Mostrar el registro sencillo del ítem
dc.contributor.author
Alvarez, Gonzalo Exequiel
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.date.available
2022-10-13T10:21:52Z
dc.date.issued
2022-04
dc.identifier.citation
Alvarez, Gonzalo Exequiel; Stochastic optimization considering the uncertainties in the electricity demand, natural gas infrastructures, photovoltaic units, and wind generation; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 160; 4-2022; 1-19
dc.identifier.issn
0098-1354
dc.identifier.uri
http://hdl.handle.net/11336/172833
dc.description.abstract
The integration of modern generation technologies along with traditional ones awakens interest at the global level. However, the main difficulties to operate these systems are the uncertainties in the predictions of electricity and gas demands, along with the wind and photovoltaic generation. Regarding mathematical programming, the main drawback is the computational effort needed to solve the models that represent the aforementioned items. In this regard, this paper proposes a stochastic model of two-stage that integrates electric power, hydraulic, and natural gas systems. Several effects are considered, not properly addressed in the literature. Besides, to reduce the computational requirement, a Mixed Integer Linear Programming model and a reduction algorithm for scenarios are implemented. To prove the effectiveness of this proposal, an IEEE 31-bus system integrated into a hydraulic and natural gas system is studied. Results demonstrate that the stochastic approach offers cost reductions up to 4% and provides flexibility for contingencies.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Pergamon-Elsevier Science Ltd
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
ELECTRIC POWER SYSTEM
dc.subject
ENERGY SYSTEM INTEGRATION
dc.subject
MONTE CARLO SIMULATION
dc.subject
NATURAL GAS GENERATION AND TRANSPORTATION
dc.subject
PV GENERATION
dc.subject
RENEWABLE SOURCES
dc.subject
TWO-STAGE STOCHASTIC PROGRAM
dc.subject.classification
Ingeniería Eléctrica y Electrónica
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.subject.classification
Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.title
Stochastic optimization considering the uncertainties in the electricity demand, natural gas infrastructures, photovoltaic units, and wind generation
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2022-07-04T20:16:59Z
dc.journal.volume
160
dc.journal.pagination
1-19
dc.journal.pais
Países Bajos
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Alvarez, Gonzalo Exequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
dc.journal.title
Computers and Chemical Engineering
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0098135422000552
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.compchemeng.2022.107712
Archivos asociados