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Title: Strengthened MILP formulation for certain gas turbine unit commitment problems

In this study, we derive a strengthened MILP formulation for certain gas turbine unit commitment problems, in which the ramping rates are no smaller than the minimum generation amounts. This type of gas turbines can usually start-up faster and have a larger ramping rate, as compared to the traditional coal-fired power plants. Recently, the number of this type of gas turbines increases significantly due to affordable gas prices and their scheduling flexibilities to accommodate intermittent renewable energy generation. In this study, several new families of strong valid inequalities are developed to help reduce the computational time to solve these types of problems. Meanwhile, the validity and facet-defining proofs are provided for certain inequalities. Finally, numerical experiments on a modified IEEE 118-bus system and the power system data based on recent studies verify the effectiveness of applying our formulation to model and solve this type of gas turbine unit commitment problems, including reducing the computational time to obtain an optimal solution or obtaining a much smaller optimality gap, as compared to the default CPLEX, when the time limit is reached with no optimal solutions obtained.
 [1] ;  [1] ;  [2] ;  [3]
  1. Univ. of Florida, Gainesville, FL (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  3. Argonne National Lab. (ANL), Lemont, IL (United States)
Publication Date:
Report Number(s):
Journal ID: ISSN 0885-8950; 583635
Grant/Contract Number:
Accepted Manuscript
Journal Name:
IEEE Transactions on Power Systems
Additional Journal Information:
Journal Volume: 5; Journal Issue: 1; Journal ID: ISSN 0885-8950
Research Org:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org:
USDOE National Nuclear Security Administration (NNSA)
Country of Publication:
United States
24 POWER TRANSMISSION AND DISTRIBUTION; gas turbines; unit commitment; mixed-integer linear programming
OSTI Identifier: