The Reference Model Project, supported by the U.S. Department of Energy, was developed to provide publically available technical and economic benchmarks for a variety of marine energy converters. The methodology to achieve these benchmarks is to develop public domain designs that incorporate power performance estimates, structural models, anchor and mooring designs, power conversion chain designs, and estimates of the operations and maintenance, installation, and environmental permitting required. The reference model designs are intended to be conservative, robust, and experimentally verified. The Backward Bent Duct Buoy (BBDB) presented in this paper is one of three wave energy conversion devices studied within the Reference Model Project. Comprehensive modeling of the BBDB in a Northern California climate has enabled a full levelized cost of energy (LCOE) analysis to be completed on this device.
Vertical axis wind turbines are receiving significant attention for offshore siting. In general, offshore wind offers proximity to large populations centers, a vast & more consistent wind resource, and a scale-up opportunity, to name a few beneficial characteristics. On the other hand, offshore wind suffers from high levelized cost of energy (LCOE) and in particular high balance of system (BoS) costs owing to accessibility challenges and limited project experience. To address these challenges associated with offshore wind, Sandia National Laboratories is researching large-scale (MW class) offshore floating vertical axis wind turbines (VAWTs). The motivation for this work is that floating VAWTs are a potential transformative technology solution to reduce offshore wind LCOE in deep-water locations. This paper explores performance and cost trade-offs within the design space for floating VAWTs between the configurations for the rotor and platform.
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.
Roberts, Jesse D.; Bull, Diana L.; Weber, Jochem W.; Costello, Ronan C.; Babarit, Aurelien B.; Nielsen, Kim N.; Bittencourt, Claudio B.; Kennedy, Ben K.
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 operation of Wave Energy Converter (WEC) devices can pose many challenging problems to the Water Power Community. A key research question is how to significantly improve the performance of these WEC devices through improving the control system design. This report summarizes an effort to analyze and improve the performance of WEC through the design and implementation of control systems. Controllers were selected to span the WEC control design space with the aim of building a more comprehensive understanding of different controller capabilities and requirements. To design and evaluate these control strategies, a model scale test-bed WEC was designed for both numerical and experimental testing (see Section 1.1). Seven control strategies have been developed and applied on a numerical model of the selected WEC. This model is capable of performing at a range of levels, spanning from a fully-linear realization to varying levels of nonlinearity. The details of this model and its ongoing development are described in Section 1.2.
This paper will introduce the Systems Engineering process utilized by the Structured Innovation team. Following the process this paper will present two key elements derived from the analysis of a successful Wave Energy Farm: the capabilities and the functions. The capabilities are the goals of a Wave Energy Farm as determined from a condensed list of the stakeholder needs. The functions are the activities or behaviors performed by the Wave Energy Farm in order to achieve the capabilities (i.e. the goals). At the framework level, both the functions and the capabilities remain independent of the design and these will be used to develop the list of requirements for a WEC in future work.
The fundamental interactions between waves, a floating rigid-body, and a moonpool that is selectively open to atmosphere or enclosed to purposefully induce pressure fluctuations are investigated. The moonpool hydrodynamic characteristics and the hydrodynamic coupling to the rigid-body are derived implicitly through reciprocity relations on an array of field points. By modeling the free surface of the moonpool in this manner, an explicit hydrodynamic coupling term is included in the equations of motion. This coupling results in the migration of the moonpool×s natural resonance frequency from the piston frequency to a new frequency when enclosed in a floating rigid-body. Two geometries that highlight distinct aspects of marine vessels and oscillating water column (OWC) renewable energy devices are analyzed to reveal the coupled natural resonance migration. The power performance of these two OWCs in regular waves is also investigated. The air chamber is enclosed and a three-dimensional, linear, frequency domain performance model that links the rigid-body to the moonpool through a linear resistive control strategy is detailed. An analytic expression for the optimal linear resistive control values in regular waves is presented.
A nonlinear three-dimensional time-domain performance model has been developed for a floating axisymmetric point absorbing WEC. This model employs a set of linear partial differential equations, in the form of a state-space model, to replace the convolution integrals needed to solve for radiation reaction. Linear time-domain results are verified against predictions from a frequency-domain model. Nonlinear timedomain predictions are compared back to frequency-domain and linear time-domain predictions to show the effects of some linearization assumptions. A simple resistive control strategy is applied throughout these scenarios.
A three dimensional time-domain model, based on Cummins equation, has been developed for an axisymmetric point absorbing wave energy converter (WEC) with an irregular cross section. This model incorporates a number of nonlinearities to accurately account for the dynamics of the device: hydrostatic restoring, motion constraints, saturation of the powertake-off force, and kinematic nonlinearities. Here, an interpolation model of the hydrostatic restoring reaction is developed and compared with a surface integral based method. The effects of these nonlinear hydrostatic models on device dynamics are explored by comparing predictions against those of a linear model. For the studied WEC, the interpolation model offers a large improvement over a linear model and is roughly two orders-of-magnitude less computationally expensive than the surface integral based method.
