Acquiring and Processing NREL Wind Prospector Data. Steven Wallace, Old Saw Consulting, 27 Sep 2016

Transcription

1 Acquiring and Processing NREL Wind Prospector Data Steven Wallace, Old Saw Consulting, 27 Sep 2016

2 NREL Wind Prospector Interactive web page for viewing and querying wind data

3 Over 40,000 sites in the WECC 2 km x 2 km grid squares Power estimated assuming maximum 16 MW per site Power at 100 m hub height using current technology Actually, kind of complicated; see web site for details

4 Clicking on a site shows some data about wind potential there Wind Prospector allows interactive views of the data but the web interface itself doesn t provide for development of hourly wind shapes for wind plants.

5 The Wind Prospector allows Download of Data Click and drag a rectangle to get data for the sites within.

6 Provide Information and an will be sent for the Query

7 A Dialog Allows Specification of Data to Retrieve Note that the Download Limit Indicator constrains the amount of data that can be captured with one query. Here, two items (wind speed and power output) for one year for the rectangle on the earlier slide (about 60 sites) takes up about 75% of the allowed quota.

8 This brings up a Problem There are over 40,000 sites in the WECC; how do we make queries for sites at a time that will return all of the sites? The method used to address this will appear in a few slides. In the meantime, back to how to finish up an interactive query...

9 The Dialog will let You know if your Query is properly formed There is no specific link between a query and the associated . Consequently, if you submit 20 queries and receive 19 s, you cannot tell which query failed without analyzing the returned ZIP files.

10 SiteID Longitude Latitude Year Month Day Hour Minute density at hub height (kg/m^3) power (MW) surface air pressure (Pa) air temperature at 2m (K) wind direction at 100m (deg) wind speed at 100m (m/s) Wind Prospector query result file A Wind Prospector query returns a ZIP file with CSV text files for each site, containing data for each five minute period of the year. This example shows all of the data elements that can be requested for sites.

11 NREL published a report describing one methodology for extracting data To avoid learning curves for R language, and because statistical analysis was not the objective, python coding was used to extract the data directly from the downloaded ZIP files and aggregate it into hourly values

12 Documentation on how to query wind data is on the NREL Developer Network site d-toolkit-extract/ One may build a text string that constitutes a web query which, when pasted as a URL into a web browser, will give NREL the data needed to produce a set of site data and an linking to the ZIP archive.

13 Declare all variables as strings. Spaces must be replaced with '+', i.e., change 'John Smith' to 'John+Smith'. Define the wkt of the location and the year wkt=point( ) year=2010 You must request a developer.nrel.gov api key api_key=yourkey Set the attributes to extract separated by commas. attributes=power,wind_direction,wind_speed,temperature,pressure,density Choose year of data year=2010 Set leap year to true or false. True will return leap day data if present, false will not. leap_year=false Specify Coordinated Universal Time (UTC), 'true' will use UTC, 'false' will use the local time zone of the data. utc=false Your full name, use '+' instead of spaces. your_name=john+smith Your reason for using the data reason_for_use=beta+testing Your affiliation your_affiliation=my+institution Your address your_ =john.smith@server.com<mailto:john.smith@server.com> Please join our mailing list so we can keep you up-to-date on new developments. mailing_list=true Some more recent information on formatting web queries Additional details for the OCD among us.

14 NREL Provided a Table of Meta- Data Describing the Wind Sites Using maps of WECC and time zones, columns were added to help further identify the sites. Of over 120,000 sites, about 41,000 were in the WECC area (a little uncertainty about Texas, where two counties are in).

15 Back to our Size Problem There are over 40,000 sites in the WECC; how do we make queries for sites at a time that will return all of the sites? To address this, a spreadsheet was divided into rectangles 0.1 degree tall and 0.2 degree wide, and all NREL sites were tallied in their respective cell. VBA code then let the user select a rectangle of cells and the code reported how many sites were within. When an acceptable number of sites were included, the user could then press a button to generate the needed query, and to shade and put a border around the rectangle of cells. When done, over 850 queries covered the sites in the WECC.

