English

Multiple-Periods Locally-Facet-Based MIP Formulations for the Unit Commitment Problem

Optimization and Control 2022-09-26 v3

Abstract

The thermal unit commitment (UC) problem has historically been formulated as a mixed integer quadratic programming (MIQP), which is difficult to solve efficiently, especially for large-scale systems. The tighter characteristic reduces the search space, therefore, as a natural consequence, significantly reduces the computational burden. In literatures, many tightened formulations for a single unit with parts of constraints were reported without presenting explicitly how they were derived. In this paper, a systematic approach is developed to formulate tight formulations. The idea is to use more binary variables to represent the state of the unit so as to obtain the tightest upper bound of power generation limits and ramping constraints for a single unit. In this way, we propose a multi-period formulation based on sliding windows which may have different sizes for each unit in the system. Furthermore, a multi-period model taking historical status into consideration is obtained. Besides, sufficient and necessary conditions for the facets of single-unit constraints polytope are provided and redundant inequalities are eliminated. The proposed models and three other state-of-the-art models are tested on 73 instances with a scheduling time of 24 hours. The number of generators in the test systems ranges from 10 to 1080. The simulation results show that our proposed multi-period formulations are tighter than the other three state-of-the-art models when the window size of the multi-period formulation is greater than 2.

Keywords

Cite

@article{arxiv.2112.08648,
  title  = {Multiple-Periods Locally-Facet-Based MIP Formulations for the Unit Commitment Problem},
  author = {Linfeng Yang and Shifei Chen and Zhaoyang Dong},
  journal= {arXiv preprint arXiv:2112.08648},
  year   = {2022}
}

Comments

76 pages, 18 figures, 10 tables. This work has been published in IEEE Transactions on Power Systems

R2 v1 2026-06-24T08:19:47.730Z