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
Quantitative performance evaluation of a wind turbine generator cluster using statistical techniques
School of Mechanical and Building Sciences, VIT University, Vellore, India.
School of Mechanical and Building Sciences, VIT University, Vellore, India.ORCID iD: 0000-0002-6245-7693
Suzlon Energy Limited, One Earth, Pune, India.
2014 (English)In: Energy Procedia, ISSN 1876-6102, Vol. 54, p. 211-220Article in journal (Refereed) Published
Abstract [en]

This report dissects the analysis of annual performance of a cluster of wind turbine generators operated by Suzlon Energy Limited to troubleshoot shortfalls in the predicted generation of individual machines for the fiscal year of 2011-12. The first phase involved an estimation of the annual energy production using wind resource assessment on the commercial software Wind Atlas, Analysis and Application Program (WAsP). Comparison of the Annual Energy Production (AEP) with direct extrapolation of monthly generation to centum machine and grid availability highlighted negative inconsistency between the two in the case of five machines. Detailed study of their data histories indicated the reason to be coarse extrapolation and generation curtailment, although the latter is a minor contributor. The second phase consists of quantification of these losses for the concerned machines using statistical extrapolation and a variety of data approaches. A qualitative comparison of the methods is presented based on accuracy and utility. It is concluded that correlation of average hub-height wind velocities with the concerned machine's generation yields the most reliable and professionally useful results. Also, the advantages and shortcomings of the other methods have been discussed. 

Place, publisher, year, edition, pages
Elsevier, 2014. Vol. 54, p. 211-220
Keywords [en]
Curve fitting, Data analysis, Generation loss quantification, Machine/grid availability, Wind power
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:hj:diva-45672DOI: 10.1016/j.egypro.2014.07.264ISI: 000346092000021Scopus ID: 2-s2.0-84906959621OAI: oai:DiVA.org:hj-45672DiVA, id: diva2:1345148
Conference
4th International Conference on Advances in Energy Research, ICAER 2013, 10 December 2013 through 12 December 2013, Mumbai
Available from: 2019-08-23 Created: 2019-08-23 Last updated: 2023-08-28Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Sainis, Salil

Search in DiVA

By author/editor
Sainis, Salil
In the same journal
Energy Procedia
Energy Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 66 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