Danish Energy Association

<strong class="journal-contentHeaderColor">Abstract.</strong> The aerodynamic design of the aircraft of fly-gen Airborne Wind Energy Systems, named windplane here, is one of the main aspects determining their power production, but it is still a largely unexplored problem. To this end, an engineering model for the aerodynamics of the onboard turbines, the aerodynamics of the wing and their interactional aerodynamics is developed and coupled to a steady-state windplane model and a far-wake model. This comprehensive model is then used to design the windplane aerodynamics for a given wingspan. Initially, a design space exploration study reveals that placing the turbines at the wing tips and rotating them inboard down increases the power production compared to other locations and rotation direction. This is because the turbines' wake swirl reduces the wing induced drag, especially when they are placed at the wing tips. Moreover, conventional efficient airfoils are found to be optimal for windplanes. Later, NACA4421 airfoils are used for the design of the wing and the turbines, placed at the wing tips. The optimal trapezoidal wing, modeled with constant twist, has an aspect ratio of 5.1, a taper ratio of 0.60 and the onboard turbines operate at a design low tip speed ratio of 1.9 to increase the wake swirl. The results from the vortex models of the wing, the turbines, and their interaction is extensively compared with the lifting line, the vortex lattice method and the vortex particle method implemented in the well-established code DUST, finding very good agreement. Finally, the windplane is studied with DUST at different wing angles of attack and at different turbine tip speed ratios to characterize its behavior away from the design point.

The power performance of a wind turbine in complex terrain is studied by means of Large Eddy Simulations (LES). The simulations show that the turbine performance is significantly different compared to what should be expected from the available wind. The reason for this deviation is that the undisturbed flow field behind the turbine is non-homogeneous and therefore results in a very different wake development and induction than seen for a turbine in flat homogeneous terrain.

We investigate the characteristic of large-scale coherent motions over a large horizontal domain using the Dynamic Mode Decomposition (DMD) spectral analysis algorithm applied on measurements from two long-range pulsed lidars. We show the results and advantages of this methodology on six cases representative of three thermal stratification conditions at two heights relevant for wind energy: near-neutral, unstable and stable stratification at 50m and 200m above ground level. For these cases the DMD algorithm show three types of structures: streaks near the surface for near-neutral for neutral stratification, large-scale convective rolls for the unstable cases and sheet-like rotational patches for stable conditions. The DMD algorithm also shows the stationary effects of the terrain on the flow at 50m above ground level, within the atmospheric surface layer. The possibility of isolating terrain effects from coherent motions makes DMD attractive for studying complex atmospheric flow phenomena as well as to have more realistic input for wind farm flow simulations.

Future distribution grids are likely to shift away from a passive grid consuming power to an active grid with a high share of weather-dependent renewable generation. Distribution grid operations are greatly interlinked between different voltage levels and depend upon the fluctuating load demand. Thus it is imperative to study and analyze multi-voltage level distribution grids to understand the challenges and opportunities in a distribution grid with a high share of weather-dependent generation. In this research, an open-source multi-voltage level distribution grid model, named the DTU 7k-Bus Active Distribution Grid Model, is presented. The distribution grid model spans across three voltage levels and is modeled on geographical data for network topologies. The generation and load time-series provided with the model are simulated from weather data and derived from measurement data respectively. This work addresses key features of the model and highlights challenges due to the high share of renewables.

Abstract. Coastal environments, in particular heavily populated semi-enclosed marginal seas and coasts like the Baltic Sea region, are stongly affected by human activities. A multitude of human impacts, including climate change, affects the different compartments of the environment, and these effects interact with each other. As part of the Baltic Earth Assessment Reports (BEAR), we present an inventory and discussion of different human-induced factors and processes affecting the environment of the Baltic Sea region, and their interrelations. Some are naturally occurring and modified by human activities (i.e. climate change, coastal processes, hypoxia, acidification, submarine groundwater discharges, marine ecosystems, non-indigenous species, land use and land cover), some are completely human-induced (i.e. agriculture, aquaculture, fisheries, river regulations, offshore wind farms, shipping, chemical contamination, dumped warfare agents, marine litter and microplastics, tourism, coastal management), and they are all interrelated to different degrees. We present a general description and analysis of the state of knowledge on these interrelations. Our main insight is that climate change has an overarching, integrating impact on all of the other factors and can be interpreted as a background effect, which has different implications for the other factors. Impacts on the environment and the human sphere can be roughly allocated to anthropogenic drivers such as food production, energy production, transport, industry and economy. We conclude that a sound management and regulation of human activities must be implemented in order to use and keep the environments and ecosystems of the Baltic Sea region sustainably in a good shape. This must balance the human needs, which exert tremendous pressures on the systems, as humans are the overwhelming driving force for almost all changes we see. The findings from this inventory of available information and analysis of the different factors and their interactions in the Baltic Sea region can largely be transferred to other comparable marginal and coastal seas in the world.

