Techniques for improving wind to power conversion

Gerry Wiener, Sue Ellen Haupt, Bill Myers, Seth Linden, Julia Pearson, Laura Imbler

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

Abstract

In forecasting wind farm power output, it is important to obtain an accurate farm power output estimate based on given forecast winds. Generally, the manufacturer's turbine power curves are applied to obtain this estimate. In this paper we will discuss the errors that result from using the manufacturer's power curves at actual wind farms. We will discuss alternative approaches that statistically model the power output based on incorporating air density data with actual wind and power observations at wind farms. We will show how these alternative approaches can reduce the overall conversion error and can thus be superior to using the manufacturer's power curves.

Original languageEnglish
Title of host publicationWorld Renewable Energy Forum, WREF 2012, Including World Renewable Energy Congress XII and Colorado Renewable Energy Society (CRES) Annual Conference
Pages1016-1020
Number of pages5
StatePublished - 2012
EventWorld Renewable Energy Forum, WREF 2012, Including World Renewable Energy Congress XII and Colorado Renewable Energy Society (CRES) Annual Conference - Denver, CO, United States
Duration: May 13 2012May 17 2012

Publication series

NameWorld Renewable Energy Forum, WREF 2012, Including World Renewable Energy Congress XII and Colorado Renewable Energy Society (CRES) Annual Conferen
Volume2

Conference

ConferenceWorld Renewable Energy Forum, WREF 2012, Including World Renewable Energy Congress XII and Colorado Renewable Energy Society (CRES) Annual Conference
Country/TerritoryUnited States
CityDenver, CO
Period05/13/1205/17/12

Keywords

  • Data mining
  • Power curve
  • Power forecasting
  • Wind forecasting
  • Wind power
  • Wind turbine

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