A novel optimization approach for sub-hourly unit commitment with large
numbers of units and virtual transactions
Abstract
Unit Commitment (UC) is an important problem in power system operations.
It is traditionally scoped for 24 hours with one-hour time intervals. To
improve system flexibility by accommodating the increasing net-load
variability, sub-hourly UC has been suggested. Such a problem is larger
and more complicated than hourly UC because of the increased number of
periods and reduced unit ramping capabilities per period. The
computational burden is further exacerbated for systems with large
numbers of virtual transactions leading to dense transmission
constraints matrices. Consequently, the state-of-the-art and practice
method, branch-and-cut (B&C), suffers from poor performance. In this
paper, our recent Surrogate Absolute-Value Lagrangian Relaxation (SAVLR)
is enhanced by embedding ordinal-optimization concepts for a drastic
reduction in subproblem solving time. Rather than formally solving
subproblems by using B&C, subproblem solutions that satisfy SAVLR’s
convergence condition are obtained by modifying solutions from previous
iterations or solving crude subproblems. All virtual transactions are
included in each subproblem to reduce major changes in solutions across
iterations. A parallel version is also developed to further reduce the
computation time. Testing on MISO’s large cases demonstrates that our
ordinal-optimization embedded approach obtains near-optimal solutions
efficiently, is robust, and provides a new way on solving other MILP
problems.