Finding space: Siting Oregon's Wind Energy Areas
A sneak peak behind the science used to support identifying areas for offshore wind energy.
Offshore Wind in Oregon
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.
Map showing current underway offshore wind projects (last updated May 2024). Credit: BOEM
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.
Project Overview
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.
Schematic of the marine spatial science process.
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.
Area of Interest
In April 2022, BOEM published a Call for Information and Nominations to assess commercial interest in and obtain public input on potential wind energy leasing activities in Federal waters off the coast of Oregon. After considering input from interested parties, BOEM identified two sections, known as the Coos Bay and Brookings Call Areas, spanning over 1 million acres. From there, BOEM partnered with NCCOS to help map out what’s happening in that large ocean neighborhood. The goal of this study was to identify potential Draft Wind Energy Areas (WEAs) that could support 3 GW of wind energy in the Oregon Call Areas with a minimum area of ~55,000 acres.
We had several questions to answer with our marine spatial planning approach, such as:
- Where is most of the fishing activity happening?
- Where are any Department of Defense-identified national security concerns located?
- Where are the protected species like sea turtles or whales most likely to be found?
- Where are the shipping lanes and existing infrastructure (e.g., oil and gas platforms and pipelines), located?
We had a lot to learn!
Gridded Overlay
The first step in our spatial planning approach is to divide the region into smaller, more manageable spaces - so we divided the Call Area set by BOEM into over 110,000 individual 10-acre hexagons!
We use hexagon grids, rather than square grids, because they have more sides than squares. Having more sides provides a better fit to ocean data, since ocean data allows for movement in all directions – not just forward, backward, and side-to-side like on land.
Compiling Available Data
One of the reasons that our work is so comprehensive is that we take into account many different sources and types of data in our models. The data in the suitability model were gathered through collaboration with non-governmental organizations, U.S. Federal and State agencies, Tribal Nations, and the general public. Many datasets were gathered from the Marine Cadastre and OROWindMap , including datasets created for the BOEM Environmental Studies Program . Our final map showing overall suitability for wind energy is actually 5 maps overlaid on top of each other:
- Constraint layers describe areas where we cannot put wind energy sites due to various factors (military operations and major shipping lane paths).
- Natural Resources layers include information about protected species like whales, marine birds, and sensitive habitats.
- Industry and Operations layers map locations of submarine cables, as well as key industry concerns like scientific surveys.
- Wind layers allow the model to take into account basic concerns like how far away the closest port is, how deep the water is, what the wind speed is, etc.
- Fisheries layers illustrate the areas where commercial and recreational fisheries are active.
30 different data layers were incorporated into the Oregon analysis!
Natural Resource Data
NOAA Fisheries Protected Species Combined Data Layer
We closely collaborated with federal agencies like NOAA Fisheries and the U.S. Geological Survey (USGS) to understand protected and endangered species and their habitats. To minimize conflicts, we identified areas that should have the least impact on species like whales, marine birds, and corals. We combined the best available data for these resources, creating comprehensive data layers.
Scoring system from Farmer et al. (2022) 10 used for NOAA Fisheries protected species.
We partnered with NOAA Fisheries and Oregon Department of Fish and Wildlife to create a combined data layer for protected species. The data layer includes information about leatherback sea turtles, southern resident killer whales, blue whales, and humpback whales, which are listed under the Endangered Species Act and/or protected under the Marine Mammal Protection Act . These are a subset of highly vulnerable species that migrate, feed, or live in the Call Areas.
Scores were assigned to each species layer based on:
- Species’ status (e.g. endangered or protected)
- Population size (how many individuals are in the populations)
- Trend (is the species growing in population or declining in population)
These scores ranged from 0.1 (most vulnerable) to 0.9 (least vulnerable) and were combined into a single data layer, giving the highest weight to the lowest score. This approach helps us prioritize areas for ocean development based on species' vulnerability - the goal is to find the most suitable locations for wind energy areas with the fewest potential conflicts with these populations as possible.
NOAA Fisheries Habitat Combined Data Layer
We also collaborated with NOAA Fisheries to create a habitat data layer. We used best available data to score five habitat types for their sensitivity to offshore wind energy. Combining these scores, we determined the suitability of each grid cell for sensitive habitats like Essential Fish Habitat , rock reef groundfish habitat, deep-sea corals , the continental shelf break, and methane bubble streams.
Marine Bird Combined Data Layer
To minimize potential impacts from wind development on marine birds, we at NCCOS partnered with BOEM and USGS. Using existing bird density data, we created a combined spatial distribution layer that included 30 different bird species and 12 taxonomic groups. Each species or group received a vulnerability rating based on its sensitivity to offshore wind. These were combined to produce a final data layer for the model, representing the relative suitability for wind energy development with respect to marine birds across the Call Areas.
