Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/160236
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dc.contributor.authorHongxing Yeen_US
dc.contributor.authorJianhui Wangen_US
dc.contributor.authorZuyi Lien_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:20:21Z-
dc.date.available2020-04-06T07:20:21Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/TPWRS.2016.2569609en_US
dc.identifier.urihttp://localhost/handle/Hannan/160236-
dc.description.abstractWith increasing renewable penetration in power systems, considerable research efforts have been focused on how to accommodate the uncertainties from renewables in the Security-Constraint Unit Commitment (SCUC) problem. One of the candidate approaches to handling uncertainties is the two-stage Robust SCUC (RSCUC), which enables system to survive in any scenario. The survivability is guaranteed by the solution optimality of the max-min problem in the second stage. However, as the non-convex max-min problem is NP-hard, it is difficult to get the exact optimal solution in acceptable time. In this paper, we propose a new efficient formulation which recasts the max-min problem to a Mixed Integer Programming (MIP) problem using Binary Expansion (BE). The upper bound of the gap between the new MIP problem and the original max-min problem is derived. The gap, which quantifies the solution optimality of the max-min problem, is controllable. Two effective acceleration techniques are proposed to improve the performance of the MIP problem by eliminating inactive flow constraints and decomposing time-coupled uncertainty budget constraints. Accordingly, the computation burden of solving the max-min problem is reduced tremendously. The simulation results for the IEEE 118-Bus system validate and demonstrate the effectiveness of the new BE-based solution approach to the two-stage RSCUC and the acceleration techniques.en_US
dc.format.extent1237,en_US
dc.format.extent1247en_US
dc.publisherIEEEen_US
dc.relation.haspart7470428.pdfen_US
dc.titleMIP Reformulation for Max-Min Problems in Two-Stage Robust SCUCen_US
dc.typeArticleen_US
dc.journal.volume32en_US
dc.journal.issue2en_US
Appears in Collections:2017

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7470428.pdf581.2 kBAdobe PDF
Full metadata record
DC FieldValueLanguage
dc.contributor.authorHongxing Yeen_US
dc.contributor.authorJianhui Wangen_US
dc.contributor.authorZuyi Lien_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:20:21Z-
dc.date.available2020-04-06T07:20:21Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/TPWRS.2016.2569609en_US
dc.identifier.urihttp://localhost/handle/Hannan/160236-
dc.description.abstractWith increasing renewable penetration in power systems, considerable research efforts have been focused on how to accommodate the uncertainties from renewables in the Security-Constraint Unit Commitment (SCUC) problem. One of the candidate approaches to handling uncertainties is the two-stage Robust SCUC (RSCUC), which enables system to survive in any scenario. The survivability is guaranteed by the solution optimality of the max-min problem in the second stage. However, as the non-convex max-min problem is NP-hard, it is difficult to get the exact optimal solution in acceptable time. In this paper, we propose a new efficient formulation which recasts the max-min problem to a Mixed Integer Programming (MIP) problem using Binary Expansion (BE). The upper bound of the gap between the new MIP problem and the original max-min problem is derived. The gap, which quantifies the solution optimality of the max-min problem, is controllable. Two effective acceleration techniques are proposed to improve the performance of the MIP problem by eliminating inactive flow constraints and decomposing time-coupled uncertainty budget constraints. Accordingly, the computation burden of solving the max-min problem is reduced tremendously. The simulation results for the IEEE 118-Bus system validate and demonstrate the effectiveness of the new BE-based solution approach to the two-stage RSCUC and the acceleration techniques.en_US
dc.format.extent1237,en_US
dc.format.extent1247en_US
dc.publisherIEEEen_US
dc.relation.haspart7470428.pdfen_US
dc.titleMIP Reformulation for Max-Min Problems in Two-Stage Robust SCUCen_US
dc.typeArticleen_US
dc.journal.volume32en_US
dc.journal.issue2en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7470428.pdf581.2 kBAdobe PDF
Full metadata record
DC FieldValueLanguage
dc.contributor.authorHongxing Yeen_US
dc.contributor.authorJianhui Wangen_US
dc.contributor.authorZuyi Lien_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:20:21Z-
dc.date.available2020-04-06T07:20:21Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/TPWRS.2016.2569609en_US
dc.identifier.urihttp://localhost/handle/Hannan/160236-
dc.description.abstractWith increasing renewable penetration in power systems, considerable research efforts have been focused on how to accommodate the uncertainties from renewables in the Security-Constraint Unit Commitment (SCUC) problem. One of the candidate approaches to handling uncertainties is the two-stage Robust SCUC (RSCUC), which enables system to survive in any scenario. The survivability is guaranteed by the solution optimality of the max-min problem in the second stage. However, as the non-convex max-min problem is NP-hard, it is difficult to get the exact optimal solution in acceptable time. In this paper, we propose a new efficient formulation which recasts the max-min problem to a Mixed Integer Programming (MIP) problem using Binary Expansion (BE). The upper bound of the gap between the new MIP problem and the original max-min problem is derived. The gap, which quantifies the solution optimality of the max-min problem, is controllable. Two effective acceleration techniques are proposed to improve the performance of the MIP problem by eliminating inactive flow constraints and decomposing time-coupled uncertainty budget constraints. Accordingly, the computation burden of solving the max-min problem is reduced tremendously. The simulation results for the IEEE 118-Bus system validate and demonstrate the effectiveness of the new BE-based solution approach to the two-stage RSCUC and the acceleration techniques.en_US
dc.format.extent1237,en_US
dc.format.extent1247en_US
dc.publisherIEEEen_US
dc.relation.haspart7470428.pdfen_US
dc.titleMIP Reformulation for Max-Min Problems in Two-Stage Robust SCUCen_US
dc.typeArticleen_US
dc.journal.volume32en_US
dc.journal.issue2en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7470428.pdf581.2 kBAdobe PDF