Two-stage stochastic day-ahead optimal resource scheduling in a distribution network with intensive use of distributed energy resources

Tiago Sousa, Mohammad Ali Fotouhi Ghazvini, Hugo Morais, Rui Castro, Zita Vale

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

The integration of renewable sources and electric vehicles will introduce new uncertainties to the optimal resource scheduling, namely at the distribution level. These uncertainties are mainly originated by the power generated by renewables sources and by the electric vehicles charge requirements. This paper proposes a two-state stochastic programming approach to solve the day-ahead optimal resource scheduling problem. The case study considers a 33-bus distribution network with 66 distributed generation units and 1000 electric vehicles.
Original languageEnglish
Title of host publicationProceedings of 2015 IEEE PES Innovative Smart Grid Technologies Latin America
PublisherIEEE
Publication date2015
Pages689-694
ISBN (Print)978-1-4673-6605-2
DOIs
Publication statusPublished - 2015
Event2015 IEEE PES Conference on Innovative Smart Grid Technologies (2015 ISGT-LA) Latin American - Montevideo, Uruguay
Duration: 5 Oct 20157 Oct 2015

Conference

Conference2015 IEEE PES Conference on Innovative Smart Grid Technologies (2015 ISGT-LA) Latin American
CountryUruguay
CityMontevideo
Period05/10/201507/10/2015

Keywords

  • Energy Engineering and Power Technology
  • Electric vehicles
  • Optimal Resource Scheduling
  • Renewable Sources
  • Stochastic Programming
  • Vehicle-to-grid
  • Energy resources
  • Scheduling
  • Smart power grids
  • Stochastic programming
  • Stochastic systems
  • Vehicles
  • Distributed Energy Resources
  • Distributed generation units
  • Distribution levels
  • Renewable sources
  • Renewables
  • Resource-scheduling
  • Two-state
  • Vehicle to grids
  • Electric power transmission networks

Fingerprint Dive into the research topics of 'Two-stage stochastic day-ahead optimal resource scheduling in a distribution network with intensive use of distributed energy resources'. Together they form a unique fingerprint.

Cite this