An Efficient Robust Solution to the Two-Stage Stochastic Unit Commitment Problem

Ignacio Blanco, Juan Miguel Morales González

Research output: Contribution to journalJournal articleResearchpeer-review

261 Downloads (Pure)

Abstract

This paper proposes a reformulation of the scenario-based two-stage unitcommitment problem under uncertainty that allows finding unit-commitment plansthat perform reasonably well both in expectation and for the worst caserealization of the uncertainties. The proposed reformulation is based onpartitioning the sample space of the uncertain factors by clustering thescenarios that approximate their probability distributions. It is, furthermore,very amenable to decomposition and parallelization using acolumn-and-constraint generation procedure.
Original languageEnglish
JournalIEEE Transactions on Power Systems
Volume32
Issue number6
Pages (from-to)4477-4488
Number of pages11
ISSN0885-8950
DOIs
Publication statusPublished - 2017

Bibliographical note

(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.

Keywords

  • Stochastic and robust unit commitment
  • Columnand- constraint generation
  • Parallel computing
  • Clustering
  • Scenario reduction

Cite this

Blanco, Ignacio ; Morales González, Juan Miguel. / An Efficient Robust Solution to the Two-Stage Stochastic Unit Commitment Problem. In: IEEE Transactions on Power Systems. 2017 ; Vol. 32, No. 6. pp. 4477-4488.
@article{a3fe70876bcd456bab421606eaec9484,
title = "An Efficient Robust Solution to the Two-Stage Stochastic Unit Commitment Problem",
abstract = "This paper proposes a reformulation of the scenario-based two-stage unitcommitment problem under uncertainty that allows finding unit-commitment plansthat perform reasonably well both in expectation and for the worst caserealization of the uncertainties. The proposed reformulation is based onpartitioning the sample space of the uncertain factors by clustering thescenarios that approximate their probability distributions. It is, furthermore,very amenable to decomposition and parallelization using acolumn-and-constraint generation procedure.",
keywords = "Stochastic and robust unit commitment, Columnand- constraint generation, Parallel computing, Clustering, Scenario reduction",
author = "Ignacio Blanco and {Morales Gonz{\'a}lez}, {Juan Miguel}",
note = "(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.",
year = "2017",
doi = "10.1109/TPWRS.2017.2683263",
language = "English",
volume = "32",
pages = "4477--4488",
journal = "I E E E Transactions on Power Systems",
issn = "0885-8950",
publisher = "Institute of Electrical and Electronics Engineers",
number = "6",

}

An Efficient Robust Solution to the Two-Stage Stochastic Unit Commitment Problem. / Blanco, Ignacio; Morales González, Juan Miguel.

In: IEEE Transactions on Power Systems, Vol. 32, No. 6, 2017, p. 4477-4488.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - An Efficient Robust Solution to the Two-Stage Stochastic Unit Commitment Problem

AU - Blanco, Ignacio

AU - Morales González, Juan Miguel

N1 - (c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.

PY - 2017

Y1 - 2017

N2 - This paper proposes a reformulation of the scenario-based two-stage unitcommitment problem under uncertainty that allows finding unit-commitment plansthat perform reasonably well both in expectation and for the worst caserealization of the uncertainties. The proposed reformulation is based onpartitioning the sample space of the uncertain factors by clustering thescenarios that approximate their probability distributions. It is, furthermore,very amenable to decomposition and parallelization using acolumn-and-constraint generation procedure.

AB - This paper proposes a reformulation of the scenario-based two-stage unitcommitment problem under uncertainty that allows finding unit-commitment plansthat perform reasonably well both in expectation and for the worst caserealization of the uncertainties. The proposed reformulation is based onpartitioning the sample space of the uncertain factors by clustering thescenarios that approximate their probability distributions. It is, furthermore,very amenable to decomposition and parallelization using acolumn-and-constraint generation procedure.

KW - Stochastic and robust unit commitment

KW - Columnand- constraint generation

KW - Parallel computing

KW - Clustering

KW - Scenario reduction

U2 - 10.1109/TPWRS.2017.2683263

DO - 10.1109/TPWRS.2017.2683263

M3 - Journal article

VL - 32

SP - 4477

EP - 4488

JO - I E E E Transactions on Power Systems

JF - I E E E Transactions on Power Systems

SN - 0885-8950

IS - 6

ER -