A novel matching formulation for startup costs in unit commitment

Knueven, Bernard; Ostrowski, James; Watson, Jean-Paul

doi:10.1007/s12532-020-00176-5

A novel matching formulation for startup costs in unit commitment

Journal Article · Mon Feb 24 00:00:00 EST 2020 · Mathematical Programming Computation

DOI:https://doi.org/10.1007/s12532-020-00176-5· OSTI ID:1607497

Knueven, Bernard ^[1]; Ostrowski, James ^[2]; Watson, Jean-Paul ^[3]

Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Univ. of Tennessee, Knoxville, TN (United States)
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

Here we present a novel formulation for startup cost computation in the unit commitment problem (UC). Both our proposed formulation and existing formulations in the literature are placed in a formal, theoretical dominance hierarchy based on their respective linear programming relaxations. Our proposed formulation is tested empirically against existing formulations on large-scale UC instances drawn from real-world data. While requiring more variables than the current state-of-the-art formulation, our proposed formulation requires fewer constraints, and is empirically demonstrated to be as tight as a perfect formulation for startup costs. This tightening can reduce the computational burden in comparison to existing formulations, especially for UC instances with large reserve margins and high penetration levels of renewables.

View Accepted Manuscript (DOE)

Research Organization:: Sandia National Laboratories (SNL-CA), Livermore, CA (United States); Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); University of Tennessee, Knoxville, TN (United States)

Sponsoring Organization:: National Science Foundation (NSF); USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)

Grant/Contract Number:: AC04-94AL85000; NA0003525; SC0018175

OSTI ID:: 1607497

Alternate ID(s):: OSTI ID: 2339868

Report Number(s):: SAND--2020-0327J; 681741

Journal Information:: Mathematical Programming Computation, Journal Name: Mathematical Programming Computation Journal Issue: 2 Vol. 12; ISSN 1867-2949

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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