Marine hydrokinetic devices, such as wave energy converters (WECs), can unlock untapped energy from the ocean's currents and waves. Acoustic impact assessments are required to ensure that the noise these devices generate will not negatively impact marine life, and accurate modeling of noise provides an a priori means to viably perform this assessment. We present a case study of the PacWave South site, a WEC testing site off the coast of Newport, Oregon, demonstrating the use of ParAcousti, an open-source hydroacoustic propagator tool, to model noise from an array of 28 WECs in a 3-dimensional (3-D) realistic marine environment. Sound pressure levels are computed from the modeled 3-D grid of pressure over time, which we use to predict marine mammal acoustic impact metrics (AIMs). We combine two AIMs, signal to noise ratio and sensation level, into a new metric, the effective signal level (ESL), which is a function of propagated sound, background noise levels, and hearing thresholds for marine species and is evaluated across 1/3 octave frequency intervals. The ESL model can be used to predict and quantify the potential impact of an anthropogenic signal on the health and behavior of a marine mammal species throughout the 3-D simulation area.
With the urgent need to mitigate climate change and rising global temperatures, technological solutions that reduce atmospheric CO2 are an increasingly important part of the global solution. As a result, the nascent carbon capture, utilization, and storage (CCUS) industry is rapidly growing with a plethora of new technologies in many different sectors. There is a need to holistically evaluate these new technologies in a standardized and consistent manner to determine which technologies will be the most successful and competitive in the global marketplace to achieve decarbonization targets. Life cycle assessment (LCA) and techno-economic assessment (TEA) have been employed as rigorous methodologies for quantitatively measuring a technology's environmental impacts and techno-economic performance, respectively. However, these metrics evaluate a technology's performance in only three dimensions and do not directly incorporate stakeholder needs and values. In addition, technology developers frequently encounter trade-offs during design that increase one metric at the expense of the other. The technology performance level (TPL) combined indicator provides a comprehensive and holistic assessment of an emerging technology's potential, which is described by its techno-economic performance, environmental impacts, social impacts, safety considerations, market/deployability opportunities, use integration impacts, and general risks. TPL incorporates TEA and LCA outputs and quantifies the trade-offs between them directly using stakeholder feedback and requirements. In this article, the TPL methodology is being adapted from the marine energy domain to the CCUS domain. Adapted metrics and definitions, a stakeholder analysis, and a detailed foundation-based application of the systems engineering approach to CCUS are presented. The TPL assessment framework is couched within the internationally standardized LCA framework to improve technical rigor and acceptance. It is demonstrated how stakeholder needs and values can be directly incorporated, how LCA and TEA metrics can be balanced, and how other dimensions (listed earlier) can be integrated into a single metric that measures a technology's potential.
Costs to permit Marine Energy projects are poorly understood. In this paper we examine environmental compliance and permitting costs for 19 projects in the U.S., covering the last 2 decades. Guided discussions were conducted with developers over a 3-year period to obtain historical and ongoing project cost data relative to environmental studies (e.g., baseline or pre-project site characterization as well as post-installation effects monitoring), stakeholder outreach, and mitigation, as well as qualitative experience of the permitting process. Data are organized in categories of technology type, permitted capacity, pre-and post-installation, geographic location, and funding types. We also compare our findings with earlier logic models created for the Department of Energy (i.e., Reference Models). Environmental studies most commonly performed were for Fish and Fisheries, Noise, Marine Habitat/Benthic Studies and Marine Mammals. Studies for tidal projects were more expensive than those performed for wave projects and the range of reported project costs tended to be wider than ranges predicted by logic models. For eight projects reporting full project costs, from project start to FERC or USACE permit, the average amount for environmental permitting compliance was 14.6%.
