• DocumentCode
    1178548
  • Title

    Experiences with Mixed Integer Linear Programming-Based Approaches in Short-Term Hydro Scheduling

  • Author

    Chang, Gee-Kung ; Aganagic, M. ; Waight, J. ; Medina, Jesus ; Burton, Ted ; Reeves, S. ; Christoforidis, M.

  • Author_Institution
    National Chung Cheng University, Taiwan; Oracle Utility Verticle; Siemens Power Systems Control; ECNZ Southern Generation Group; Power Plant Department, Swiss Rail (SBB)
  • Volume
    21
  • Issue
    9
  • fYear
    2001
  • Firstpage
    63
  • Lastpage
    63
  • Abstract
    This paper describes experiences with mixed integer linear programming (MILP)-based approaches on the short-term hydro scheduling (STHS) function. The STHS is used to determine the optimal or near-optimal schedules for the dispatchable hydro units in a hydro-dominant system for a user-definable study period at each time step while respecting all system and hydraulic constraints. The problem can be modeled in detail for a hydro system that contains both conventional and pumped-storage units. Discrete and dynamic constraints such as unit startup/shutdown and minimum-up/minimum-down time limits are also included in the model for hydro unit commitment (HUC). The STHS problem is solved with a state-ofthe-art package that includes an algebraic modeling language and an MILP solver. The usefulness of the proposed solution algorithm is illustrated by testing the problem with actual hydraulic system data. Numerical experiences show that the solution technique is computationally efficient, simple, and suitable for decision support of short-term hydro operations planning. In addition, the proposed approaches can be easily extended for scheduling applications in deregulated environments.
  • Keywords
    Convergence; Environmental economics; Fuel economy; Intelligent sensors; Mixed integer linear programming; Power generation; Power generation economics; Power system control; Processor scheduling; Search methods; Algebraic modeling language; hydro unit commitment; interior point method; mixed integer linear programming; short-term hydro scheduling;
  • fLanguage
    English
  • Journal_Title
    Power Engineering Review, IEEE
  • Publisher
    ieee
  • ISSN
    0272-1724
  • Type

    jour

  • DOI
    10.1109/MPER.2001.4311628
  • Filename
    4311628