Optimization of Wave Energy Converter Array Deployments while Minimizing Potential Environmental Risks

Craig Alexander Jones1, Samuel McWilliams2, Kaus Raghukumar1, Grace Chang1 and Jesse Roberts3, (1)Integral Consulting Inc., Santa Cruz, CA, United States, (2)Integral Consulting Inc., Santa Cruz, United States, (3)Sandia National Laboratories, Albequerque, NM, United States
The development of offshore renewable energy projects is growing rapidly worldwide and wave energy is potentially one of the largest resources. It has been shown that optimization of wave energy converter (WEC) device archetype and array size and shape to wave resources is a critical component for reduction of the levelized cost of wave energy such that it becomes a viable resource. However, a WEC array optimized to harness the maximum available wave energy could feasibly number in the hundreds of individual devices per array. These WEC arrays have the potential to alter nearshore wave propagation and circulation patterns and ecosystem processes. To help accelerate the realization of commercial-scale wave power, the Spatial Environmental Assessment Tool (SEAT) has been developed to assess WEC power output and simultaneously, evaluate the likelihood of environmental impact to coastal regions. A SEAT case study is presented for the central Oregon coast (USA) through coupled numerical model simulations and quantitative risk assessments of a number of different WEC array configurations. Derived climatological wave conditions were used as inputs to the model to allow for the calculation of risk metrics associated with various hydrodynamic and sediment transport variables such as maximum shear stress, bottom velocity, and change in bed elevation. Resultant risk maps and WEC power evaluation provide simple, quantitative, and spatially-resolved means of evaluating physical changes in the vicinity of hypothetical WEC arrays in response to varying wave conditions. The results demonstrate the utility of SEAT in informing stakeholders, regulators, and developers about the benefits of data-driven analysis that takes into account characteristics of WEC device characteristics, array layouts, site-specific modeling, and knowledge of wave dynamics to yield array shapes and sizes that satisfy multiple, often competing requirements.