Pink-footed Shearwater. Credit: USFWS
Fisheries Data
NOAA Fisheries and Oregon Department of Fish and Wildlife Fisheries Combined Data Layer
Considering the importance of fishing in Oregon, NOAA Fisheries and the Oregon Department of Fish and Wildlife (ODFW) collaborated to create a combined data layer for fisheries. This data layer includes commercial and recreational fisheries and considers factors like fishing effort and revenue. Fisheries included:
- At-sea hake mid-water trawl
- Shoreside hake mid-water trawl
- Groundfish bottom trawl
- Groundfish pot gear
- Groundfish longline gear
- Pink shrimp trawl
- Dungeness crab
- Commercial troll/hook and line albacore
- Charter vessel albacore troll/hook and line
Operations Data
NOAA Fisheries Scientific Surveys Combined Data Layer
To minimize conflicts with scientific surveys conducted by NOAA Fisheries’ Northwest and Southwest Fisheries Science Centers, we collaborated to develop a combined scientific surveys data layer. This layer represents the survey operations' geographic footprints within the Call Areas, and assigns a lower score to the most sensitive survey operations.
Modeling Approach
Weighting the Submodels
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.
Generalized approach to a Multi-Criteria Decision Analysis suitability model.
Calculating the Final Score
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.
Wind Energy Area Option Identification and Ranking
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.
Diagram illustrating the concept of high-high clustering.
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
Suitability Results
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 .
Constraints Submodel
Constraints are data layers that have been identified as having a high level of conflict and are likely to limit wind energy development. This map shows the areas of the Call Area that are constrained by ocean activity (represented in red) and the areas that are potentially suitable for wind energy development (represented in blue). We collaborated with local interested parties to determine which data layers should be considered constraints based on their knowledge of ocean uses in the area.
National security assets are relatively extensive throughout many portions of U.S. Federal waters. The U.S. Department of Defense assessed the Call Areas, and they set areas that would conflict with their usage of the ocean.
Also in this layer is activity from the U.S. Coast Guard (USCG). They conducted a Pacific Coast Port Access Route Study (PACPARS) along the western seaboard to determine if the U.S. needs to modify existing or establish new shipping lanes. The USCG provided a fairway zone data layer that was included as a constraint.
This submodel is unique from the others in that it only had two score options - 1 (suitable) or 0 (not suitable).
Industry and Operations Submodel
Six NOAA Fisheries scientific survey footprints overlap with the Call Areas. Four data layers were developed and combined to be used in the suitability model as a single NOAA Fisheries scientific surveys layer. Eight 4-nautical-mile-wide survey corridors were given a lower score than areas with less survey activity.
While the majority of submarine cables were avoided in the Call Area development process, cables were taken into consideration as well. No overlap of submarine cables is present within the Brookings Call Area, and minimal overlap remains in the Coos Bay Call Area. A 500 and 1000 meter (0.26 and 0.54 nautical miles) setback was added to avoid potential interactions with those cables.
Natural Resources Submodel
Natural resources in and around the Call Areas were assessed to determine biologically important and sensitive habitats, along with designated marine protected areas. Protected species, habitat, and marine birds were considered, and the three combined data layers discussed earlier in this StoryMap were created and used within the natural resources submodel.
Fisheries Submodel
Several commercial and recreational fisheries datasets were considered for inclusion in the fisheries submodel. Overall, a total of nine fisheries were selected and used in the suitability model as a single NOAA Fisheries & ODFW fisheries layer. The Coos Bay Call Area had the highest overlap with the lowest suitability scores for trawling fisheries, and the majority of the fisheries interactions for the Brookings Call Area can be seen toward the eastern side.
Wind Submodel
Wind Energy Areas closer to shore, under normal circumstances, require less fuel and travel time for vessels and may reduce overall costs for running transmission lines. Being closer to principal ports should help new wind energy development sites use available port infrastructure.
In terms of wind speed, Oregon has some of the best wind resources in the country, and the high average wind speeds and consistency of the wind leads to consistent and continuous operation of wind energy sites. A levelized cost of energy model developed by the National Renewable Energy Laboratory (NREL) was used to represent these factors in dollars per megawatt for the year 2027. The overall levelized cost of energy is relatively higher in the northern portion of the Coos Bay Call Area.
Final Suitability
With all of those layers overlaid one on top of each other, the resulting suitability map is at the right.
Wind Energy Area Identification
Overall, using the spatial suitability model and public comments on the draft Wind Energy Areas, BOEM identified two WEAs , one in Coos Bay at 61,000 acres (slightly larger than Palm Springs, CA) and the second in Brookings at 158,00 acres (slightly larger than Virginia Beach, VA).
Coos Bay Wind Energy Area
The Coos Bay WEA is located on the northwest side of the Coos Bay Call Area. The 61,000-acre site is located offshore approximately 40 miles northwest of the Port of Coos Bay, Oregon.
Brookings Wind Energy Area
The Brookings WEA is located on the western side of the Brookings Call Area. The 158,000-acre site is located offshore approximately 24 miles west of the Port of Brookings Harbor, Oregon.
Conclusions
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!
Image of a floating offshore wind turbine. Credit: University of Maine
Interactive Web Map
Experience
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