Surrogate models maximize information utility by building predictive models in place of computational or experimentally expensive model runs. Marine hydrokinetic current energy converters require large-domain simulations to estimate array efficiencies and environmental impacts. Meso-scale models typically represent turbines as actuator discs that act as momentum sinks and sources of turbulence and its dissipation. An OpenFOAM model was developed where actuator disc k-ε turbulence was characterized using an approach developed for flows through vegetative canopies. Turbine-wake data from laboratory flume experiments collected at two influent turbulence intensities were used to calibrate parameters in the turbulence-source terms in the k-ε equations. Parameter influences on longitudinal wake profiles were estimated using Gaussian process regression with subsequent optimization minimizing the objective function within 3.1% of those obtained using the full model representation, but for 74% of the computational cost (far fewer model runs). This framework facilitates more efficient parameterization of the turbulence-source equations using turbine-wake data.
This report summarizes the key contributions and lessons learned from SNL experience in technical reviews of Controls awardees in the DOE SPA program from 2013 - 2020. The purpose of this report is to provide observations and technical suggestions that are likely to be beneficial to the WEC industry as a whole. Over the course of the SPA FOA program, SNL has engaged in technical review for a total of 5 different Controls awardees. The awardees represent a diversity of WEC devices and the application of different control design approaches. The report begins with a summary of key performance metrics results reported by the 5 Controls awardees. This is followed by a summary of observations and lessons learned distilled from the technical reviews of the awardees . The report concludes with a list of general technical suggestions for future WEC controls projects.
For renewable ocean wave energy to support global energy demands, wave energy converters (WECs) will likely be deployed in large numbers (farms), which will necessarily change the nearshore environment. Wave farm induced changes can be both helpful (e.g., beneficial habitat and coastal protection) and potentially harmful (e.g., degraded habitat, recreational, and commercial use) to existing users of the coastal environment. It is essential to estimate this impact through modeling prior to the development of a farm, and to that end, many researchers have used spectral wave models, such as Simulating WAves Nearshore (SWAN), to assess wave farm impacts. However, the validity of the approaches used within SWAN have not been thoroughly verified or validated. Herein, a version of SWAN, called Sandia National Laboratories (SNL)-SWAN, which has a specialized WEC implementation, is verified by comparing its wave field outputs to those of linear wave interaction theory (LWIT), where LWIT is theoretically more appropriate for modeling wave-body interactions and wave field effects. The focus is on medium-sized arrays of 27 WECs, wave periods, and directional spreading representative of likely conditions, as well as the impact on the nearshore. A quantitative metric, the Mean Squared Skill Score, is used. Results show that the performance of SNL-SWAN as compared to LWIT is “Good” to “Excellent”.
The marine and hydrokinetic (MHK) industry plays a vital role in the U.S. clean energy strategy by providing a renewable, domestic energy source that may offset the need for traditional energy sources. The first MHK deployments in the U.S. have incurred very high permitting costs and long timelines for deploying projects, which increases project risk and discourages investment. A key challenge to advancing an economically competitive U.S. MHK industry is reducing the time and cost required for environmental permitting and compliance with government regulations. Other industries such as offshore oil and gas, offshore wind energy, subsea power and data cables, onshore wind energy, and solar energy facilities have all developed more robust permitting and compliance pathways that provide lessons for the MHK industry in the U.S. and may help inform the global consenting process. Based on in-depth review and research into each of the other industries, we describe the environmental permitting pathways, the main environmental concerns and types of monitoring typically associated with them, and factors that appear to have eased environmental permitting and compliance issues.
Integration of renewable power sources into grids remains an active research and development area,particularly for less developed renewable energy technologies such as wave energy converters (WECs).WECs are projected to have strong early market penetration for remote communities, which serve as naturalmicrogrids. Hence, accurate wave predictions to manage the interactions of a WEC array with microgridsis especially important. Recently developed, low-cost wave measurement buoys allow for operationalassimilation of wave data at remote locations where real-time data have previously been unavailable. This work includes the development and assessment of a wave modeling framework with real-time dataassimilation capabilities for WEC power prediction. The availability of real-time wave spectral componentsfrom low-cost wave measurement buoys allows for operational data assimilation with the Ensemble Kalmanfilter technique, whereby measured wave conditions within the numerical wave forecast model domain areassimilated onto the combined set of internal and boundary grid points while taking into account model andobservation error covariances. The updated model state and boundary conditions allow for more accuratewave characteristic predictions at the locations of interest. Initial deployment data indicated that measured wave data from one buoy that were assimilated intothe wave modeling framework resulted in improved forecast skill for a case where a traditional numericalforecast model (e.g., Simulating WAves Nearshore; SWAN) did not well represent the measured conditions.On average, the wave power forecast error was reduced from 73% to 43% using the data assimilationmodeling with real-time wave observations.
