The workshop, titled “From Risk to Readiness: Mapping Environmental Effects and Information Needs” brought together marine energy stakeholders – including developers, researchers, students, and science advisors – to discuss how different groups conceptualize the environmental effects of marine energy.
Participants were divided into five groups to discuss how research and information around environmental effects – collision risk, noise, habitat change, EMF, and entanglement – can be improved to better address end-user needs. Key themes from the workshop include:
Re-evaluating environmental terms that can cause confusion for larger audiences
Importance of researchers being receptive to hearing and incorporating feedback when studying environmental effects
A mismatch between required studies for marine energy and public concerns associated with the technology
In addition to the workshop, Marg Daly participated in a panel where she discussed the potential for AI to support marine energy. The panel, titled “Improving AI with Better Data, DOE’s Mission Genesis, and AI for Marine Energy,” highlighted the benefits of AI, efforts across the national labs and DOE related to AI, and the advancements needed to ensure high-quality data processing using AI.
PNNL researchers at OREC+MECC 2026 in Portland, Oregon
Data Annotation for Marine Monitoring
Publicly available datasets can be annotated to train machine learning and AI models to support marine energy monitoring systems. High-quality and validated annotations are essential to produce accurate and reliable models, but the process is time-consuming and resource intensive.
The Data Annotation for Marine Monitoring (DAMM) project is exploring opportunities to use machine learning and AI to improve efficiencies for data processing and analysis of environmental datasets around marine energy deployments. DAMM is developing an active learning workflow, where expert review guides and refines the model iteratively rather than using a pre-trained model. The DAMM team is currently working with passive acoustics data and is interested in developing workflows for optical imagery and active acoustics in the future.
DAMM researchers are currently looking for test cases with passive acoustic data. If you’re interested in supporting a test case, or interested in learning more about this project, reach out to Margaret Daly (marg.daly@pnnl.gov).
Recently, DAMM has been supporting Triton's Acoustic Particle Motion research, which examined the physiological responses of juvenile Chinook salmon to low-frequency sounds. This work examined different acoustic components and their effects on species that rely on underwater sound for sensor input. During the experiment, optical imaging of the holding tank recorded fish movement. The DAMM team is applying the Segment Anything Model v3 (SAMv3) to track the salmon over time and detect any behavioral responses (i.e. startle response) to the playback sound and confirm that the fish “heard” the sounds.
AI annotations of Chinook Salmon using Segment Anything Model 3. (Image provided by Margaret Daly | PNNL)
PNNL-TUNAMELT Dataset Available
The Pacific Northwest National Laboratory dataset for Tracking Underwater Nautical Activity around Marine Energy LocaTions (PNNL-TUNAMELT) is the first, publicly available, labeled dataset of marine life interactions around underwater marine energy converters. Led by researchers Ted Nowak and Garrett Staines, this dataset contains over 100,000 acoustic camera video frames capturing marine life interactions around an underwater tidal turbine.
You can find the dataset here, and read the accompanying publication here!
Example acoustic camera image from the PNNL-TUNAMELT dataset that shows a marine creature (labeled in red) near the underwater turbine (center right) being detected in green.
In Other Energy News
Taking an Ecosystem Approach to Support Integrated Management of Marine Energy
PNNL researchers Andrea Copping, Lenaïg Hemery,Lysel Garavelli, and Mikaela Freeman recently published a paper in the Journal of Ocean Technologies titled “Progressing tidal energy through organized data approaches.” This paper highlights the applications of tools and approaches developed by OES-Environmental, including those that assist in organizing and applying data and information on potential risks from tidal turbines to permitting, mitigation, and licensing. You can read the paper here.
Webinar: Lessons Learned from the SURF-WEC Project in Hawaii
Join the Portal and Repository for Information on Renewable Energy (PRIMRE) on August 11, 2026 for a webinar on the Small Underwater Research Flap Wave Energy Converter (SURF-WEC), an oscillating surge wave energy converter that has been deployed off the coast of Oahu, Hawaii since March 2026. In this webinar, the SURF-WEC team will provide an in-depth overview of the project lifecycle and share critical lessons learned to support the marine energy community. You can sign up for the webinar here.
Triton is designed to support the development and testing of more precise and cost-effective environmental monitoring technologies for marine energy. Pacific Northwest National Laboratory leads Triton on behalf of the Department of Energy’s Hydropower and Hydrokinetics Office.
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