; Lorca Gálvez, Álvaro Hugo; 0000-0002-9864-0932; 148348
dc.information.autorucEscuela de Ingeniería; Poulos Campbell, Alan John; S/I; 177702
dc.information.autorucEscuela de Ingeniería; Llera Martin, Juan Carlos de la; 0000-0002-9064-0938; 53086
dc.information.autorucEscuela de Ingeniería; Negrete Pincetic, Matías Alejandro; S/I; 13212
dc.language.isoen
dc.revistaComputers & Operations Research
dc.rights.licenseCC BY-NC-ND Atribución-NonComercial-NoDerivadas Internacional 4.0
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectOR in energy
dc.subjectData-driven optimization
dc.subjectRobust optimization
dc.subjectPower systems resilience
dc.subjectSeismic hazards
dc.subject.ddc620
dc.subject.deweyIngenieríaes_ES
dc.titleData-driven optimization for seismic-resilient power network planning
dc.typeartículo
dc.volumen166
sipa.codpersvinculados245300
sipa.codpersvinculados148348
sipa.codpersvinculados177702
sipa.codpersvinculados53086
sipa.codpersvinculados13212
sipa.indexWOS
sipa.trazabilidadORCID;2024-03-25
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