An Evaluation of Advanced Tools for Distributed Wind Turbine Performance Estimation

Research output: Contribution to journalArticlepeer-review

3 Scopus Citations

Abstract

We evaluate various classes of distributed wind turbine performance tools across two sites in the United States. The class of tools ranges from the simple mass conservation model to the coupled Reynolds-averaged Navier-Stokes model, all initiated by the WIND Toolkit data set. The resource estimation at the site is evaluated against measured data at the mast location. Taking a sample 100-kW wind turbine and constant losses, we evaluate Openwind, Continuum, and WindNinja tools and document annual energy production (AEP) and time-series statistics associated with the performance estimation of the wind turbine. Using a methodology that is consistent and unbiased across the three options currently available in the industry, we elaborate results at the two sample locations and discuss the probable sources of discrepancy in the AEP estimates. Two main sources of the discrepancy come from the input WIND Toolkit data and the spatial modeling techniques of the tools to capture atmospheric physics. The discussion includes additional values that these tools may bring into the energy assessment process to enhance the owners' confidence over the distributed wind power systems.

Original languageAmerican English
Article numberArticle No. 012017
Number of pages10
JournalJournal of Physics: Conference Series
Volume1452
Issue number1
DOIs
StatePublished - 3 Mar 2020
EventNorth American Wind Energy Academy, NAWEA 2019 and the International Conference on Future Technologies in Wind Energy 2019, WindTech 2019 - Amherst, United States
Duration: 14 Oct 201916 Oct 2019

Bibliographical note

See NREL/CP-5000-74610 for preprint

NREL Publication Number

  • NREL/JA-5000-77179

Keywords

  • AEP
  • distributed wind power
  • energy assessment
  • wind turbine performance

Fingerprint

Dive into the research topics of 'An Evaluation of Advanced Tools for Distributed Wind Turbine Performance Estimation'. Together they form a unique fingerprint.

Cite this