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Title: Guide to Using the WIND Toolkit Validation Code

Abstract

In response to the U.S. Department of Energy's goal of using 20% wind energy by 2030, the Wind Integration National Dataset (WIND) Toolkit was created to provide information on wind speed, wind direction, temperature, surface air pressure, and air density on more than 126,000 locations across the United States from 2007 to 2013. The numerical weather prediction model output, gridded at 2-km and at a 5-minute resolution, was further converted to detail the wind power production time series of existing and potential wind facility sites. For users of the dataset it is important that the information presented in the WIND Toolkit is accurate and that errors are known, as then corrective steps can be taken. Therefore, we provide validation code written in R that will be made public to provide users with tools to validate data of their own locations. Validation is based on statistical analyses of wind speed, using error metrics such as bias, root-mean-square error, centered root-mean-square error, mean absolute error, and percent error. Plots of diurnal cycles, annual cycles, wind roses, histograms of wind speed, and quantile-quantile plots are created to visualize how well observational data compares to model data. Ideally, validation will confirm beneficial locations tomore » utilize wind energy and encourage regional wind integration studies using the WIND Toolkit.« less

Authors:
; ;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy Wind Power Technologies Office
OSTI Identifier:
1166659
Report Number(s):
NREL/TP-5000-62595
DOE Contract Number:
AC36-08GO28308
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; WIND INTEGRATION NATIONAL DATASET TOOLKIT; WIND TOOLKIT; NUMERICAL WEATHER PREDICTION MODEL; WIND POWER PRODUCTION; NREL; Wind Energy

Citation Formats

Lieberman-Cribbin, W., Draxl, C., and Clifton, A. Guide to Using the WIND Toolkit Validation Code. United States: N. p., 2014. Web. doi:10.2172/1166659.
Lieberman-Cribbin, W., Draxl, C., & Clifton, A. Guide to Using the WIND Toolkit Validation Code. United States. doi:10.2172/1166659.
Lieberman-Cribbin, W., Draxl, C., and Clifton, A. Mon . "Guide to Using the WIND Toolkit Validation Code". United States. doi:10.2172/1166659. https://www.osti.gov/servlets/purl/1166659.
@article{osti_1166659,
title = {Guide to Using the WIND Toolkit Validation Code},
author = {Lieberman-Cribbin, W. and Draxl, C. and Clifton, A.},
abstractNote = {In response to the U.S. Department of Energy's goal of using 20% wind energy by 2030, the Wind Integration National Dataset (WIND) Toolkit was created to provide information on wind speed, wind direction, temperature, surface air pressure, and air density on more than 126,000 locations across the United States from 2007 to 2013. The numerical weather prediction model output, gridded at 2-km and at a 5-minute resolution, was further converted to detail the wind power production time series of existing and potential wind facility sites. For users of the dataset it is important that the information presented in the WIND Toolkit is accurate and that errors are known, as then corrective steps can be taken. Therefore, we provide validation code written in R that will be made public to provide users with tools to validate data of their own locations. Validation is based on statistical analyses of wind speed, using error metrics such as bias, root-mean-square error, centered root-mean-square error, mean absolute error, and percent error. Plots of diurnal cycles, annual cycles, wind roses, histograms of wind speed, and quantile-quantile plots are created to visualize how well observational data compares to model data. Ideally, validation will confirm beneficial locations to utilize wind energy and encourage regional wind integration studies using the WIND Toolkit.},
doi = {10.2172/1166659},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Dec 01 00:00:00 EST 2014},
month = {Mon Dec 01 00:00:00 EST 2014}
}

Technical Report:

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  • Renewable energy integration studies require wind data sets of high quality with realistic representations of the variability, ramping characteristics, and forecast performance for current wind power plants. The Wind Integration National Data Set (WIND) Toolkit is meant to be an update for and expansion of the original data sets created for the weather years from 2004 through 2006 during the Western Wind and Solar Integration Study and the Eastern Wind Integration Study. The WIND Toolkit expands these data sets to include the entire continental United States, increasing the total number of sites represented, and it includes the weather years frommore » 2007 through 2012. In addition, the WIND Toolkit has a finer resolution for both the temporal and geographic dimensions. Three separate data sets will be created: a meteorological data set, a wind power data set, and a forecast data set. This report describes the validation of the wind power data set.« less
  • The Wind Integration National Dataset (WIND) Toolkit described in this report fulfills these requirements, and constitutes a state-of-the-art national wind resource data set covering the contiguous United States from 2007 to 2013 for use in a variety of next-generation wind integration analyses and wind power planning. The toolkit is a wind resource data set, wind forecast data set, and wind power production and forecast data set derived from the Weather Research and Forecasting (WRF) numerical weather prediction model. WIND Toolkit data are available online for over 116,000 land-based and 10,000 offshore sites representing existing and potential wind facilities.
  • This report describes a method for determining the value of wind energy systems to electric utilities. It is performed by a package of computer models available from SERI that can be used with most utility planning models. The final output of these models gives a financial value ($/kW) of the wind energy system under consideration in the specific utility system. This volume, the second of two volumes, is a user's guide for the computer programs available from SERI. The first volume describes the value determination methodology and gives detailed discussion on each step of the computer modeling.
  • This guide explains how to use MBC3, a MATLAB-based script NREL developed to perform multi-blade coordinate transformation of system matrices for three-bladed wind turbines. In its current form, MBC3 can be applied to system matrices generated by FAST.2.
  • A methodology for analyzing the economic impact of WECS on a utility is described in Volume I of this report. The methodology requires extrapolating both historical utility load data and historical wind power into a year of analysis; calculating the total amount of funds made available in that year, as a result of the inclusion of wind power in the utility mix; and then estimating the present value of the total funds made available to the utility over the life of the WECS. To apply the methodology to a specific case, it was necessary to develop various computer programs. Themore » following sections in this report list the programs developed for this study, briefly summarize their contents, and explain how they are used. Wherever possible, a typical input/output file is shown.« less