Assessing Long-Term Wind Conditions by Combining Different Measure-Correlate-Predict Algorithms: Preprint

Jie Zhang

Research output: Contribution to conferencePaper

Abstract

This paper significantly advances the hybrid measure-correlate-predict (MCP) methodology, enabling it to account for variations of both wind speed and direction. The advanced hybrid MCP method uses the recorded data of multiple reference stations to estimate the long-term wind condition at a target wind plant site. The results show that the accuracy of the hybrid MCP method is highly sensitive tothe combination of the individual MCP algorithms and reference stations. It was also found that the best combination of MCP algorithms varies based on the length of the correlation period.
Original languageAmerican English
Number of pages13
StatePublished - 2013
EventASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference - Portland, Oregon
Duration: 4 Aug 20137 Aug 2013

Conference

ConferenceASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
CityPortland, Oregon
Period4/08/137/08/13

NREL Publication Number

  • NREL/CP-5500-57647

Keywords

  • National Renewable Energy Laboratory (NREL)
  • NREL
  • power generation
  • renewable energy (RE)
  • wind distribution
  • wind resource assessment

Fingerprint

Dive into the research topics of 'Assessing Long-Term Wind Conditions by Combining Different Measure-Correlate-Predict Algorithms: Preprint'. Together they form a unique fingerprint.

Cite this