Search

The modes delivered by proper orthogonal decomposition (POD) are uncorrelated as per definition; but interestingly, they are not necessarily independent in terms of spatio-temporal flow-pattern dynamics. For instance, periodic structures that travel as waves through a series of snapshots often consist of pairs of modes with harmonic functions shifted 90 degree in phase and/or a spatial offset by a quarter of the spatial wave length of the convective flow pattern. Identification of such pairs, however, largely builds upon experience, visual inspection and/or the analysis of the reconstructed coefficients in cyclograms (Lissajous figures). This effort becomes even more challenging if measurement noise or other spurious information contaminates the raw data under consideration. One possibility to automatically pair corresponding patterns with common POD algorithms is the immediate application of the POD method to complex data (see Pfeffer et al., 1990). As outlined by Horel (1984), the Hilbert transform is a well-known and straight forward means to obtain the required extension of the original signal with an appropriate 90 degrees phase shift, which is independent of the fundamental frequencies. The complex extension of the original (real) signal Xi and its (discrete) Hilbert transform HT{Xi} as the imaginary part Xi +iHT{Xi} with the imaginary unit i is commonly known as the so-called analytical signal.

Vertical-axis wind turbines (VAWTs) are being reconsidered as a complementary technology to the more widely used horizontal-axis wind turbines (HAWTs) due to their unique suitability for offshore deployments. In addition, field experiments have confirmed that vertical-axis wind turbines can interact synergistically to enhance the total power production when placed in close proximity. Here, we use an actuator line model in a large-eddy simulation to test novel VAWT farm configurations that exploit these synergistic interactions. We first design clusters with three turbines each that preserve the omni-directionality of vertical-axis wind turbines, and optimize the distance between the clustered turbines. We then configure farms based on clusters, rather than individual turbines. The simulations confirm that vertical-axis wind turbines have a positive influence on each other when packed in well-designed clusters: such configurations increase the power generation of a single turbine by about 10 percent. In addition, the cluster designs allow for closer turbine spacing resulting in about three times the number of turbines for a given land area compared to conventional configurations. Therefore, both the turbine and wind-farm efficiencies are improved, leading to a significant increase in the density of power production per unit land area.

Experimental results from three different full scale arrays of vertical-axis wind turbines (VAWTs) under natural wind conditions are presented. The wind velocities throughout the turbine arrays are measured using a portable meteorological tower with seven, vertically staggered, three-component ultrasonic anemometers. The power output of each turbine is recorded simultaneously. The comparison between the horizontal and vertical energy transport for the different turbine array sizes shows the importance of vertical transport for large array configurations. Quadrant-hole analysis is employed to gain a better understanding of the vertical energy transport at the top of the VAWT arrays. The results show a striking similarity between the flows in the VAWT arrays and the adjustment region of canopies. Namely, an increase in ejections and sweeps and decrease in inward and outward interactions occur inside the turbine array. Ejections are the strongest contributor, which is in agreement with the literature on evolving and sparse canopy flows. The influence of the turbine array size on the power output of the downstream turbines is examined by comparing a streamwise row of four single turbines with square arrays of nine turbine pairs. The results suggest that a new boundary layer forms on top of the larger turbine arrays as the flow adjusts to the new roughness length. This increases the turbulent energy transport over the whole planform area of the turbine array. By contrast, for the four single turbines, the vertical energy transport due to turbulent fluctuations is only increased in the near wake of the turbines. These findings add to the knowledge of energy transport in turbine arrays and therefore the optimization of the turbine spacing in wind farms.

Increased power production is observed in downstream vertical-axis wind turbines (VAWTs) when positioned offset from the wake of upstream turbines. This effect is found to exist in both laboratory and field environments with pairs of co- and counter-rotating turbines, respectively. It is hypothesized that the observed production enhancement is due to flow acceleration adjacent to the upstream turbine due to bluff body blockage, which would increase the incident freestream velocity on appropriately positioned downstream turbines. A low-order model combining potential flow and actuator disk theory captures this effect. Additional laboratory and field experiments further validate the predictive capabilities of the model. Finally, an evolutionary algorithm reveals patterns in optimized VAWT arrays with various numbers of turbines. A “truss-shaped” array is identified as a promising configuration to optimize energy extraction in VAWT wind farms by maximizing the performance enhancement of downstream turbines.