Integration of renewable power sources into grids remains an active research and development area,particularly for less developed renewable energy technologies such as wave energy converters (WECs).WECs are projected to have strong early market penetration for remote communities, which serve as naturalmicrogrids. Hence, accurate wave predictions to manage the interactions of a WEC array with microgridsis especially important. Recently developed, low-cost wave measurement buoys allow for operationalassimilation of wave data at remote locations where real-time data have previously been unavailable. This work includes the development and assessment of a wave modeling framework with real-time dataassimilation capabilities for WEC power prediction. The availability of real-time wave spectral componentsfrom low-cost wave measurement buoys allows for operational data assimilation with the Ensemble Kalmanfilter technique, whereby measured wave conditions within the numerical wave forecast model domain areassimilated onto the combined set of internal and boundary grid points while taking into account model andobservation error covariances. The updated model state and boundary conditions allow for more accuratewave characteristic predictions at the locations of interest. Initial deployment data indicated that measured wave data from one buoy that were assimilated intothe wave modeling framework resulted in improved forecast skill for a case where a traditional numericalforecast model (e.g., Simulating WAves Nearshore; SWAN) did not well represent the measured conditions.On average, the wave power forecast error was reduced from 73% to 43% using the data assimilationmodeling with real-time wave observations.
Flood irrigation benefits from low infrastructure costs and maintenance but the scour near the weirs can cause channeling of the flow preventing the water from evenly dispersing across the field. Using flow obstructions in front of the weir could reduce be a low cost solution to reduce the scour. The mitigation strategy was to virtually simulate the effects of various geometric changes to the morphology (e.g. holes and bumps) in front of the weir as a means to diffuse the high intensity flow coming from the gate. After running a parametric study for the dimensions of the shapes that included a Gaussian, semi-circle, and rectangle; a Gaussian-hole in front of the gates showed the most promise to reduce farm field shear-stresses with the added benefit of being easy to construct and implement in practice. Further the simulations showed that the closer the Gaussian-hole could be placed to the gate the sooner the high shear stress could be reduced. To realize the most benefit from this mitigation strategy, it was determined that the maximum depth of the Gaussian-hole should be 0.5 m. The width of the hole in the flow direction and the length of the Gaussian-hole normal to the flow should be 0.5 m and 3 m respectively as measured by the full width at half maximum.
Variability in the predicted cost of energy of an ocean energy converter array is more substantial than for other forms of energy generation, due to the combined stochastic action of weather conditions and failures. If the variability is great enough, then this may influence future financial decisions. This paper provides the unique contribution of quantifying variability in the predicted cost of energy and introduces a framework for investigating reduction of variability through investment in components. Following review of existing methodologies for parametric analysis of ocean energy array design, the development of the DTOcean software tool is presented. DTOcean can quantify variability by simulating the design, deployment and operation of arrays with higher complexity than previous models, designing sub-systems at component level. A case study of a theoretical floating wave energy converter array is used to demonstrate that the variability in levelised cost of energy (LCOE) can be greatest for the smallest arrays and that investment in improved component reliability can reduce both the variability and most likely value of LCOE. A hypothetical study of improved electrical cables and connectors shows reductions in LCOE up to 2.51% and reductions in the variability of LCOE of over 50%; these minima occur for different combinations of components.
Scour beneath seafloor pipelines, cables, and other offshore infrastructure is a well-known problem. Recent interest in seafloor mounted wave energy converters brings another dynamic element into the traditional seafloor scour problem. In this paper, we consider the M3 Wave APEX device, which utilizes airflow between two flexible chambers to generate electricity from waves. In an initial at-sea deployment of a demonstration/experimental APEX in September 2014 off the coast of Oregon, scour beneath the device was observed. As sediment from the beneath the device was removed by scour, the device's pitch orientation was shifted. This change in pitch orientation caused a degradation in power performance. Characterizing the scour associated with seafloor mounted wave energy conversion devices such as the M3 device is the objective of the present work.
