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- Fredriksson, Sam, 1966, et al.
(author)
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Modelling Deep Green tidal power plant using large eddy simulations and the actuator line method
- 2021
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In: Renewable Energy. - : Elsevier BV. - 0960-1481 .- 1879-0682. ; 179, s. 1140-1155
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Journal article (peer-reviewed)abstract
- The Deep Green technique for tidal power generation is suitable for moderate flows which is attractive since larger areas for tidal energy generation hereby can be used. It operates typically at mid-depth and can be seen as a "flying" kite with a turbine and generator attached underneath. It moves in a lying figure-eight path almost perpendicular to the tidal flow. Large eddy simulations and an adaption of the actuator line method (in order to describe arbitrary paths) are used to study the turbulent flow with and without Deep Green for a specific site. This methodology can in later studies be used for e.g. array analysis that include Deep Green interaction. It is seen that Deep Green creates a unique wake composed of two velocity deficit zones with increased velocity in each wake core. The flow has a tendency to be directed downwards which results in locally increased bottom shear. The persistence of flow disturbances of Deep Green can be scaled with its horizontal path width, D-y, with a velocity deficit of 5% at approximately 8-10D(y) downstream of the power plant. The turbulence intensity and power deficit are approximately two times the undisturbed value and 10%, respectively, at 10D(y). (C) 2021 The Authors. Published by Elsevier Ltd.
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| 2. |
- Lewis, Matt, et al.
(author)
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A standardised tidal-stream power curve, optimised for the global resource
- 2021
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In: Renewable Energy. - : Elsevier BV. - 0960-1481 .- 1879-0682. ; 170, s. 1308-1323
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Journal article (peer-reviewed)abstract
- Tidal-stream energy resource can be predicted deterministically, provided tidal harmonics and turbine-device characteristics are known. Many turbine designs exist, all having different characteristics (e.g. rated speed), which creates uncertainty in resource assessment or renewable energy system-design decision-making. A standardised normalised tidal-stream power-density curve was parameterised with data from 14 operational horizontal-axis turbines (e.g. mean cut-in speed was ∼30% of rated speed). Applying FES2014 global tidal data (1/16° gridded resolution) up to 25 km from the coast, allowed optimal turbine rated speed assessment. Maximum yield was found for turbine rated speed ∼97% of maximum current speed (maxU) using the 4 largest tidal constituents (M2, S2, K1 and O1) and ∼87% maxU for a “high yield” scenario (highest Capacity Factor in top 5% of yield cases); with little spatial variability found for either. Optimisation for firm power (highest Capacity Factor with power gaps less than 2 h), which is important for problematic or expensive energy-storage cases (e.g. off-grid), turbine rated speed of ∼56% maxU was found – but with spatial variability due to tidal form and maximum current speed. We find optimisation and convergent design is possible, and our standardised power curve should help future research in resource and environmental impact assessment.
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