The unit commitment problem is to nd the production scheduling of a set of electric power generating units, and the generation levels for each unit, over a short term, typically from 24 hours to one week. The objective is to find the optimal schedule which meets the energy demand forecast at a minimum cost, and satisfy technological constraints such as the minimum up and down times for the units. First, we assume the demands are known and made a bench mark for the mixed-integer programming formulations for this model. Second, we consider the case with uncertain demands and review stochastic versions of the problem, which allow the schedule to adjust to the observed demands. Then, we tested two different Lagrangian relaxations techniques for solving the stochastic programming problem. Finally, we tested a heuristic method we developed, based on the linear relaxation for some binary variables, which exploits the structure of the stochastic problem.
By: Julio Goez; James Luedtke; Deepak Rajan; Jayant Kalagnanam
Published in: RC24713 in 2008
LIMITED DISTRIBUTION NOTICE:
This Research Report is available. This report has been submitted for publication outside of IBM and will probably be copyrighted if accepted for publication. It has been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be filled only by reprints or legally obtained copies of the article (e.g., payment of royalties). I have read and understand this notice and am a member of the scientific community outside or inside of IBM seeking a single copy only.
Questions about this service can be mailed to reports@us.ibm.com .