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Rank-constrained semidefinite program for unit commitment
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AI
DOI：10.1016/j.ijepes.2012.10.056.png)
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Abstract
En 中文
Unit Commitment (UC) is a combinatorial optimization problem that can be posed as minimizing a quadratic objective function under quadratic constraints. This paper presents a solution to UC based on Semidefinite Programming (SDP). In particular, it shows that an approximate solution can be obtained by using Shor's semidefinite relaxation scheme together with a rank constraint enforced via convex iteration. The approximate solution has the majority of Boolean variables set by the SDP solver to either 0 or 1; it is modified by a simple heuristic to yield a feasible schedule. The proposed SDP formulation employs 3 x 3 semidefinite matrices and therefore requires computational effort that increases only moderately with problem size. Numerical results on test systems with up to 100 units dispatched over a period of 24 h show that the method is robust and produces schedules that are comparable with those from previous techniques. (C) 2012 Elsevier Ltd. All rights reserved.
Keywords:
Integer programming
Optimization methods
Power generation dispatch
Power system economics
Semidefinite programming
Unit commitment
Journal
I
IF:
5
Papers:
1.1W
Citations:
3.1W
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