A new multi-year effort has been launched by the Department of Energy to validate the extent to which control strategies can increase the power produced by resonant wave energy conversion (WEC) devices. This paper describes the design of a WEC device to be employed by this program in the development and assessment of WEC control strategies. The operational principle of the device was selected to provide a test-bed for control strategies, in which a specific control strategies effectiveness and the parameters on which its effectiveness depends can be empirically determined. Numerical design studies were employed to determine the device geometry, so as to maximize testing opportunities in the Maneuvering and Seakeeping (MASK) Basin at the Naval Surface Warfare Centers David Taylor Model Basin. Details on the physical model including specific components and model fabrication methodologies are presented. Finally the quantities to be measured and the mechanisms of measurement are listed.
This report is an addendum to SAND2013-9040: Methodology for Design and Economic Analysis of Marine Energy Conversion (MEC) Technologies. This report describes an Oscillating Water Column Wave Energy Converter reference model design in a complementary manner to Reference Models 1-4 contained in the above report. In this report, a conceptual design for an Oscillating Water Column Wave Energy Converter (WEC) device appropriate for the modeled reference resource site was identified, and a detailed backward bent duct buoy (BBDB) device design was developed using a combination of numerical modeling tools and scaled physical models. Our team used the methodology in SAND2013-9040 for the economic analysis that included costs for designing, manufacturing, deploying, and operating commercial-scale MEC arrays, up to 100 devices. The methodology was applied to identify key cost drivers and to estimate levelized cost of energy (LCOE) for this RM6 Oscillating Water Column device in dollars per kilowatt-hour ($/kWh). Although many costs were difficult to estimate at this time due to the lack of operational experience, the main contribution of this work was to disseminate a detailed set of methodologies and models that allow for an initial cost analysis of this emerging technology. This project is sponsored by the U.S. Department of Energy's (DOE) Wind and Water Power Technologies Program Office (WWPTO), within the Office of Energy Efficiency & Renewable Energy (EERE). Sandia National Laboratories, the lead in this effort, collaborated with partners from National Laboratories, industry, and universities to design and test this reference model.
An oscillating water column (OWC) wave energy converter is a structure with an opening to the ocean below the free surface, i.e. a structure with a moonpool. Two structural models for a non-axisymmetric terminator design OWC, the Backward Bent Duct Buoy (BBDB) are discussed in this report. The results of this structural model design study are intended to inform experiments and modeling underway in support of the U.S. Department of Energy (DOE) initiated Reference Model Project (RMP). A detailed design developed by Re Vision Consulting used stiffeners and girders to stabilize the structure against the hydrostatic loads experienced by a BBDB device. Additional support plates were added to this structure to account for loads arising from the mooring line attachment points. A simplified structure was designed in a modular fashion. This simplified design allows easy alterations to the buoyancy chambers and uncomplicated analysis of resulting changes in buoyancy.
Experiments were conducted with a Backward Bent Duct Buoy (BBDB) oscillating water column wave energy conversion device with a scaling factor of 50 at HMRC at University College Cork, Ireland. Results were compared to numerical performance models. This work experimentally verified the migration of the natural resonance location of the water column due to hydrodynamic coupling for a floating non- axisymmetric device without a power conversion chain PCC present. In addition, the experimental results verified the performance model with a PCC of the same non- axisymmetric device when both floating and grounded.
To reduce the price of the reference Backward Bent Duct Buoy (BBDB), a study was done analyzing the effects of reducing the mooring line length, and a new mooring design was developed. It was found that the overall length of the mooring lines could be reduced by 1290 meters, allowing a significant price reduction of the system. In this paper, we will first give a description of the model and the storm environment it will be subject to. We will then give a recommendation for the new mooring system, followed by a discussion of the severe weather simulation results, and an analysis of the conservative and aggressive aspects of the design.
Smith, Christopher S.; Bull, Diana L.; Willits, Steven M.; Fontaine, Arnold A.
This Technical Report presents work completed by The Applied Research Laboratory at The Pennsylvania State University, in conjunction with Sandia National Labs, on the optimization of the power conversion chain (PCC) design to maximize the Average Annual Electric Power (AAEP) output of an Oscillating Water Column (OWC) device. The design consists of two independent stages. First, the design of a floating OWC, a Backward Bent Duct Buoy (BBDB), and second the design of the PCC. The pneumatic power output of the BBDB in random waves is optimized through the use of a hydrodynamically coupled, linear, frequency-domain, performance model that links the oscillating structure to internal air-pressure fluctuations. The PCC optimization is centered on the selection and sizing of a Wells Turbine and electric power generation equipment. The optimization of the PCC involves the following variables: the type of Wells Turbine (fixed or variable pitched, with and without guide vanes), the radius of the turbine, the optimal vent pressure, the sizing of the power electronics, and number of turbines. Also included in this Technical Report are further details on how rotor thrust and torque are estimated, along with further details on the type of variable frequency drive selected.