Generation maintenance scheduling via robust optimization

Morteza Shabanzadeh, Mohammad Fattahi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

It is essential to develop versatile decision-making tools for GENCOs by which the most efficient maintenance schedules in highly competitive electricity markets are devised. The key of preventive Generation Maintenance Scheduling (GMS), or Outage Planning, is to determine the optimal time period for which generating units of a GENCO should be taken off-line over the course of a one-year planning horizon. In practice, GMS is mathematically modeled as an optimization problem with a multitude of variables and uncertain parameters which need to be determined for optimal commercial decisions. This context explores a robust optimization-based procedure to evaluate the impact of price uncertainty on GENCOs' profits and their desired maintenance schedules. In contrast with the probabilistic and stochastic methods, the proposed approach is more practical because it only requires an uncertainty interval, rather than a probability distribution of the uncertain data. To demonstrate the tremendous performance of the proposed approach, a GENCO with three generation units is investigated.
Original languageEnglish
Title of host publicationProceedings of the 23rd Iranian Conference on Electrical Engineering
Place of PublicationPiscataway
PublisherIEEE
Pages1504-1509
Number of pages6
Volume2
ISBN (Electronic)9781479919727, 9781479919710
ISBN (Print)9781479919734
DOIs
Publication statusPublished - May 2015
Externally publishedYes
Event2015 23rd Iranian Conference on Electrical Engineering (ICEE 2015) - Sharif University of Technology, Tehran, Iran, Islamic Republic of
Duration: 10 May 201514 May 2015
http://icee2015.conf.sharif.ir/

Conference

Conference2015 23rd Iranian Conference on Electrical Engineering (ICEE 2015)
CountryIran, Islamic Republic of
CityTehran
Period10/05/1514/05/15
Internet address

Fingerprint

Dive into the research topics of 'Generation maintenance scheduling via robust optimization'. Together they form a unique fingerprint.

Cite this