2021
DOI: 10.1016/j.enconman.2021.114768
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Experimental investigation of the wake characteristics behind twin vertical axis turbines

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Cited by 28 publications
(19 citation statements)
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“…We note that the VAWT wind farm would still outperform the HAWT wind farm by 30% if the downwind direction was increased to 8D [49]. Furthermore, downwind spacing could be decreased to 5D if counter-rotation was to be employed [46]. This would automatically double ρ WF due to the pairs of turbines working at every node of the wind farm.…”
Section: Wind Farm Power Densitymentioning
confidence: 97%
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“…We note that the VAWT wind farm would still outperform the HAWT wind farm by 30% if the downwind direction was increased to 8D [49]. Furthermore, downwind spacing could be decreased to 5D if counter-rotation was to be employed [46]. This would automatically double ρ WF due to the pairs of turbines working at every node of the wind farm.…”
Section: Wind Farm Power Densitymentioning
confidence: 97%
“…Wind farm power density (ρ WF ) is a metric that quantifies how much power per square metre a wind farm produces. VAWTs can be placed next to each other in counter-rotation in the crosswind direction [46], whilst in the downwind direction a spacing between 4 to 8 diameters could be enough for the wake to recover above 80% [47][48][49]. In contrast HAWTs require a distance of 8 and 10 diameters in the cross-wind and in the downwind directions [50], respectively, to achieve C P, max .…”
Section: Wind Farm Power Densitymentioning
confidence: 99%
“…However, an i th -device operating behind a number of n turbines can be affected by the impact of n i−1 upstream turbines whose low-velocity wakes overlap enhancing the velocity deficit. In a time-averaged sense, this wake interaction can be estimated using linear and quadratic wake superposition methods, as widely used in literature for both HATs (Stansby and Stallard 2016;Niayifar and Porté-Agel 2016;Lanzilao and Meyers 2021) and VATs (Mueller et al 2021). Taking into account that each individual turbine generates a velocity deficit U i , this is adopted to calculate the local incident velocity for every turbine (U i 0 ) in Eqs.…”
Section: Wake Superpositionmentioning
confidence: 99%
“…Furthermore, irrespective of the standalone turbine efficiency, the rectangular cross-section of VAT rotors allows to deploy two devices close to one another which induces a flow acceleration between them Posa (2019) that can increase the individual performance up to 5% (Hezaveh et al 2018). Mueller et al (2021) observed that the rotational direction of twin-VAT systems induces larger changes to the wake dynamics than the turbine spacing, with a counter-rotating forwards motion providing the fastest wake recovery. These synergistic effects means that in VAT arrays reduce detrimental wake effects to achieve large power densities, about 10-20 times larger than those achievable by HATs, meaning that a higher power capacity can be deployed per unit of planform area (Dabiri 2011).…”
Section: Introductionmentioning
confidence: 98%
“…As it can be seen, the computed maximum displacement agrees reasonably well with the results reported by [22] for both tip immersions. On the other hand, the study of wake development is of importance to determine the optimal spacing between HAHTs in a hydrokinetic farm [11,[39][40][41]. Time-averaged velocity deficit profiles downstream of the simulated HAHT are shown in Figure 11a and Figure 11b for the deep tip and shallow tip immersions, respectively.…”
Section: Wake and Free Surface Interactionsmentioning
confidence: 99%