The wave energy resource for U.S. coastal regions has been estimated at approximately 1,200 TWh/ yr (EPRI 2011). The magnitude is comparable to the natural gas and coal energy generation. Although the wave energy industry is relatively new from a commercial perspective, wave energy conversion (WEC) technology is developing at an increasing pace. Ramping up to commercial scale deployment of WEC arrays requires demonstration of performance that is economically competitive with other energy generation methods. The International Electrotechnical Commission has provided technical specifications for developing wave energy resource assessments and characterizations, but it is ultimately up to developers to create pathways for making a specific site competitive. The present study uses example sites to evaluate the annual energy production using different wave energy conversion strategies and examines pathways available to make WEC deployments competitive. The wave energy resource is evaluated for sites along the U.S. coast and combinations of wave modeling and basic resource assessments determine factors affecting the cost of energy at these sites. The results of this study advance the understanding of wave resource and WEC device assessment required to evaluate commercial-scale deployments.
Integration of renewable power sources into electrical grids remains an active research and development area, particularly for less developed renewable energy technologies, such as wave energy converters (WECs). High spatio-temporal resolution and accurate wave forecasts at a potential WEC (or WEC array) lease area are needed to improve WEC power prediction and to facilitate grid integration, particularly for microgrid locations. The availability of high quality measurement data from recently developed low-cost buoys allows for operational assimilation of wave data into forecast models at remote locations where real-time data have previously been unavailable. This work includes the development and assessment of a wave modeling framework with real-time data assimilation capabilities for WEC power prediction. Spoondrift wave measurement buoys were deployed off the coast of Yakutat, Alaska, a microgrid site with high wave energy resource potential. A wave modeling framework with data assimilation was developed and assessed, which was most effective when the incoming forecasted boundary conditions did not represent the observations well. For that case, assimilation of the wave height data using the ensemble Kalman filter resulted in a reduction of wave height forecast normalized root mean square error from 27% to an average of 16% over a 12-hour period. This results in reduction of wave power forecast error from 73% to 43%. In summary, the use of the low-cost wave buoy data assimilated into the wave modeling framework improved the forecast skill and will provide a useful development tool for the integration of WECs into electrical grids.
This three-year effort started in FY17 with the primary objective of detailing the environmental compliance costs and lessons learned from U.S. based MHK projects that have gone through the permitting and compliance process. The project goal is to find ways to improve the efficiency and effectiveness of the permitting and compliance process that reduce deployment uncertainties and associated risks/costs; ultimately encouraging investment in MHK projects. The project team is composed of Sandia National Laboratories, H. T. Harvey & Associates, Integral Consulting, and Kearns & West. Step one of the project process, collect data to determine permitting and compliance costs, was a focus during 2017, but is an ongoing process to ensure the project team is working with the most recent and accurate data as possible. Currently, the project team is focusing on step two of the project process, identify cost reduction pathways. Step three, develop cost reduction strategies, will follow during Fall 2018 and Winter 2019. Each step is envisioned as an iterative approach working with industry and regulators to best meet the project goal.
Marine hydrokinetic (MHK) devices generate electricity from the motion of tidal and ocean currents, as well as ocean waves, to provide an additional source of renewable energy available to the United States. These devices are a source of anthropogenic noise in the marine ecosystem and must meet regulatory guidelines that mandate a maximum amount of noise that may be generated. In the absence of measured levels from in situ deployments, a model for predicting the propagation of sound from an array of MHK sources in a real environment is essential. A set of coupled, linearized velocity-pressure equations in the time-domain are derived and presented in this paper, which are an alternative solution to the Helmholtz and wave equation methods traditionally employed. Discretizing these equations on a three-dimensional (3D), finite-difference grid ultimately permits a finite number of complex sources and spatially varying sound speeds, bathymetry, and bed composition. The solution to this system of equations has been parallelized in an acoustic-wave propagation package developed at Sandia National Labs, called Paracousti. This work presents the broadband sound pressure levels from a single source in two-dimensional (2D) ideal and Pekeris wave-guides and in a 3D domain with a sloping boundary. The paper concludes with demonstration of Paracousti for an array of MHK sources in a simple wave-guide.
