• DocumentCode
    2192418
  • Title

    A practical mixed integer linear programming based approach for unit commitment

  • Author

    Chang, G.W. ; Tsai, Y.D. ; Lai, C.Y. ; Chung, J.S.

  • Author_Institution
    Dept. of Electr. Eng., Nat. Chung Cheng Univ., Chia-Yi, Taiwan
  • fYear
    2004
  • fDate
    6-10 June 2004
  • Firstpage
    221
  • Abstract
    This paper presents a practical mixed integer linear programming (MILP) based approach for unit commitment (UC), which is suitable for both traditional and deregulated environments. In general, the UC problem is complicated large-scale, combinatorial, and non-convex in nature, it is very difficult to solve by conventional approaches to achieve both solution accuracy and efficiency. With the recent development of solution techniques, there is a trend to tackle the UC problem by using MILP approaches. In this paper the authors propose a detailed procedure to formulate the UC problem in MILP manners. The problems are then solved via a state-of-the-art optimization package. The usefulness of the proposed solution technique is illustrated by testing the problem with actual system data. The solution obtained not only gives the unit on/off states and MW schedules, but also provides marginal price information associated with system constraints such as load demand requirement to assist strategic bidding in the power market.
  • Keywords
    integer programming; linear programming; power generation dispatch; power generation economics; power generation scheduling; power markets; pricing; thermal power stations; load demand requirement; marginal price information; mixed integer linear programming; power market; state-of-the-art optimization package; strategic bidding; unit commitment; Cost function; Fuels; Helium; Integer linear programming; Large-scale systems; Mixed integer linear programming; Packaging; Power generation economics; Power markets; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society General Meeting, 2004. IEEE
  • Print_ISBN
    0-7803-8465-2
  • Type

    conf

  • DOI
    10.1109/PES.2004.1372789
  • Filename
    1372789