Solving Unit Commitment problems with general ramp constraints

Lagrangian Relaxation (LR) algorithms are among the most successful approaches for solving large-scale hydro-thermal Unit Commitment (UC) problems; this is largely due to the fact that the Single-Unit Commitment (1UC) problems resulting from the decomposition, incorporating many kinds of technical constraints such as minimum up- and down-time requirements and time-dependent startup costs, can be efficiently solved by Dynamic Programming (DP) techniques. Ramp constraints have historically eluded efficient exact DP approaches; however, this has recently changed \cite{FrGe05}. We show that the newly proposed DP algorithm for ramp-constrained (1UC) problems allows to extend existing LR approaches to ramp-constrained (UC); this is not obvious since the heuristic procedures typically used to recover a primal feasible solution are not easily extended to take ramp limits into account. However, dealing with ramp constraints in the subproblems turns out to be sufficient to provide the LR heuristic enough guidance to produce good feasible solutions even with no other modification of the approach; this is due to the fact that (sophisticated) LR algorithms to (UC) duly exploit the primal information computed by the Lagrangian Dual, which in the proposed approach is ramp feasible. We also show by computational experiments that the LR is competitive with those based on general-purpose Mixed-Integer Program (MIP) solvers for large-scale instances, especially hydro-thermal ones.