This three-year effort started in FY17 with the primary objective of detailing the environmental compliance costs and lessons learned from U.S. based MHK projects that have gone through the permitting and compliance process. The project goal is to find ways to improve the efficiency and effectiveness of the permitting and compliance process that reduce deployment uncertainties and associated risks/costs; ultimately encouraging investment in MHK projects. The project team is composed of Sandia National Laboratories, H. T. Harvey & Associates, Integral Consulting, and Kearns & West. Step one of the project process, collect data to determine permitting and compliance costs, was a focus during 2017, but is an ongoing process to ensure the project team is working with the most recent and accurate data as possible. Currently, the project team is focusing on step two of the project process, identify cost reduction pathways. Step three, develop cost reduction strategies, will follow during Fall 2018 and Winter 2019. Each step is envisioned as an iterative approach working with industry and regulators to best meet the project goal.
Developing sound methods to evaluate risk of seabed mobility and alteration of sediment transport patterns in the near-shore coastal regions due to the presence of Offshore Wind (OW) infrastructure is critical to project planning, permitting, and operations. OW systems may include seafloor foundations, cabling, floating structures with gravity anchors, or a combination of several of these systems. Installation of these structures may affect the integrity of the sediment bed, thus affecting seabed dynamics and stability. It is therefore necessary to evaluate hydrodynamics and seabed dynamics and the effects of OW subsea foundations and cables on sediment transport. A methodology is presented here to map a site's sediment (seabed) stability and can in turn support the evaluation of the potential for these processes to affect OW deployments and the local ecology. Sediment stability risk maps are developed for a site offshore of Central Oregon. A combination of geophysical site characterization, metocean analysis, and numerical modeling is used to develop a quantitative assessment of local scour and overall seabed stability. The findings generally show the presence of structures reduces the sediment transport in the lee area of the array by altering current and wave fields. The results illustrate how the overall regional patterns of currents and waves influence local scour near pilings and cables.
This three year effort started in FY17 with the objectives of capturing environmental compliance costs and lessons learned from MHK developments that have gone through the permitting and compliance process. The goal is to find ways to improve the efficiency and effectiveness of the permitting and compliance process and reduce costs to encourage investment in MHK projects. The project team is composed of Sandia National Laboratories, Integral Consulting, Kearns & West, and H. T. Harvey & Associates. Step one of the project process, collect data to determine permitting and compliance costs, is currently underway. Step two of the project process, identify cost reduction pathways and step three, develop cost reduction strategies, will follow and are envisioned as an iterative approach to best meet the project goal.
Hydrokinetic energy from flowing water in open channels has the potential to support local electricity needs with lower regulatory or capital investment than impounding water with more conventional means. MOU agencies involved in federal hydropower development have identified the need to better understand the opportunities for hydrokinetic (HK) energy development within existing canal systems that may already have integrated hydropower plants. This document provides an overview of the main considerations, tools, and assessment methods, for implementing field tests in an open-channel water system to characterize current energy converter (CEC) device performance and hydrodynamic effects. It describes open channel processes relevant to their HK site and perform pertinent analyses to guide siting and CEC layout design, with the goal of streamlining the evaluation process and reducing the risk of interfering with existing uses of the site. This document outlines key site parameters of interest and effective tools and methods for measurement and analysis with examples drawn from the Roza Main Canal, in Yakima, WA to illustrate a site application.
