Robust Dynamic Transmission and Renewable Generation Expansion Planning: Walking Towards Sustainable Systems

Recent breakthroughs in Dynamic Transmission Network Expansion Planning (DTNEP) have demonstrated that the use of robust optimization, while maintaining the full temporal dynamic complexity of the problem, renders the capacity expansion planning problem considering uncertainties computationally trac...

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Autores: Roldán, Cristina, Sánchez de la Nieta, Agustín Alejandro, García Bertrand, Raquel, Mínguez, Roberto
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Universidad de Castilla-La Mancha
Repositorio:RUIdeRA. Repositorio Institucional de la UCLM
OAI Identifier:oai:ruidera.uclm.es:10578/16411
Acceso en línea:https://hdl.handle.net/10578/16411
Access Level:acceso abierto
Palabra clave:Power systems
Renewable generation expansion planning
Robust optimization
Transmission network expansion planning
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spelling Robust Dynamic Transmission and Renewable Generation Expansion Planning: Walking Towards Sustainable SystemsRoldán, CristinaSánchez de la Nieta, Agustín AlejandroGarcía Bertrand, RaquelMínguez, RobertoPower systemsRenewable generation expansion planningRobust optimizationTransmission network expansion planningRecent breakthroughs in Dynamic Transmission Network Expansion Planning (DTNEP) have demonstrated that the use of robust optimization, while maintaining the full temporal dynamic complexity of the problem, renders the capacity expansion planning problem considering uncertainties computationally tractable for real systems. In this paper an adaptive robust formulation is proposed that considers, simultaneously: i) a year-by-year integrated representation of uncertainties and investment decisions, ii) the capacity expansion lines have and iii) the construction and/or dismantling of renewable and conventional generation facilities as well. The Dynamic Transmission Network and Renewable Generation Expansion Planning (DTNRGEP) problem is formulated as a three-level adaptive robust optimization problem. The first level minimizes the investment costs for the transmission network and generation expansion planning, the second level maximizes the costs of operating the system with respect to uncertain parameters, while the third level minimizes those operational costs with respect to operational decisions. The method is tested on two cases: i) an illustrative example based on the Garver IEEE system and ii) a case study using the IEEE 118-bus system. Numerical results from these examples demonstrate that the proposed model enables optimal decisions to be made in order to reach a sustainable power system, while overcoming problem size limitations and computational intractability for realistic cases.Elsevier201820182018info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://hdl.handle.net/10578/16411reponame:RUIdeRA. Repositorio Institucional de la UCLMinstname:Universidad de Castilla-La ManchaInglésENE2015-63879-RPOII-2014-012-PGI20163388info:eu-repo/semantics/openAccessoai:ruidera.uclm.es:10578/164112026-05-27T07:36:41Z
dc.title.none.fl_str_mv Robust Dynamic Transmission and Renewable Generation Expansion Planning: Walking Towards Sustainable Systems
title Robust Dynamic Transmission and Renewable Generation Expansion Planning: Walking Towards Sustainable Systems
spellingShingle Robust Dynamic Transmission and Renewable Generation Expansion Planning: Walking Towards Sustainable Systems
Roldán, Cristina
Power systems
Renewable generation expansion planning
Robust optimization
Transmission network expansion planning
title_short Robust Dynamic Transmission and Renewable Generation Expansion Planning: Walking Towards Sustainable Systems
title_full Robust Dynamic Transmission and Renewable Generation Expansion Planning: Walking Towards Sustainable Systems
title_fullStr Robust Dynamic Transmission and Renewable Generation Expansion Planning: Walking Towards Sustainable Systems
title_full_unstemmed Robust Dynamic Transmission and Renewable Generation Expansion Planning: Walking Towards Sustainable Systems
title_sort Robust Dynamic Transmission and Renewable Generation Expansion Planning: Walking Towards Sustainable Systems
dc.creator.none.fl_str_mv Roldán, Cristina
Sánchez de la Nieta, Agustín Alejandro
García Bertrand, Raquel
Mínguez, Roberto
author Roldán, Cristina
author_facet Roldán, Cristina
Sánchez de la Nieta, Agustín Alejandro
García Bertrand, Raquel
Mínguez, Roberto
author_role author
author2 Sánchez de la Nieta, Agustín Alejandro
García Bertrand, Raquel
Mínguez, Roberto
author2_role author
author
author
dc.subject.none.fl_str_mv Power systems
Renewable generation expansion planning
Robust optimization
Transmission network expansion planning
topic Power systems
Renewable generation expansion planning
Robust optimization
Transmission network expansion planning
description Recent breakthroughs in Dynamic Transmission Network Expansion Planning (DTNEP) have demonstrated that the use of robust optimization, while maintaining the full temporal dynamic complexity of the problem, renders the capacity expansion planning problem considering uncertainties computationally tractable for real systems. In this paper an adaptive robust formulation is proposed that considers, simultaneously: i) a year-by-year integrated representation of uncertainties and investment decisions, ii) the capacity expansion lines have and iii) the construction and/or dismantling of renewable and conventional generation facilities as well. The Dynamic Transmission Network and Renewable Generation Expansion Planning (DTNRGEP) problem is formulated as a three-level adaptive robust optimization problem. The first level minimizes the investment costs for the transmission network and generation expansion planning, the second level maximizes the costs of operating the system with respect to uncertain parameters, while the third level minimizes those operational costs with respect to operational decisions. The method is tested on two cases: i) an illustrative example based on the Garver IEEE system and ii) a case study using the IEEE 118-bus system. Numerical results from these examples demonstrate that the proposed model enables optimal decisions to be made in order to reach a sustainable power system, while overcoming problem size limitations and computational intractability for realistic cases.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018
2018
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10578/16411
url https://hdl.handle.net/10578/16411
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv ENE2015-63879-R
POII-2014-012-P
GI20163388
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RUIdeRA. Repositorio Institucional de la UCLM
instname:Universidad de Castilla-La Mancha
instname_str Universidad de Castilla-La Mancha
reponame_str RUIdeRA. Repositorio Institucional de la UCLM
collection RUIdeRA. Repositorio Institucional de la UCLM
repository.name.fl_str_mv
repository.mail.fl_str_mv
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