cris.boxmetadata.label.title
Robust Multi-Stage Substation Expansion Planning Considering Stochastic Demand
cris.boxmetadata.label.dateissued
01 browse.startsWith.months.may 2016
cris.boxmetadata.label.accesslevel
open access
cris.boxmetadata.label.resourcetype
journal article
cris.boxmetadata.label.authors
Franco J.F.
Rider M.J.
Romero R.
cris.boxmetadata.label.publisher
Institute of Electrical and Electronics Engineers Inc.
cris.boxmetadata.label.abstract
This paper presents a novel mixed-integer second-order cone programming model for the robust multi-stage substation expansion planning problem considering stochastic demand. The stochastic nature of the demands is considered through a robust model that uses chance constraints to guarantee that the substation capacity limits are satisfied within a given robustness probability. Furthermore, a multi-objective formulation that takes into account the total expected expansion planning cost and the robustness probability related to the violation of the substation capacity limits is proposed. The optimal solution of the proposed model is guaranteed by the convexity of the formulation, when classical optimization techniques are used in its solution. The results found (construction of new substations, reinforcement of existing substations, and service area of each substation) for two test systems demonstrate the efficiency and robustness of the proposed model. Additionally, Monte Carlo simulations were carried out in order to evaluate the extent to which the solutions found were able to satisfy the substation capacity limits.
cris.boxmetadata.label.citationstartpage
2125
cris.boxmetadata.label.citationendpage
2134
cris.boxmetadata.label.volume
31
cris.boxmetadata.label.issue
3
cris.boxmetadata.label.language
English
cris.boxmetadata.label.ocdeknowledgeArea
Ingeniería eléctrica, Ingeniería electrónica
Matemáticas
cris.boxmetadata.label.subjects
cris.boxmetadata.label.doi
cris.boxmetadata.label.scopusidentifier
2-s2.0-84937231609
cris.boxmetadata.label.source
IEEE Transactions on Power Systems
cris.boxmetadata.label.containerissn
08858950
cris.boxmetadata.label.sponsor
This work was supported by the Brazilian institutions CNPq, FEPISA and FAPESP (grant number 2012/01100-6). Paper no. TPWRS-01582-2014.
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