The technology performance level (TPL) assessments can be applied at all technology development stages and associated technology readiness levels (TRLs). Even, and particularly, at low TRLs the TPL assessment is very effective as it, holistically, considers a wide range of WEC attributes that determine the techno-economic performance potential of the WEC farm when fully developed for commercial operation. The TPL assessment also highlights potential showstoppers at the earliest possible stage of the WEC technology development. Hence, the TPL assessment identifies the technology independent “performance requirements.” In order to achieve a successful solution, the entirety of the performance requirements within the TPL must be considered because, in the end, all the stakeholder needs must be achieved. The basis for performing a TPL assessment comes from the information provided in a dedicated format, the Technical Submission Form (TSF). The TSF requests information from the WEC developer that is required to answer the questions posed in the TPL assessment document.
The Wave - SPARC project developed the Technology Performance Level (TPL) assessment procedure based on a rigorous Systems Engineering exercise. The TPL assessment allows a whole system evaluation of Wave Energy Conversion Technology by measuring it against the requirements determined through the Systems Engineering exercise. The TPL assessment is intended to be useful in technology evaluation; in technology innovation; in allocation of public or priva te investment, and; in making equipment purchasing decisions. This Technical Submission Form (TSF) serves the purpose of collecting relevant and complete information, in a technology agnostic way, to allow TPL assessment s to be made by third party assessor s. The intended usage of this document is that the organization or people that are performing the role of developers or promoters of a particular technology will use this form to provide the information necessary for the organization or people who are perf orming the assessor role to use the TPL assessment.
A motivation for undertaking this stakeholder requirements analysis and Systems Engineering exercise is to document the requirements for successful wave energy farms to facilitate better design and better design assessments. A difficulty in wave energy technology development is the absence to date of a verifiable minimum viable product against which the merits of new products might be measured. A consequence of this absence is that technology development progress, technology value, and technology funding have largely been measured, associated with, and driven by technology readiness, measured in technology readiness levels (TRLs). Originating primarily from the space and defense industries, TRLs focus on procedural implementation of technology developments of large and complex engineering projects, where cost is neither mission critical nor a key design driver. The key deficiency with the TRL approach in the context of wave energy conversion is that WEC technology development has been too focused on commercial readiness and not enough on the stakeholder requirements and particularly economic viability required for market entry.
This document presents the revised Technology Performance Level (TPL) assessment methodology. There are three parts to this revised methodology 1) the Stakeholder Needs and Assessment Guidance (this document), 2) the Technical Submission form, 3) the TPL scoring spreadsheet. The TPL assessment is designed to give a technology neutral or agnostic assessment of any wave energy converter technology. The focus of the TPL is on the performance of the technology in meeting the customer’s needs. The original TPL is described in [1, 2] and those references also detail the critical differences in the nature of the TPL when compared to the more widely used technology readiness level (TRL). (Wave energy TRL is described in [3]). The revised TPL is particularly intended to be useful to investors and also to assist technology developers to conduct comprehensive assessments in a way that is meaningful and attractive to investors. The revised TPL assessment methodology has been derived through a structured Systems Engineering approach. This was a formal process which involved analyzing customer and stakeholder needs through the discipline of Systems Engineering. The results of the process confirmed the high level of completeness of the original methodology presented in [1] (as used in the Wave Energy Prize judging) and now add a significantly increased level of detail in the assessment and an improved more investment focused structure. The revised TPL also incorporates the feedback of the Wave Energy Prize judges.
Three different ways of combining scores are used in the revised formulation. These are arithmetic mean, geometric mean and multiplication with normalisation. Arithmetic mean is used when combining scores that measure similar attributes, e.g. used for combining costs. The arithmetic mean has the property that it is similar to a logical OR, e.g. when combining costs it does not matter what the individual costs are only what the combined cost is. Geometric mean and Multiplication are used when combining scores that measure disparate attributes. Multiplication is similar to a logical AND, it is used to combine ‘must haves.’ As a result, this method is more punitive than the geometric mean; to get a good score in the combined result it is necessary to have a good score in ALL of the inputs. e.g. the different types of survivability are ‘must haves.’ On balance, the revised TPL is probably less punitive than the previous spreadsheet, multiplication is used sparingly as a method of combining scores. This is in line with the feedback of the Wave Energy Prize judges.
