Mapping the Nation's Wind Power: Using the U.S. Wind Turbine Database
Did you know there are more than 57,000 wind turbines in the United States? In this video, we'll show you how you can get to know each and every one of them with our U.S. Wind Turbine Database and viewer, which we've assembled in partnership with the U.S. Department of Energy, DOE’s Lawrence Berkeley National Laboratory and the American Wind Energy Association.
Image Dimensions: 480 x 360
Location Taken: US
The U.S. Wind Turbine Database provides the locations of land-based and offshore wind turbines,
corresponding wind project information, and turbine technical specifications
for nearly 60,000 wind turbines in the United States.
For those who wish to explore the database without the need for additional software,
we’ve created a web application called the U.S. Wind Turbine Database Viewer.
The viewer let’s lets you visualize, inspect, and interact with the turbine
database through your favorite web browser.
In this video, we’ll highlight some of the major features of the viewer,
and show you how to easily navigate through the interface.
When you launch the Viewer, you’ll see a turbine density heatmap
that shows the current coverage of features in the database.
If you’d prefer to visualize turbine data as points when zoomed out,
simply toggle the heatmap switch, at the top of the sidebar.
Note that by default, the heatmap will transition to show the individual turbine locations as you zoom in.
For zooming into an area, we offer standard zoom tools along the left side of the interface.
Users can also use the mouse scroll wheel for zooming in or out,
or hold the shift key, and drag a box over their area of interest.
Map panning is enabled by default.
Simply click anywhere on the map, hold down the left mouse button, and drag the mouse.
Panning the map while holding down the CTRL key will allow you to adjust your pitch and bearing.
This is particularly useful when you want to visualize turbines in a perspective view.
For users with touch enabled devices, multi-touch pinch and swipe
gestures allow you to navigate through the map in a similar fashion.
When you want to zoom to a certain location, such as your house, town, or larger area,
use the location tool in the upper right of the interface.
There, you can enter specific information, such as a street address, lat/long coordinate pair,
or more general information like a zip code, or county name.
To access turbine data, hover the mouse over any turbine in the map interface.
If you’re using a touch enabled device, simply tap any of the turbine features
Upon hover or tap, a pop-up will appear showing a variety of turbine specific information.
Turbine level information includes, feature ID, project name,
year online, rated capacity, hub height, rotor diameter,
total height, turbine manufacturer and model, relative attribute and location confidence,
and the lat/long coordinates of the turbine.
When you move the map, the count and cumulative capacity of turbines
in the map view is displayed in the sidebar.
In addition, a wind project table will be populated that lists the wind projects that appear in the view.
The project table includes information like project name, project year online,
the number of turbines in the project, and the average rated capacity per turbine.
To highlight a particular project in the interface,
simply mouseover a project in the records table.
Clicking or tapping a record will zoom you to the selected project in the map window.
Users who are familiar with wind turbine project names can find them via
the project keyword search in the upper left of the interface.
As you type, project search returns matching your inquiry become
auto-populated in a drop-down list below the input field.
Simply click the name of the project in the drop-down list to be zoomed to the project site.
Table records can be sorted and filtered to make browsing more efficient.
Click on the column header of any field, to sort the table records in ascending or descending order.
To filter table records, enter text in the filter keywords box at the top of the records table.
In this example, if I wanted to filter projects that were in the state of Washington,
I’d simply type in "WA" as my keyword.
Note that sidebar information dynamically changes based on filtered results.
By default, the turbine features in the Viewer have a color ramp applied to them by rated capacity.
Users can change turbine styling by selecting any one of the attributes in the color ramp list,
or remove data-driven styling by selecting “None”.
When data-driven styling is applied, lower values will be displayed as cooler colors,
like blues and greens, and higher values will be displayed as warmer colors,
like oranges and reds.
As an example, let’s say I wanted to quickly get an idea of when turbines began
producing power in an area outside of Los Angeles.
To do this, I’ll choose “Year” as my data-driven attribute from the color ramp tool.
When clicked, a legend appears showing the range of years the turbines went online.
I see the earliest turbines, sited closer together in this area, were installed in the 1980’s, and appear as light blues and greens on the map.
Turbines that began producing power more recently, show up as oranges and reds in the interface.
I can combine data-driven styling with dynamic filtering using the range filter in my sidebar.
Turbine data can be filtered by total height, rated capacity, or year online.
In this same area, let’s say I wanted to know the number of turbines
that went online between 2000 and 2010.
I’ll choose “Year” as my range filter attribute, and move my slider handles to 2000 and 2010 respectively.
When the filter is applied, turbines that don’t meet these criteria disappear from the interface,
and sidebar information dynamically changes based on the active filter.
As a result, I see that there were 280 turbines that went online here during this time.
As a final example, let’s say I wanted to visualize the growth of turbine features over time,
at a national scale, with an emphasis on turbine capacity.
In my sidebar, I’ll switch from heatmap to point, choose “Year” as my range filter,
and choose “Capacity” as my data-driven style attribute.
To animate through time, I’ll simply click the animation tool next to my range filter attributes.
As the animation begins, I can see that some of the earliest turbines to go online
were in California, the Midwest, and Texas.
Since we’ve applied a style based on “Capacity", I can observe that the majority
of these early turbines, up until about the late 1990’s, are blue and green,
and have rated capacities less than about 2 MW.
The majority of red turbines, indicating rated capacities of around 3 MW or more, appear around 2010.
These are just some of the features available through the U.S. Wind Turbine Database Viewer.
We invite you to try it for yourself, or download the database free of charge at the link below.