Abstract. Advanced aeroelastically optimized tip extensions are among rotor innovation concepts which could contribute to higher performance and lower cost of wind turbines. A novel design optimization framework for wind turbine blade tip extensions, based on surrogate aeroelastic modeling is presented. An academic wind turbine is modelled in an aeroelastic code equipped with a near wake aerodynamic module, and tip extensions with complex shapes are parametrized using 11 design variables. The design space is explored via full aeroelastic simulations in extreme turbulence and a surrogate model is fitted to the data. Direct optimization is performed based on the surrogate model, seeking to maximize the power of the retrofitted turbine within the ultimate load constraints. The presented optimized design achieves a load neutral gain of up to 6 % in annual energy production. Its performance is further evaluated in detail by means of the near wake model used for the generation of the surrogate model, and compared with a higher fidelity aerodynamic module comprising a hybrid filament-particle-mesh vortex method with a lifting-line implementation. A good agreement between the solvers is obtained at low turbulence levels, while differences in predicted power and flap-wise blade root bending moment grow with increasing turbulence intensity.

Abstract. The outlined analysis validates the dynamic wake meandering (DWM) model based on loads and power production measured at an onshore wind farm with small turbine distances. Special focus is given to the performance of a version of the DWM model that was previously recalibrated at the site. The recalibration is based on measurements from a turbine nacelle-mounted lidar system. The different versions of the DWM model are compared to the commonly used Frandsen wake-added turbulence model. The results of the recalibrated wake model agree very well with the measurements, whereas the Frandsen model overestimates the loads drastically for short turbine distances. Furthermore, lidar measurements of the wind speed deficit as well as the wake meandering are incorporated in the DWM model definition in order to decrease the uncertainties.

Load carrying components of modern wind turbine blades are manufactured from composites, consisting of non-crimp fabrics infused with polymer resins. The effective stiffness of the resulting laminate is a combination of the properties of its building blocks i.e. fibers, and matrix as well as from the fabric texture imperfections e.g. fiber undulations. Moreover, ply inherent boundary conditions, e.g. the restriction of the Poisson deformation of the matrix imposed from the adjacent fibers, are determining the in-situ orthotropic performance. Towards modelling the in-plane stiffness of a unidirectional (UD) infused non-crimp fabric, a two-step modular procedure is proposed, accounting for the aforementioned parameters, based only on experimental data and analytical formulations. Initially, a micromechanical model is predicting the stiffness of the ideal UD ply i.e. disregarding fiber undulations. Subsequently, a plate model is generated based on the classical lamination theory, approximating the UD laminate as a multiaxial configuration of ideal UD sub-plies. Each sub-ply thickness and orientation is based on the fiber angle density distribution of dry fabrics and cured laminates. These are derived experimentally with an integrated optical camera system and Computer Tomography scans respectively. The theoretical laminate stiffness is correlating very well with standard and thick UD laminate quasi-static tests.

Perfect foresight hydroeconomic optimization models are tools to evaluate impacts of water infrastructure investments and policies considering complex system interlinkages. However, when assuming perfect foresight, management decisions are found assuming perfect knowledge of climate and runoff, which might bias the economic evaluation of investments and policies. We investigate the impacts of assuming perfect foresight by using Model Predictive Control (MPC) as an alternative. We apply MPC in WHAT-IF, a hydroeconomic optimization model, for two study cases: a synthetic setup inspired by the Nile River, and a large-scale investment problem on the Zambezi River Basin considering the water-energy-food nexus. We validate the MPC framework against Stochastic Dynamic Programming and observe more realistic modelled reservoir operation compared to perfect foresight, especially regarding anticipation of spills and droughts. We find that the impact of perfect foresight on total system benefits remains small (<2%). However, when evaluating investments and policies using with-without analysis, perfect foresight is found to overestimate or underestimate values of investments by more than 20% in some scenarios. As the importance of different effects varies between scenarios, it is difficult to find general, case-independent guidelines predicting whether perfect foresight is a reasonable assumption. However, we find that the uncertainty linked to climate change generally has more significant impacts than the assumption of perfect foresight. Hence, we recommend MPC to perform the economic evaluation of investments and policies, however, under high uncertainty of future climate, increased computational costs of MPC must be traded off against computational costs of exhaustive scenario exploration.