Permafrost-dominated coastlines in the Arctic are rapidly disappearing. Arctic coastal erosion rates in the United States have doubled since the middle of the twentieth century and appear to be accelerating. Positive erosion trends have been observed for highly-variable geomorphic conditions across the entire Arctic, suggesting a major (human-timescale) shift in coastal landscape evolution. Unfortunately, irreversible coastal land loss in this region poses a threat to native, industrial, scientific, and military communities. The Arctic coastline is vast, spanning more than 100,000 km across eight nations, ten percent of which is overseen by the United States. Much of area is inaccessible by all-season roads. People and infrastructure, therefore, are commonly located near the coast. The impact of the Arctic coastal erosion problem is widespread. Homes are being lost. Residents are being dispersed and their villages relocated. Shoreline fuel storage and delivery systems are at greater risk. The U.S. Department of Energy (DOE) and Sandia National Laboratories (SNL) operate research facilities along some of the most rapidly eroding sections of coast in the world. The U.S. Department of Defense (DOD) is struggling to fortify coastal radar sites, operated to ensure national sovereignty in the air, against the erosion problem. Rapid alterations to the Arctic coastline are facilitated by oceanographic and geomorphic perturbations associated with climate change. Sea ice extent is declining, sea level is rising, sea water temperature is increasing, and permafrost state is changing. The polar orientation of the Arctic exacerbates the magnitude and rate of the environmental forcings that facilitate coastal land area loss. The fundamental mechanics of these processes are understood; their non-linear combination poses an extreme hazard. Tools to accurately predict Arctic coastal erosion do not exist. To obtain an accurate predictive model, a coupling of the influences of evolving wave dynamics, thermodynamics, and sediment dynamics must be developed. The objective of this document is to present the state-of-the-science and outline the key steps for creation of a framework that will allow for improved prediction of Arctic coastal erosion rates. This is the first step towards the quantification of coastal hazards that will allow for sustainable planning and development of Arctic infrastructure.
Capabilities and functions are hierarchical structures (i.e. taxonomies) that are used in a systems engineering framework to identify complimentary requirements for the system: what the system must do to achieve what it must be. In the case of capabilities, the taxonomy embodies the list of characteristics that are desired, from the perspective of the stakeholders, for the system to be successful. In terms of the functions, the hierarchy represents the solution agnostic (i.e. independent of specific design embodiments) elements that are needed to meet the stakeholder requirements. This paper will focus on the development of the functions. The functions define the fundamental elements of the solution that must be provided in order to achieve the mission and deliver the capabilities. They identify the behaviors the farm must possess, i.e. the farm must be able to generate and deliver electricity from wave power. High-level functions are independent of the technology or design used to implement the function. However, detailed functions may begin to border on specific design choices. Hence a strong effort has been made to maintain functions that are design agnostic.
The numerical model, SWAN (Simulating WAves Nearshore) , was used to simulate wave conditions in Kaneohe Bay, HI in order to determine the effects of wave energy converter ( WEC ) devices on the propagation of waves into shore. A nested SWAN model was validated then used to evaluate a range of initial wave conditions: significant wave heights (H s ) , peak periods (T p ) , and mean wave directions ( MWD) . Differences between wave height s in the presence and absence of WEC device s were assessed at locations in shore of the WEC array. The maximum decrease in wave height due to the WEC s was predicted to be approximately 6% at 5 m and 10 m water depths. Th is occurred for model initiation parameters of H s = 3 m (for 5 m water depth) or 4 m (10 m water depth) , T p = 10 s, and MWD = 330deg . Subsequently, bottom orbital velocities were found to decrease by about 6%.
The goal s of this study were to develop tools to quantitatively characterize environments where wave energy converter ( WEC ) devices may be installed and to assess e ffects on hydrodynamics and lo cal sediment transport. A large hypothetical WEC array was investigated using wave, hydrodynamic, and sediment transport models and site - specific average and storm conditions as input. The results indicated that there were significant changes in sediment s izes adjacent to and in the lee of the WEC array due to reduced wave energy. The circulation in the lee of the array was also altered; more intense onshore currents were generated in the lee of the WECs . In general, the storm case and the average case show ed the same qualitative patterns suggesting that these trends would be maintained throughout the year. The framework developed here can be used to design more efficient arrays while minimizing impacts on nearshore environmen ts.
A modified version of an indust ry standard wave modeling tool was evaluated, optimized, and utilized to investigate model sensitivity to input parameters a nd wave energy converter ( WEC ) array deployment scenarios. Wave propagation was investigated d ownstream of the WECs to evaluate overall near - and far - field effects of WEC arrays. The sensitivity study illustrate d that wave direction and WEC device type we r e most sensitive to the variation in the model parameters examined in this study . Generally, the changes in wave height we re the primary alteration caused by the presence of a WEC array. Specifically, W EC device type and subsequently their size directly re sult ed in wave height variations; however, it is important to utilize ongoing laboratory studies and future field tests to determine the most appropriate power matrix values for a particular WEC device and configuration in order to improve modeling results .
A modified version of an indust ry standard wave modeling tool, SNL - SWAN, was used to perform model simulations for hourly initial wave conditio ns measured during the month of October 2009. The model was run with an array of 50 wave energy converters (WECs) and compared with model runs without WECs. Maximum changes in H s were found in the lee of the WEC array along the angles of incident wave dire ction and minimal changes were found along the western side of the model domain due to wave shadowing by land. The largest wave height reductions occurred during observed typhoon conditions and resulted in 14% decreases in H s along the Santa Cruz shoreline . Shoreline reductions in H s were 5% during s outh swell wave conditions and negligible during average monthly wave conditions.
A n indust ry standard wave modeling tool was utilized to investigate model sensitivity to input parameters and wave energy converter ( WEC ) array deploym ent scenarios. Wave propagation was investigated d ownstream of the WECs to evaluate overall near - and far - field effects of WEC arrays. The sensitivity study illustrate d that b oth wave height and near - bottom orbital velocity we re subject to the largest pote ntial variations, each decreas ed in sensitivity as transmission coefficient increase d , as number and spacing of WEC devices decrease d , and as the deployment location move d offshore. Wave direction wa s affected consistently for all parameters and wave perio d was not affected (or negligibly affected) by varying model parameters or WEC configuration .
This guidance document provide s the reader with an overview of the key environmental considerations for a typical offshore wind coastal location and the tools to help guide the reader through a thoro ugh planning process. It will enable readers to identify the key coastal processes relevant to their offshore wind site and perform pertinent analysis to guide siting and layout design, with the goal of minimizing costs associated with planning, permitting , and long - ter m maintenance. The document highlight s site characterization and assessment techniques for evaluating spatial patterns of sediment dynamics in the vicinity of a wind farm under typical, extreme, and storm conditions. Finally, the document des cribe s the assimilation of all of this information into the conceptual site model (CSM) to aid the decision - making processes.
This document describes the marine hydrokinetic (MHK) input file and subroutines for the Sandia National Laboratories Environmental Fluid Dynamics Code (SNL-EFDC), which is a combined hydrodynamic, sediment transport, and water quality model based on the Environmental Fluid Dynamics Code (EFDC) developed by John Hamrick [1], formerly sponsored by the U.S. Environmental Protection Agency, and now maintained by Tetra Tech, Inc. SNL-EFDC has been previously enhanced with the incorporation of the SEDZLJ sediment dynamics model developed by Ziegler, Lick, and Jones [2-4]. SNL-EFDC has also been upgraded to more accurately simulate algae growth with specific application to optimizing biomass in an open-channel raceway for biofuels production [5]. A detailed description of the input file containing data describing the MHK device/array is provided, along with a description of the MHK FORTRAN routine. Both a theoretical description of the MHK dynamics as incorporated into SNL-EFDC and an explanation of the source code are provided. This user manual is meant to be used in conjunction with the original EFDC [6] and sediment dynamics SNL-EFDC manuals [7]. Through this document, the authors provide information for users who wish to model the effects of an MHK device (or array of devices) on a flow system with EFDC and who also seek a clear understanding of the source code, which is available from staff in the Water Power Technologies Department at Sandia National Laboratories, Albuquerque, New Mexico.