Finding space: Siting Oregon's Wind Energy Areas

In the United States, wind power development is happening along many coastlines. By investing in research and development projects, on land and offshore, the United States strives to improve technology, create jobs, and grow the  Blue Economy . The Biden Administration seeks to  achieve 30 gigawatts of offshore wind power by 2030  and  15 gigawatts of floating offshore wind power capacity by 2035 , which will reduce our need for fossil fuels and combat climate change.

The Oregon coastline holds great potential for wind energy development, as almost the entire area has sustained ideal wind speeds (between 10-22 mph). In the process of siting wind energy development areas, a variety of interested parties — Tribal, federal, state, and local government entities; industry; conservation organizations; fishers; and the general public — provide feedback on concerns related to offshore wind energy site placement. Integrating all of those voices into the planning process is important to make sure that wind energy development happens in the areas of least conflict with existing ocean users, but determining those locations in the large, busy ocean can be challenging.

That's where NOAA's National Centers for Coastal Ocean Science (NCCOS) comes in. Our spatial scientists, in partnership with the Bureau of Ocean Energy Management (BOEM), used best available data to develop spatial models to inform siting for Oregon’s wind energy areas.

At NCCOS, we use  marine spatial science  to support BOEM in deciding suitable places for offshore wind energy development. We gather data from academia, government, industry, and local ecological knowledge sources to understand the ocean better.

The marine spatial planning process for siting wind energy areas is simple in theory:

• Gather the most relevant and best available data
• Add those data to a map
• Give the data a score from 0 to 1 (with 0 being "this is a place where we can't consider developing wind energy" and 1 being "there are no obvious conflicts with other users in this location”)
• Determine the areas that "score" closest to 1 across all factors.

In practice, a comprehensive study has many more steps!

One important note about this marine spatial planning process: it specifically includes input from various groups, like fishing communities, conservationists, government agencies, Tribal governments, and industries, to minimize disruption to important ocean activities and impacts to sensitive species and habitats. Our goal is to find suitable areas for offshore wind projects that don't disturb other ocean uses.

With that said, there’s a caveat here. The ocean is a busy place, between human uses of the ocean and the natural system of the ocean ecosystem. As such, there is no acre that is not conflicted. There will always be something happening in every mile of the ocean, whether that is a fishing ground, a vessel transit area, a feeding ground for birds, a location of an unexploded munition, a shipwreck site, or a myriad of other uses. The purpose of BOEM and NCCOS’ suitability modeling process is to deconflict as much as we can, using the best science to show us what’s happening in each parcel of the ocean.

The modeling process that we use at NCCOS is equally-weighted. What does that mean?

The first thing we do is remove all the constrained areas - the areas where we cannot put a wind energy development site.

Then, we consider four other categories (natural resources, industry and operations, fisheries, wind - the submodels shown in the mapview above) that could impact wind energy development. Each of these categories was considered equally, making sure that no one category of data was more important than another.

To determine suitability, each data layer received a score from 0 to 1. Higher scores, closer to 1, meant the area was more suitable for wind energy development. Constraints, places where we can't build a wind energy site like on major shipping fairways or already existing artificial reefs, were removed from analysis. The final suitability score for each hexagon was determined using the geometric mean (a special type of average) of all the individual scores from the data layers within each submodel.

This method is key because it gives all submodels equal weighting in the analysis—for example, natural resource concerns are just as important as fishery concerns.

The goal was to find at least two ocean areas in the Oregon study area that would be highly suitable for wind energy development. We used a technique called High-High clustering, which identifies areas—rather than just one hexagon grid cell—with the highest suitability.  

For example, take a look at the diagram on the right. In the model, there could be a grid cell that looks perfect for a wind energy area—a suitability score of 1. However, if that single grid cell is surrounded by grid cells that have low suitability—say, a score of 0.01—the whole area is less suitable for wind energy development. On the other hand, if the model returns a single grid cell that has low suitability by itself but is surrounded by grid cells with very high suitability, the whole cluster is identified as being highly suitable.

Wind energy areas should be contiguous areas that are large enough to allow for commercial scale electricity generation. So, this method of high-high clustering identifies the clusters that, considered all together, have high suitability.

To find these clusters, we:

• Overlaid BOEM’s aliquots onto the high-high clusters, and selected all clusters that intersected with an aliquot, forming continuous groups of aliquots (Aliquots are a boundary delineation unit used in offshore energy leasing.)
• Removed groups of aliquots that were less than 55,000 acres (slightly smaller than Baton Rouge, LA), to ensure there is enough space for wind energy development
• Added additional aliquots if they were fully surrounded by other high scoring aliquots

The results of the suitability analysis (from low to high relative suitability) are shown in the following maps, with a special category - constraints - for areas that are not suitable at all. The colors show the range of suitability on a scale from red to blue:

• Red - the area is not suitable at all for wind energy development
• Dark Orange - the area is low in suitability
• Light Orange - the area is moderately low in suitability
• Light Green - the area is moderately suitable
• Light Blue - the area is moderately high in suitability
• Blue - the area is highly suitable for wind energy development

For additional details on each submodel's inputs and results, see the full report  here .

The Oregon coast is a promising area for offshore wind energy. Working with interested parties has helped us find suitable areas for wind energy development while considering other ocean activities. By integrating a wide range of data sources and considering the perspectives of different interest groups, NCCOS and BOEM have identified areas with high wind potential that have the least conflict with other ocean uses for further consideration and analyses.

This comprehensive approach to offshore wind development in Oregon not only promises to diversify our energy mix but also offers significant economic opportunities, job creation, and a reduction in our nation's reliance on fossil fuels. These WEAs will contribute to the Biden Administration’s vision of achieving  15 gigawatts of floating offshore wind power capacity by 2035  and  Oregon’s goal of 100% clean energy usage by 2040 . By embracing the potential of offshore wind and continuing to prioritize responsible planning, we can create a thriving ecosystem where renewable energy coexists harmoniously with other ocean uses. The journey to a greener future begins here!

NOAA makes no warranties or representations whatsoever regarding the availability, quality, accuracy, content, completeness or suitability for the user's needs of such information. The services, information, and data made available on this storymap are provided 'as is' without warranties of any kind. These data are intended for coastal and ocean use planning and explicitly not for navigational use.