On Mixed-Integer Programming Formulations for the Unit Commitment Problem

Author:

Knueven Bernard1ORCID,Ostrowski James2,Watson Jean-Paul3

Affiliation:

1. Discrete Math & Optimization, Sandia National Laboratories, Albuquerque, New Mexico 87185;

2. Industrial and Systems Engineering, University of Tennessee, Knoxville, Tennessee 37996;

3. Data Science & Cyber Analytics, Sandia National Laboratories, Livermore, California 94551

Abstract

We provide a comprehensive overview of mixed-integer programming formulations for the unit commitment (UC) problem. UC formulations have been an especially active area of research over the past 12 years due to their practical importance in power grid operations, and this paper serves as a capstone for this line of work. We additionally provide publicly available reference implementations of all formulations examined. We computationally test existing and novel UC formulations on a suite of instances drawn from both academic and real-world data sources. Driven by our computational experience from this and previous work, we contribute some additional formulations for both generator production upper bounds and piecewise linear production costs. By composing new UC formulations using existing components found in the literature and new components introduced in this paper, we demonstrate that performance can be significantly improved—and in the process, we identify a new state-of-the-art UC formulation.

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

Subject

General Engineering

Cited by 68 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Managing power balance and reserve feasibility in the AC unit commitment problem;Electric Power Systems Research;2024-09

2. Near-optimal solutions for day-ahead unit commitment;Electric Power Systems Research;2024-09

3. Analyzing the computational performance of balance constraints in the medium-term unit commitment problem: Tightness, compactness, and arduousness;International Journal of Electrical Power & Energy Systems;2024-09

4. Harnessing Inferior Solutions For Superior Outcomes: Obtaining Robust Solutions From Quantum Algorithms;Proceedings of the Genetic and Evolutionary Computation Conference Companion;2024-07-14

5. Electricity Grid Capacity Expansion Planning Considering Interconnection Queue Uncertainty;2024 18th International Conference on Probabilistic Methods Applied to Power Systems (PMAPS);2024-06-24

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3