OES-Environmental distributes metadata forms (questionnaires) to solicit information from researchers around the world who are exploring the environmental effects of marine renewable energy. This page provides a description and contact information related to the research. Content is updated on an annual basis.

Developing Parametric Source Functions for Wave Energy Converters

Status

In Progress

Principle Investigator Contact Information

Name: Brian Polagye
Affiliation: University of Washington, Pacific Marine Energy Center
Phone: (206) 543-7544
Email: bpolagye@uw.edu

Description

Because marine animals use sound for a wide range of biological functions, the noise radiated from wave energy converters (WECs) has the potential to affect marine animals by masking other types of sound or causing avoidance behaviours. To date, observations have found the radiated noise from WECs to be relatively limited, but, at the same time, relatively few WECs have been deployed and acoustically characterized. Increasing the knowledge base about radiated noise from WECs will help regulators and developers contextualize any associated risks for marine animals and reduce barriers to future WEC deployments. In addition, abnormal underwater noise can be indicative of mechanical issues with WECs that may not yet be apparent through other types of condition monitoring (e.g., component temperature, vibration). The University of Washington (UW) and Integral Consulting are partnering to characterize radiated noise from WECs deployed at PacWave and correlate noise attributable to WECs with environmental (e.g., sea state) and operational (e.g., mechanical rotation rate) covariates. 

At-sea measurements involve a two-stage approach. UW first deploys groups of Drifting Acoustic Instrumentation SYstems (DAISYs) around a WEC. These short term deployments of drifting hydrophones gather information about the types of sounds produced by a WEC and the range at which these sounds are likely to be detectable above background levels. Using time-delay-of-arrival processing, researchers are able to localize some of these sounds and differentiate between those originating from the WEC and those from other sources in the area (natural or anthropogenic). Following this, Integral Consulting deploys its NoiseSpotter® platform on the seabed near the WEC for a period of 30 days to capture temporal variations in radiated noise. The NoiseSpotter® is equipped with vector sensors that measure acoustic particle velocity, as well as a traditional hydrophone that measures acoustic pressure. Particle velocity is particularly useful because it conveys information about the direction of sound propagation and can be used to identify sounds originating from the WEC.

These measurements are post-processed through a semi-automated pipeline that isolates specific types of events (e.g., sound originating from the WEC power take-off) and correlates these with environmental and operational covariates. That comparison can help researchers, developers, and regulators to understand why the frequency and intensity of these sounds vary in time. Subsequently, these WEC "source functions" can be used to predict radiated noise under different conditions and, in combination with source functions for ambient noise, predict the range at which certain types of WEC sound might be audible to marine life.

Project websites:

Funding Source

U.S. Department of Energy Water Power Technologies Office

Funding Contact

Denis-Marc Nault (Denis-Marc.Nault@ee.doe.gov)

Location of Research

PacWave in Newport, OR

Project Aims

Using complementary data from NoiseSpotter(R) deployments by Integral Consulting and DAISY deployments by the University of Washington around wave energy converters at PacWave off Newport OR, the project team will assess the sources of sounds produced by wave energy converters and what drives them.

Study Progress

Initial work has focused on incremental upgrades to the DAISY and NoiseSpotter® platforms to improve data quality and endurance for deployment around WECs at PacWave. In parallel, the project team is developing an automated pipeline for detecting events of interest, localizing these to a WEC or other source, and identifying the probable source of the event (e.g., WEC power take-off, WEC mooring).

Key Findings

None to date.

Related Publications

None to date.