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A convex quadratic programming model for unit commitment global optimization
Author(s) -
Hou Wenting,
Wei Hua,
Tan Jiancheng,
Lin Chunmei
Publication year - 2018
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.22583
Subject(s) - mathematical optimization , quadratic programming , linear programming , global optimization , convex optimization , set (abstract data type) , quadratic equation , regular polygon , computer science , mathematics , geometry , programming language
This paper presents a convex quadratic programming (CQP) model of the thermal unit commitment (UC) problem based on the recent advancement in mathematics. The proposed model employs convex transformation techniques and is able to achieve the global optimal solution. In the CQP model, the startup cost is represented by using two kinds of binary variables (0–1); the nonconvex constraints, namely the minimum up and down times, are expressed as equivalent linear constraints via a set of linear inequalities; then the nonconvex UC problem is transformed into a convex problem with a quadratic objective function and linear constraints. Comparison studies are carried out based on the results obtained from 20 algorithms applied to 10–60 unit 24‐h systems. The appendices give the details of these results. The CQP model shows unbeatable performance on global optimal searching and arrives at the overall global optimization solution constantly, and so, for the first time, is able to get the globally optimal solution of the UC problem. The proposed CQP formulation serves as a reliable standard reference for various optimization algorithms. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.