Content area

Abstract

Unit maintenance and unit commitment are two critical and interrelated aspects of electric power system operation, both of which face the challenge of coordinating efforts to enhance reliability and economic performance. This challenge becomes increasingly pronounced in the context of increased integration of renewable energy and flexible loads, such as wind power and electric vehicles, into the power system, where high uncertainty is prevalent. To tackle this issue, this paper develops a two-stage adaptive robust optimization model for the joint unit maintenance and unit commitment strategy. The first stage focuses on making joint decisions regarding unit maintenance and unit commitment, while the second stage addresses economic dispatch under the worst-case scenarios of wind power and load demand. Then a practical solution methodology is proposed to solve this model efficiently, which combines the inexact column-and-constraint generation algorithm with an outer approximation method. Finally, the economic viability and adaptability of the proposed method is demonstrated based on the RTS-79 test system.

Details

1009240
Identifier / keyword
Title
Two-Stage Adaptive Robust Optimization Model for Joint Unit Maintenance and Unit Commitment Considering Source-Load Uncertainty
Publication title
arXiv.org; Ithaca
Publication year
2024
Publication date
Dec 1, 2024
Section
Computer Science; Electrical Engineering and Systems Science
Publisher
Cornell University Library, arXiv.org
Source
arXiv.org
Place of publication
Ithaca
Country of publication
United States
University/institution
Cornell University Library arXiv.org
e-ISSN
2331-8422
Source type
Working Paper
Language of publication
English
Document type
Working Paper
Publication history
 
 
Online publication date
2024-12-03
Milestone dates
2024-12-01 (Submission v1)
Publication history
 
 
   First posting date
03 Dec 2024
ProQuest document ID
3139001942
Document URL
https://www.proquest.com/working-papers/two-stage-adaptive-robust-optimization-model/docview/3139001942/se-2?accountid=208611
Full text outside of ProQuest
Copyright
© 2024. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2024-12-04
Database
ProQuest One Academic