16 The List of Queries was then Processed for the Year & Data needed A python-language program sequenced through the queries at specified intervals, in order to minimize impact on NREL s system and to avoid their system-imposed limits. One year s data for two items for all WECC sites resulted in over 30 gigabytes of downloaded ZIP files.

17 The next Step is to Aggregate the Site Data into Hourly Time Series The data are stored in a custom binary data archive where the data for one year for one item requires about 1.5 gigabytes.

18 Need a way to define the zones A zone can be defined by bounding grid points TEPPC used rectangular zones in 2024 It is not difficult to allow arbitrary simple polygons Need a list of sites that are in the zone Given a list of vertices for the polygon, routines exist to determine whether a given site is inside or outside of the polygon Sequencing through the list of WECC sites provides a list of those in the defined zone Need to add and scale the hourly series for the sites The data are downloaded for local standard time, so some need to be shifted to Mountain Standard Time (by repeating the first hour and dropping the last) The hourly energy numbers are scaled by dividing the sum over sites for each hour by the total output capacity of the sites and then multiplying by 10,000 to give an integervalued curve Then the Site Data need to be Aggregated into Hourly Zonal Series

19 Maps from the Internet Show WECC and Time Zone Details for Texas

20 Time Zones in Oregon and Idaho may also be Approximated by Counties, though this Should be Improved in the Future

21 Google Provides Definitions of State Borders Excel Scatter Plots can Chart the Borders State Boundaries from Google fusiontables (125) (120) (115) (110) (105) (100) Nevada Arizona Montana Colorado Idaho New Mexico Wyoming Utah Washington Oregon NV AZ MT CO ID NM WY UT WA OR Lon Lat Lon Lat Lon Lat Lon Lat Lon Lat Lon Lat Lon Lat Lon Lat Lon Lat Lon ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( )

22 Adding Coordinates for Wind Sites Helps in Locating Them State Boundaries from Google fusiontables (125) (120) (115) (110) (105) (100) Nevada Arizona Montana Colorado Idaho New Mexico Wyoming Utah Washington Oregon NV AZ MT CO ID NM WY UT WA OR Lon Lat Lon Lat Lon Lat Lon Lat Lon Lat Lon Lat Lon Lat Lon Lat Lon Lat Lon ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( )

23 Top Left Bottom right Name Lat Long Lat Long Cap MW # NREL Profiles 1 WT_WA_SO WT_WA_WE WT_WA_CE WT_WA_EA WT_OR_NO WT_OR_CE WT_OR_EA WT_ID_SO WT_ID_EA WT_MT_NO WT_MT_SO WT_WY_CE WT_WY_SW WT_WY_SE WT_UT_NO WT_UT_SO WT_CO_NE WT_CO_CE WT_CO_SO WT_CO_SE WT_NM_EA WT_NM_CE WT_NM_SO WT_TX_WE WT_AZ_WE WT_AZ_SO WT_AZ_EA WT_NV_EA WT_NE_SW WT_CA_NO WT_CA_CE WT_CA_SO WT_CA_LA A Table of Coordinates Defines the TEPPC 2024 Wind Zones

24 The TEPPC 2024 Wind Zones may also be plotted Note that the zones, selected for the wind and solar data sets, do not align well with sites identified in the dataset

25 Wind Zone Defs and Sites Within Polygons Test Zone One Points Lon Lat 1 ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) New Polygons may be defined with more Complexity by a List of Vertex Coordinates

26 76 Sites 1,118 MW Capcity Site ID Longitude Latitude ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) All wind sites can be examined by VBA code to determine whether they are inside the polygon. The hourly generation curves for the sites may then be aggregated and normalized (so that the range from zero to total capacity runs from 0 to 10,000) to produce hourly shape files for the specified wind zones

27 What s Next? An effort is underway to download data for all available years ( ) for the WECC Power output data are the values estimated by NREL as being appropriate to the site (see their documentation for the curves used) The wind speed at 100 meters is also being downloaded, to allow other wind power curves to be applied What is needed is a definition of bounding polygons for wind energy zones to use in production cost modeling, in order to aggregate the correct sites

28 Existing Wind Plants Their locations may raise questions about how to use the NREL sites to select the best build options

29 Existing Sites might be used to Define Wind Zones