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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-e 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-e 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.

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. The research leading to this publication is part of the DTOceanPlus project which has received funding from the EuropeanUnion's Horizon 2020 research and innovation programme under grant agreement No 785921. Funding was also received from the European Community's Seventh Framework Programme for the DTOcean Project (grant agreement No. 608597). The contribution of Sandia National Laboratories was funded by the U.S. Department of Energy's Water Power Technologies Office. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government. The image of the RM3 device, in Fig. 7, was reproduced with the permission of Sandia National Laboratories

While some engineering fields have benefited from systematic design optimization studies, wave energy converters have yet to successfully incorporate such analyses into practical engineering workflows. The current iterative approach to wave energy converter design leads to sub-optimal solutions. This short paper presents an open-source MATLAB toolbox for performing design optimization studies on wave energy converters where power take-off behavior and realistic constraints can be easily included. This tool incorporates an adaptable control co-design approach, in that a constrained optimal controller is used to simulate device dynamics and populate an arbitrary objective function of the user’s choosing. A brief explanation of the tool’s structure and underlying theory is presented. To demonstrate the capabilities of the tool, verify its functionality, and begin to explore some basic wave energy converter design relationships, three conceptual case studies are presented. In particular, the importance of considering (and constraining) the magnitudes of device motion and forces in design optimization is shown.

Hydrokinetic tidal energy converter (TEC) technology is yet to become cost competitive with other renewable energy sources. Understanding the interaction between energy production and the costs incurred harvesting that energy may unlock the economic potential of this technology. Although hydrodynamic simulation of TEC arrays has matured over time, including demonstration of how small and large arrays affect the resource, integration of cost modelling is often limited. The advanced ocean energy array techno-economic modelling tool `DTOcean&rsquo, enables designers to calculate and improve the levelised cost of energy (LCOE) of an array through parametric simulation of the energy extraction, design of the electrical network, moorings and foundations, and simulation of the installation and lifetime operations and maintenance of the array. This work presents a verification of DTOcean&rsquo, s ability to simulate the techno-economic performance of TEC arrays by reproducing the hypothetical RM1 reference model, a semi-analytical model of a TEC array based in the Tacoma Narrows of Washington state, U.S.A. It is demonstrated that DTOcean can produce a reasonable estimate to the LCOE predicted by the reference model, giving (in Euro cents per kiloWatt hour) 36.69 &cent, /kWh against the reference model&rsquo, s 34.612 &cent, /kWh for 10 TECs, while for 50 TECs, DTOcean calculated 20.34 &cent, /kWh compared to 17.34 &cent, /kWh for the reference model.

Reduced-order models for mesoscale current energy converter (CEC) modeling allow for tractable computation times for investigations of array configurations on power performance and environmental effects to support design optimization. The CEC representation in these models take the form of actuator discs in codes such as SNL-Delft3D-CEC-FM treating the rotating CEC blades as momentum sinks. In the first-of-its-kind, whole-plant optimization software, DTOcean, the hydrodynamic modelling of CECs is reduced one step further by superimposing wake models based on normalized CFD simulations onto a set of pre-computed velocity fields, to provide power estimates. DTOcean is a new tool and the amount of verification and validation evidence gathered is presently limited. To gain additional confidence and industry buy-in to the software penetration, this study investigated a primary component of levelized cost of electricity (LCOE) calculation, annual energy production (AEP), through an analytic calculation of power using the results of an identical simulation in SNL-Delt3D-CEC-FM. Three configurations of an 8-turbine array are studied with DTOcean where two rows of 4-turbines are spaced (unstaggered) 5-, 10-, and 20-Diameters apart and the AEP was calculated; The energy calculation in SNL-Delft3D-CEC-FM were more computationally expensive for the mesoscale domain making the optimization of solely an arrays power production using the wake superposition method implemented DTOcean attractive. The codes however are complementary as SNL-Delft3D-CEC-FM simultaneously investigates environmental effects of varying array configurations while DTOcean considers all aspects of array costs through its lifetime to optimize LCOE from a whole-plant perspective.

As the technology of hydrokinetic tidal energy conversion looks to exploit smaller markets in the wider ‘blue economy’, innovation is still required to ensure cost competitiveness with other energy sources. A typical assumption of existing techno-economic models of tidal energy converter (TEC) arrays is that TECs positioned to minimise negative hydrodynamic interactions will maximise economic return. That the number of TECs within an array should be chosen to maximise the annual energy production, follows from this assumption. To examine the validity of these assertions for small, area-constrained arrays, a hypothetical model of the relationship of levelised cost of energy (LCOE) to the mean mechanical annual energy production (MMAEP) is developed. The model exhibits three classes of behaviour, determined by the rate of energy lost to interactions as TECs are added to an optimally positioned array; significantly, only one class has greatest MMAEP corresponding to lowest LCOE. To test this model, a contemporary optimisation algorithm is added to the advanced ocean energy techno-economic simulation tool ‘DTOcean’ and applied to arrays of TECs constrained by a 2 ha deployment area. It is shown that the hypothetical LCOE model accurately describes the DTOcean results up to and including 12 TECs deployed. At 13 TECs deployed, the level of TEC interaction increases dramatically, invalidating the hypothetical model. Notably, however, the LCOE is shown to reduce significantly by allowing negative interactions between TECs, reducing by 47.8% from the best non-interacting array. Thus, subject to an improved understanding of the relationship between the environment, TEC reliability and costs, the results indicate that allowing negative interactions between TECs may increase the economically extractable resource of small area-constrained tidal energy sites.