Ordinal optimization theory to solve large‐scale power system unit commitment

The complexity of the multiperiod dynamic unit commitment problem makes it difficult or even unviable to find the global optimal solution. Ordinal optimization provides a simulation‐based approach suitable for solving this kind of problem. It uses crude models and rough estimates to derive a small s...

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Bibliographic Details
Published in:IEEJ transactions on electrical and electronic engineering Vol. 13; no. 2; pp. 187 - 194
Main Authors: Xie, Min, Zhu, Yanhan, Ke, Shaojia, Du, Yuxin, Liu, Mingbo
Format: Journal Article
Language:English
Published: Hoboken, USA John Wiley & Sons, Inc 01.02.2018
Wiley Subscription Services, Inc
Subjects:
Computer simulation
good enough solution
large‐scale dynamic unit commitment
Optimization
ordinal optimization
Unit commitment
ISSN:1931-4973, 1931-4981
Online Access:Get full text
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Summary:The complexity of the multiperiod dynamic unit commitment problem makes it difficult or even unviable to find the global optimal solution. Ordinal optimization provides a simulation‐based approach suitable for solving this kind of problem. It uses crude models and rough estimates to derive a small set of unit commitment schemes for which simulations are necessary and worthwhile to find good enough solutions with drastically reduced computational burden. The 10–100 thermal units standard test example and the case of an actual provincial power system with 128 units verify the feasibility of ordinal optimization to solve the large‐scale dynamic unit commitment problem. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
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ISSN:1931-4973
1931-4981
DOI:10.1002/tee.22513