Parallel augment Lagrangian relaxation method for transient stability constrained unit commitment

This paper presents a transient stability constrained unit commitment (TSCUC) model which achieves the objective of maintaining both transient stability and economical operation. In the TSCUC model, transient stability constraints are incorporated into the framework of unit commitment. In order to s...

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Bibliographic Details
Published in:IEEE transactions on power systems Vol. 28; no. 2; pp. 1140 - 1148
Main Authors: Jiang, Quanyuan, Zhou, Boran, Zhang, Mingze
Format: Journal Article
Language:English
Published: New York IEEE 01.05.2013
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Augmented Lagrangian relaxation
Conferences
Constraints
Dynamic programming
Economics
Hybrid power systems
hybrid sub-gradient
Load flow
Operations research
Optimization
parallel computing
Parallel processing
Power system stability
reduced-space interior point method
Reproduction
Stability criteria
Transient analysis
Transient stability
transient stability constrained optimal power flow
transient stability constrained unit commitment
Unit commitment
ISSN:0885-8950, 1558-0679
Online Access:Get full text
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Summary:This paper presents a transient stability constrained unit commitment (TSCUC) model which achieves the objective of maintaining both transient stability and economical operation. In the TSCUC model, transient stability constraints are incorporated into the framework of unit commitment. In order to solve TSCUC problem, augmented Lagrangian relaxation (ALR) combined with variable duplication techniques and the auxiliary problem principle (APP) is used to decompose the TSCUC problem into two sub-problems: one sub-problem is a traditional unit commitment (UC) problem with prevailing constraints; another sub-problem is modeled as a transient stability constrained optimal power flow (TSCOPF) problem. The first sub-problem is solved by dynamic programming, while the second sub-problem is solved using a reduced-space interior point method. In ALR, an efficient hybrid sub-gradient method is developed to update all Lagrangian multipliers. The iterative process continues until the duality gap is sufficiently small. Finally, case studies show that the proposed methodology is very efficient for solving TSCUC problems within a parallel computing framework.
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ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2012.2216553