Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Hydropower Bidding Strategies to Day-Ahead and Real-Time Markets: Different Approaches
KTH, School of Electrical Engineering (EES), Electric Power Systems.
KTH, School of Electrical Engineering (EES), Electric Power Systems.ORCID iD: 0000-0002-8189-2420
KTH, School of Electrical Engineering (EES), Electric Power Systems.ORCID iD: 0000-0001-6000-9363
2013 (English)In: 24th International Workshop on Database and Expert Systems Applications: DEXA 2013 : proceedings, 26-29 August 2013, Prague, Czech Republic, IEEE Computer Society, 2013, 209-213 p.Conference paper, Published paper (Refereed)
Abstract [en]

The ongoing growth in wind power introduce huge amount of uncertainties to the power market. The stochastic nature of these power sources increases the need for the reserve power in real-time market. Having a flexible power source, hydropower producer can provide reserve power and increase its profit. Therefore, to build a planning model, which will allocate available capacity in different market places is an essential task for the price-taker hydropower producer. This paper uses optimal bidding model to the day-ahead market considering real-time balancing market under the uncertainties of the day-ahead and real-time market prices. Specifically, the model is built using stochastic linear programming approach. According to the results, for simultaneous bidding to day-ahead and real-time markets two extreme cases are happening. To make the bidding strategies more realistic and robust different novel approaches are modeled and assessed. Discussions on the results are provided and summarized.

Place, publisher, year, edition, pages
IEEE Computer Society, 2013. 209-213 p.
Series
Proceedings - International Workshop on Database and Expert Systems Applications, DEXA, ISSN 1529-4188
Keyword [en]
Stochastic programming, optimal bidding, dayahead market, regulating market, scenario generation
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-139316DOI: 10.1109/DEXA.2013.45ISI: 000335791800038Scopus ID: 2-s2.0-84887913296ISBN: 978-0-7695-5070-1 (print)OAI: oai:DiVA.org:kth-139316DiVA: diva2:684923
Conference
24th International Workshop on Database and Expert Systems Applications, DEXA 2013; Prague; Czech Republic; 26 August 2013 through 29 August 2013
Funder
StandUp
Note

QC 20140110

Available from: 2014-01-08 Created: 2014-01-08 Last updated: 2014-06-09Bibliographically approved

Open Access in DiVA

fulltext(214 kB)220 downloads
File information
File name FULLTEXT01.pdfFile size 214 kBChecksum SHA-512
4343523e77c6a39690572658316caf7f9dea976ebc66aa3056ec95f56222a3da1c1a4c6a398b8facf68d43ee0d38e051a3b6175a4076ca9817c6448827f338a1
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopusIEEEXplore

Search in DiVA

By author/editor
Vardanyan, YelenaSöder, LennartAmelin, Mikael
By organisation
Electric Power Systems
Other Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 220 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 185 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf