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DOE OSTI2016

Marine Hydrokinetic Energy Site Identification and Ranking Methodology Part II: Tidal Energy

Marine hydrokinetic energy is a promising and growing piece of the renewable energy sector that offers high predictability and additional energy sources for a diversified energy economy. This report investigates the market opportunities for tidal energy along the U.S. coastlines. It is part one of a two-part investigation into the United States' two largest marine hydrokinetic resources (wave and tidal). Tidal energy technology is still an emerging form of renewable energy for which large-scale grid-connected project costs are currently poorly defined. Ideally, device designers would like to know the resource conditions at economical project sites so they can optimize device designs. On the other hand, project developers need detailed device cost data to identify sites where projects are economical. That is, device design and siting are, to some extent, a coupled problem. This work describes a methodology for identifying likely deployment locations based on a set of criteria that tidal energy experts in industry, academia, and national laboratories agree are likely to be important factors for all technology types. Several factors that will affect tidal project costs and siting have not been considered here -- including permitting constraints, conflicting use, seasonal resource variability, extreme event likelihood, and distance to ports -- because consistent data are unavailable or technology-independent scoring could not be identified. As the industry continues to mature and converge around a subset of device archetypes with well-defined costs, more precise investigations of project siting that include these factors will be possible. For now, these results provide a high-level guide pointing to the regions where markets and resource will one day support commercial tidal energy projects.

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DOE OSTI2016

University of Washington/ Northwest National Marine Renewable Energy Center Tidal Current Technology Test Protocol, Instrumentation, Design Code, and Oceanographic Modeling Collaboration: Cooperative Research and Development Final Report, CRADA Number CRD-11-452

The University of Washington (UW) - Northwest National Marine Renewable Energy Center (UW-NNMREC) and the National Renewable Energy Laboratory (NREL) will collaborate to advance research and development (R&D) of Marine Hydrokinetic (MHK) renewable energy technology, specifically renewable energy captured from ocean tidal currents. UW-NNMREC is endeavoring to establish infrastructure, capabilities and tools to support in-water testing of marine energy technology. NREL is leveraging its experience and capabilities in field testing of wind systems to develop protocols and instrumentation to advance field testing of MHK systems. Under this work, UW-NNMREC and NREL will work together to develop a common instrumentation system and testing methodologies, standards and protocols. UW-NNMREC is also establishing simulation capabilities for MHK turbine and turbine arrays. NREL has extensive experience in wind turbine array modeling and is developing several computer based numerical simulation capabilities for MHK systems. Under this CRADA, UW-NNMREC and NREL will work together to augment single device and array modeling codes. As part of this effort UW NNMREC will also work with NREL to run simulations on NREL's high performance computer system.

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DOE OSTI2017

WindFloat Pacific Project, Final Scientific and Technical Report

PPI’s WindFloat Pacific project (WFP) was an up to 30 MW floating offshore wind demonstration project proposed off the Coast of Oregon. The project was to be sited approximately 18 miles due west of Coos Bay, in over 1000 ft. of water, and is the first floating offshore wind array proposed in the United States, and the first offshore wind project of any kind proposed off the West Coast. PPI’s WindFloat, a semi-submersible foundation designed for high-capacity (6MW+) offshore wind turbines, is at the heart of the proposed project, and enables access to the world class wind resource at the project site and, equally, to other deep water, high wind resource areas around the country.

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DOE OSTI2017

State estimation for wave energy converters

This report gives a brief discussion and examples on the topic of state estimation for wave energy converters (WECs). These methods are intended for use to enable real-time closed loop control of WECs.

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DOE OSTI2017

Technology Performance Level Assessment Methodology.

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.

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DOE OSTI2017

Technical Submission Form: Technical Specification of a Wave Energy Farm.

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.

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DOE OSTI2017

Systems Engineering Applied to the Development of a Wave Energy Farm.

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.

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DOE OSTI2018

Automatic optical detection and classification of marine animals around MHK converters using machine vision

Optical systems provide valuable information for evaluating interactions and associations between organisms and MHK energy converters and for capturing potentially rare encounters between marine organisms and MHK device. The deluge of optical data from cabled monitoring packages makes expert review time-consuming and expensive. We propose algorithms and a processing framework to automatically extract events of interest from underwater video. The open-source software framework consists of background subtraction, filtering, feature extraction and hierarchical classification algorithms. This principle classification pipeline was validated on real-world data collected with an experimental underwater monitoring package. An event detection rate of 100% was achieved using robust principal components analysis (RPCA), Fourier feature extraction and a support vector machine (SVM) binary classifier. The detected events were then further classified into more complex classes – algae | invertebrate | vertebrate, one species | multiple species of fish, and interest rank. Greater than 80% accuracy was achieved using a combination of machine learning techniques.

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DOE OSTI2018

2017 Marine Hydrokinetic Instrumentation Workshop Report

The third Marine Hydrokinetic Instrumentation Workshop was held at Florida Atlantic University's Sea Tech Campus in Dania Beach, Florida, from February 28 to March 1, 2017. The workshop brought together 37 experts in marine energy measurement, testing, and technology development to present and discuss the instrumentation and data-processing needs of the marine energy industry. The workshop was comprised of a plenary session followed by two focused breakout sessions. The half-day plenary session reviewed findings from prior instrumentation workshops, presented research activities that aim to fill previously identified gaps, and had industry experts present the state of the marine energy measurement technologies. This report provides further detail on the workshop, objectives, and findings.

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DOE OSTI2018

Marine Mammal Behavioral Response to Tidal Turbine Sound

The sound emitted by tidal turbines overlaps with the generalized hearing ranges for marine mammals and may, consequently, affect marine mammal behavior. Because of the strong environmental protections for marine mammals, these effects are of interest to resource agencies and project developers. The primary goal of this project is to improve the understanding of how sound emitted by tidal turbines may affect marine mammal behavior, with the intent that such understanding may allow this environmental risk to be “retired” for initial demonstrations and arrays. A secondary project goal is to evaluate the efficacy of marine mammal observations from a shore-based vantage point as a method to detect change as a consequence of marine energy stressors. Three, two-week trials were conducted across spring, summer and autumn of 2017 during which vantage-point observations of marine mammals were made from land. We refer to these two-week periods as ‘trials’ as they represent different periods of field data collection. These observations consisted of scan samples every 10 minutes with a set of binoculars and a DSLR camera. When pinnipeds were sighted, still images were taken. When harbor porpoise were sighted, focal follows using video were initiated. These data were later analyzed to estimate the location of animals sighted using photogrammetric techniques. For approximately half of each trial period, a boat was moored in the study area from which an underwater projector was used to play back tidal turbine sounds at a broadband source level of 158 dB re µPa @ 1 m. The other half of each trial period had no playbacks and was used as a control period. During the control and playback periods, ancillary data were collected in the study area near the sea floor (ambient noise, tidal velocity, and porpoise clicks) while weather and vessel tracks were recorded near the vantage-point station. Harbor seals did not show a significant response to the simulated turbine noise, nor did harbor porpoise change their closest point of approach or change the direction/deviation of the paths during periods when the playback was occurring. While porpoise sightings and porpoise acoustic detections were significantly reduced during playback periods in the first two trials, the number of detections during the playback periods increased during the third trial. Similarly, the calculated distance from porpoises to the playback location suggests that harbor porpoises avoided an area around the playback location of approximately 300 m during Trial 1, which decreased to approximately 100 m in Trial 2, and disappeared in Trial 3. This could be an indication of habituation or increased tolerance, either to the playback sound or the vessel presence. Our finding of no significant effect of turbine noise on harbor seals contrast with the findings in a previous study by Hastie et al. (2017) conducted in United Kingdom waters. However, due to substantive differences in source levels and propagation loss, seals in our study would need to have been within 10 m of the playback location to experience similar received levels to those in the Hastie et al. study. Consequently, the two studies may actually be in agreement. Our findings of significant effect of turbine noise on harbor porpoise are in line with previous studies suggesting the harbor porpoise are sensitive to noise. However, we note that, due to cost and logistical constraints, the playback vessel was only mooring during the playback periods. Consequently, we cannot definitively ascribe the changes in porpoise behavior to the simulated turbine noise, playback vessel presence, or a combination of both factors. This methodological limitation and other lessons learned are discussed to benefit future studies that explore the effects of acoustic stressors on marine mammals.

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DOE OSTI2018

A comparative study on wave prediction for WECs

The idea of acausality for control of a wave energy converter (WEC) is a concept that has been popular since the birth of modern wave energy research in the 1970s. This concept has led to considerable research into wave prediction and feedforward WEC control algorithms. However, the findings in this report mostly negate the need for wave prediction to improve WEC energy absorption, and favor instead feedback driven control strategies. Feedback control is shown to provide performance that rivals a prediction-based controller, which has been unrealistically assumed to have perfect prediction. It is well known in classical control engineering that perfect knowledge of past and future events will always lead to higher performing systems. However, it is also well known that the underlying system must be well-designed; control cannot fix a bad design. Additionally, one must consider the practical application of a control design, which relies on measurements and actuation systems. There are major implications to cost and reliability when relying on remote sensors requiring real-time data-streaming (e.g., remote wave buoys). This report shows that for a well-designed WEC, in which closed loop dynamics is considered since early stages of design, a suboptimal controller using no prediction can achieve more than 90% of the theoretical maximum. A predictionless feedback resonating (FBR) controller performs within 0.1% percent of a controller with perfect future knowledge (something which is not practically attainable). Given the major challenges with accurate and robust wave prediction, this result provides a major argument and incentive for utilizing feedback for WEC control. Implementation of these feedback strategies is readily attainable, while the strategy requiring perfect wave prediction will demand an unknown number of additional years to research and develop, all in the service of a marginal 1% benefit.

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DOE OSTI2018

A comparative study on wave prediction for WECs

The idea of acausality for control of a wave energy converter (WEC) is a concept that has been popular since the birth of modern wave energy research in the 1970s. This concept has led to considerable research into wave prediction and feedforward WEC control algorithms. However, the findings in this report mostly negate the need for wave prediction to improve WEC energy absorption, and favor instead feedback driven control strategies. Feedback control is shown to provide performance that rivals a prediction-based controller, which has been unrealistically assumed to have perfect prediction.

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DOE OSTI2018

Florida Atlantic University-Southeast National Marine Renewable Energy Center: Cooperative Research and Development Final Report, CRADA Number CRD-10-377

Florida Atlantic University's Southeast National Marine Renewable Energy Center (SNMREC) and the National Renewable Energy Laboratory's National Wind Technology Center (NWTC) will collaborate to advance research and development (R&D) of marine and hydrokinetic (MHK) renewable energy technology, specifically renewable energy captured from oceanic currents such as the Florida Current. SNMREC is endeavoring to establish infrastructure and capabilities that will form the base of a marine energy technology testing center focused on energy production from open-ocean currents and ocean thermal resources. As part of this effort, SNMREC is also aiming to create technology development tools and an experimental hydrokinetic device to operate in the Florida Current. NWTC has experience in developing testing infrastructure and modeling tools. SNMREC has expertise in ocean engineering and operations, a large inventory of ocean instrumentation, and ready access to the ocean. NWTC and SNMREC will therefore work together on numerical modeling, technology design review and testing, the development of standardized MHK instrumentation, field testing, establishing testing protocols, and moving the SNMREC testing capability through A2LA accreditation.

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DOE OSTI2018

Data Transferability and Collection Consistency in Marine Renewable Energy

Concerns about the potential effects of tidal turbines and wave energy devices on the marine environment continue to slow siting and permitting/consenting of single devices and arrays worldwide. While research studies and early results from post-installation monitoring over the past decade have informed interactions between marine renewable energy (MRE) devices, marine animals, and habitats, regulators still demonstrate considerable reluctance to accelerate the permitting/consenting process for devices and arrays. Furthermore, the MRE industry is struggling with the high costs of baseline assessments and post-installation monitoring, as well as long timelines for obtaining permits, which leads to uncertainty and risk related to project financing. Regulators require assessment and monitoring information to allow them to carry out the necessary analyses to describe, permit/consent, and manage the environmental risks associated with new MRE technologies and new uses of ocean space. One way to reduce risks to the industry and the environment and to allow for acceleration of the permitting/consenting process could be to transfer learning, analyses, and data sets from one country to another, among projects, and across jurisdictional boundaries. In addition, data are collected around early-stage MRE devices using many different methods, instruments, and measurement scales. If similar parameters and accessible methods of data collection were used for baseline assessments and post-installation monitoring around all early-stage devices and MRE developments, the results would be more readily comparable. This comparability would lead to a decrease in scientific uncertainty and support a common understanding of the risk of MRE devices to the marine environment. This in turn would facilitate more efficient and shorter permitting/consenting processes, which would decrease the financial risk for MRE project development. As a means of addressing the concept of transferring data (information, learning, analyses, and data sets) among projects and collecting data consistently, Annex IV has developed a data transferability process that has been socialized with the MRE community, which includes regulators, industry, developers, consultants, and researchers. The data transferability process consists of five components: 1. A Data Transferability Framework brings together data sets in an organized fashion, compares the applicability of each data set for use on other projects, and guides the process of data transfer 2. A Data Collection Consistency Table provides preferred measurement methods or processes, reporting units, and the most common methods of analysis or interpretation and use of data 3. A Monitoring Data Sets Discoverability Matrix allows a practitioner to discover data sets based on the approach presented in the Framework 4. Best Management Practices (BMPs) include five BMPs related to data transferability and collection consistency 5. An Implementation Plan presents an approach for implementing and applying the data transferability process. This report documents the background and development of the data transferability process and associated components and summarizes the next steps needed to successfully implement and apply the data transferability process.

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DOE OSTI2019

Storm Surge Modeling in Puget Sound

In this study, a storm surge model of the Salish Sea was developed to simulate storm surge in Puget Sound using the unstructured-grid, finite-volume community ocean model (FVCOM). The model was based on Pacific Northwest National Laboratory’s existing Puget Sound hydrodynamic model that has been validated extensively in previous studies. To identify representative historical storm events, a systematic approach was developed based on the non-tidal residual (NTR) method. A total of 34 storm surge events between 1980 and 2016 were identified and simulated. To accurately simulate storm surge inside Puget Sound, the model was driven by reanalyzed Climate Forecast System Reanalysis meteorological forcing and observed water levels at the entrance of Strait of Juan de Fuca and southern entrance of Johnstone Strait. Model results for total water level, storm surge, and currents were compared with field measurements. A series of error statistics parameters were also calculated to quantify the model’s skills in simulating storm surge in the Salish Sea. Error statistics of model performance metrics demonstrated that the Salish Sea storm surge model was able to simulate storm surge inside Puget Sound with high accuracy. Storm surge propagation into Puget Sound is a nonlinear process that cannot be simply determined by a static approach for the entire domain. The maximum NTR distribution inside Puget Sound suggests that storm surge tends to be amplified in several sub-basins and inlets of the Puget Sound, such as Bellingham Bay, Hood Canal, south Puget Sound, and the multi-inlet basin behind Agate and Rich Passages. Therefore, future study is necessary to further quantify the storm surge level in these high-risk areas through field measurements and refined model simulations.

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DOE OSTI2019

High-Resolution Regional Wave Hindcast for Hawaii

This report summarizes modeling efforts for hindcasting of wave climate within the exclusive economic zone (EEZ) around the state of Hawaii. Specifically, the report provides detailed description of model mesh development, sensitivity analysis of the configuration of model parameters, data used for model forcing and validation, model skill assessment, and model outputs for resource characterization. The unstructured, nested-grid modeling approach incorporates a regional high-resolution SWAN (Simulating WAves Nearshore) model within the global-regional WAVEWATCH III® (WW3) wave model. The models were configured to comply with the International Electrotechnical Commission (IEC) Technical Standards for wave energy resource characterization. The SWAN model domain covers the entire EEZ with a spatial resolution of approximately 300 m in the nearshore region. Two levels of WW3 nested grids, from 0.5 arc-degree at global to 7.5 arc-minute at regional scale, were used to provide boundary conditions that drive the high-resolution nearshore SWAN model. The WW3 and SWAN models were forced by 0.5 arc-degree Climate Forecast System Reanalysis wind and 5 km regional Weather Research and Forecasting wind, respectively. Wave resource and bulk wave parameters were simulated for a 32-year period from 1979 to 2010, and were subsequently validated using wave buoy data within the model domain. Model performance was evaluated using a set of error statistics. Overall, the model shows good skills in reproducing the wave climate in the Hawaii EEZ in both spatial and temporal domains. Comparisons of time series and scatter plots for the six IEC resource parameters and the associated error statistics tables, and horizontal two-dimensional plots of annually averaged and monthly averaged IEC parameters are provided.

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DOE OSTI2019

A summary of the Advanced WEC Dynamics and Control project

This report serves as a comprehensive summary of the work completed by the "Advanced WEC Dynamics and Controls projecr during the period of 2013-2019. This project was first envisioned to simply consider the question of designing a controller for wave energy converters (WECs), without a complete recognition of the broader considerations that such a task must necessarily examine. This document describes both the evolution of the project scope and the key findings produced. The basic goal of the project has been to deliver tractable methodologies and work flows that WEC designers can use to improve the performance of their machines. Engineering solutions, which may offer 80% of the impact, but require 20% of the effort compared to a perfect result (which may be many years of development down the road) were preferred. With this doctrine, the work of the project often involved translating existing methods that have been successfully developed and applied for other fields, into the application area of wave energy.

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DOE OSTI2017

WEC Extreme Conditions Modeling Sandia Summer Intern 2017 Report

This report contains work completed by a group of student interns during the summer of 2017. Under the guidance of Ryan Coe, Aubrey Eckert-Gallup, and Nevin Martin, a series of interrelated projects were completed on topics relating to extreme response and survival analysis of wave energy converters (WECs). Jarred Canning studied long-term design response analysis methods for WECs. Sam Edwards studied how variation in the selection of an environmental contour affects the characterization of WEC response in extreme conditions. Sam also led the integration of various components of this report and overall editing. Tyler Esterly produced a catalog of analyses for different ocean sites. Bibiana Seng studied clustering analyses for comparing the wave environments of different ocean sites. Lori Smith performed a comparison between analyses conducted using spectral wave data and analyses using deterministic time-domain wave data. William ("Zach") Stuart studied the sensitivity and convergence of environmental contour methods.

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