Abstract. Renewable power systems have to cope with highly variable generation. Increasing the spatial extent of an interconnected power transmission grid smooths the feed-in by exchange of excess energy over long distances and therefore supports renewable power integration. In this work, we investigate and quantify the balancing potential of a supergrid covering Europe, Africa and Asia. We use ten years of historical weather data to model the interplay of renewable generation and consumption and show that a pan-continental Afro-Eurasian supergrid can smooth renewable generation to a large extent and reduce the need for backup energy by around 50 %. In addition, we show that results for different weather years vary by up to approximately 50 %.

The calculation of the velocity deficit in the wake of individual wind turbines is a fundamental part of the wind farm analysis. A good approximation of the wake deficit behind a single wind turbine will improve the power estimation for downwind turbines. Large-eddy simulation (LES) is a research tool widely used in studying the velocity deficit and turbulence intensity in the wake. However, the computational cost of the LES prevents its application in wind farm performance analysis and control. Existing analytical wake models provide a fast estimation of the velocity deficit and the wake expansion rate downstream from the rotor. The Gaussian wake models use a Gaussian distribution to improve the prediction of the wake velocity deficit. With the number of analytical models available, an extensive evaluation of their performance under different flow parameters is needed. In this work, we simulate a wake of a single wind turbine using the LES code PALM (Parallelized LES Model) combined with an actuator disc model with rotation. We compare the computed flow field with the predictions made by Gaussian models and fit their parameters to obtain the best possible fit for the wake field data as computed by LES.

In this paper, the primary objective is to investigate flow structures in the wake of wind turbines based on applying a truncated Proper Orthogonal Decomposition (POD) approach. This scheme decomposes the three-dimensional velocity fields produced by the high-fidelity PArallelized LES Model (PALM) into a number of orthogonal spatial modes and time-dependent weighting coefficients. PALM has been combined with an actuator disk model with rotation to incorporate the effects of a turbine array. The time-dependent deterministic weights from applying the POD scheme are replaced by stochastic weights, estimated from two independent stochastic techniques that aim to account for unresolved small-scale features for a number of POD modes. We then reconstruct the flow field by a small number of stochastic modes to investigate how well the applied stochastic methodologies can reproduce the flow field compared to the original LES results.

The Parallelized Large-Eddy Model (PALM) and the Simulator for Wind Farm Applications (SOWFA) have been used to simulate the marine boundary layer flows under neutral stability condition. The present work aims to investigate the capability of the two models in reproducing the structure of turbulence in the offshore environment through comparative analysis with a focus on wind spectra and coherence. Wind spectra obtained from the two LES solvers agree well with the empirical spectral model near the surface but show lower turbulence intensity in the low frequency range above the surface layer. Both models also produce highly consistent estimates of coherence with different horizontal and vertical separations, which match well with Davenport and IEC coherence models at height of 180m and 140m respectively. As the height decreases, LES predicts lower vertical coherence compared with the IEC model and the fitted decay coefficient for Davenport model grows as the separation distance increases.