The development and success of commercial scale marine energy (ME) projects are connected to a thorough understanding of how ME devices interact with the surrounding environment. Quantification of these effects can help facilitate effective site planning and communication between developers, regulators, and stakeholders. Understanding the interplay of ME conversion technologies and the local environment can be achieved by combining calibrated and validated numerical models, site-specific receptor information, and risk assessment tools. These components have been integrated into the Spatial Environmental Assessment Toolkit (SEAT).
The SEAT is designed to help assess coastal, estuarine, and riverine sites where wave or current energy converters may be deployed. The change in wave fields and/or currents due to the presence of ME devices could result in modified circulation and sediment transport patterns. These changes could have an effect on local habitats, water quality, and the transport of larvae or sediment that are important to the local ecosystem, and therefore must be understood. Open-source numerical models, such as the spectral wave model SWAN and hydrodynamic model Dflow-FM, have been modified by Sandia National Laboratories to simulate the energy transfer of wave energy converters and current energy converters. The modified models, SNL-SWAN and Dflow-FM-CEC, incorporate device-specific characteristics, including size, power matrices, and/or rating curves to account for the energy produced by each device and the potential changes to the local environment. In addition, Sandia has developed Paracousti, a high-fidelity underwater sound propagation tool for evaluating changes to pressures and particle velocities within the marine environment from arrays of current- and wave-energy converters.
The framework outlined in the SEAT produces quantitative metrics for the potential risk resulting from the presence of devices and scaled by the spatial distribution of site-specific receptors. The results can be displayed in spatial gradients and summarized by receptor type. The analysis has been developed into a plug-in to the open-source, publicly available QGIS geospatial data program. This plug-in allows the user to integrate model results, receptor data, and site-specific thresholds to produce maps of risk at a site of interest. The use of the plug-in allows end-users to compare different array configurations and/or device types and integrate additional spatial information in their assessment of a site.
Two test cases, using publicly available, site-specific data have been developed for the PacWave South Site on the Oregon Coast and the Tanana River Current Energy Converter deployment site in Nenana, Alaska. The results demonstrate the ability for the SEAT to integrate different data types using the QGIS plug-in to assess a site’s potential environmental response due to the presence of ME devices.