The offshore wind energy market is highly dynamic and one of the major challenges is to become more cost competitive against other sources of energy. The support structure of an offshore wind turbine shows a high potential for further cost reduction. Jules Dock is investigating in the replacement of a steel tower on a monopile foundation by a Glass Fiber Reinforced Plastic (GFRP) tower, which has a higher specific strength and better corrosion resistance compared to steel. This would enable lower transportation and installation costs and a potentially longer lifetime. Currently Jules Dock assesses the feasibility of a GFRP tower versus a steel tower using an aero-elastic simulation tool. However, such a tool is computationally demanding and requires detailed turbine data, which are often not available in a preliminary design phase. For this reason, a research project has been set-up to develop a parametric design model which can effectively be used without detailed turbine data and aero-elastic simulations, to identify the design driving constraints for preliminary designs and mass optimization purposes. The parametric design model analyses the natural frequency constraint and Ultimate Limit State (ULS). The natural frequency of the support structure is intended to be in the soft-soft region, which will result in the lowest mass possible as has been found in previous research. The natural frequency of the support structure is analyzed with a finite beam element model, in which the Rotor Nacelle Assembly (RNA) is modelled as a point mass. The interaction with soil is also included using a three spring model. For the ULS, the yield and buckling capacity of the support structure are analyzed. For the steel monopile and transition piece, dedicated design standards have been used. For the composite tower, however, these design standards are not existing and therefore analytical solutions from composite tube applications have been used and verified for this purpose. FEM analysis showed that the yield capacity can be determined exactly. The buckling capacity approximation in the parametric design model showed conservative results compared to a dedicated buckling analysis tool. In the parametric design model the maximum loading for the ULS constraints has been analyzed using a quasi-static load analysis method which includes turbulence and dynamic wave loading effects. This method has been compared with the time-domain simulation tool Phatas, which is integrated in Focus6. This comparison showed that also the tower top bending moment should have been included. If this is taken into account, the integrated load analysis method appears to approach the maximum loading for a very stiff tower quite accurately compared with the time-domain simulations. For flexible towers, however, the loads are less accurately approached, since dynamic interactions between wind and wave loading have appeared to be relevant, especially for load cases with a wave excitation frequency close to the natural frequency of the support structure. In the quasi-static load analysis method these dynamic effects are only taken into account for the submerged part of the support structure, but the time-domain simulations have shown that these effects will increase the maximum loading on the support structure above water level as well. For mass optimization and identification of the design driving constraints of this support structure, a genetic algorithm has been developed. Several optimization runs have been made, resulting in multiple feasible solutions with only small differences in support structure mass. While the buckling constraint drives the design of the monopile, transition piece and top of the tower, the lower part of the tower is design driven by the yield constraint. It has been concluded that the loading analysis method in the developed parametric design model should include the tower top bending moment, since this leads to a mass increase of up to 20% of the support structure mass. Next to that, it has been observed that the optimization algorithm tends to converge to solutions with a natural frequency to be as low as possible, such that the dynamic amplification of the wave loading is minimized. For these solutions, the loading analysis method in the parametric design model may have underestimated the maximum loading on the flexible support structure. This needs to be further investigated.

The main purpose of this project was the creation of a tool, based on the research performed by Scheldbergen [25] and Roscher [24], capable of performing Finite Element Analysis (FEA) on a Horizontal Axis Wind Turbine (HAWT) blade and minimize its weight by altering the various thicknesses locally, always satisfying a number of structural constraints. The first goal was the development of a geometry creation algorithm based on a Non Uniform Rational Basis Splines (NURBS) algorithm developed by Ferede [14], with a more complex spanwise/chordwise discretization technique in order to more accurately design a discretized HAWT blade. The second goal was the alteration of the material creation algorithm developed by Scheldbergen [25], so that different stacks at various blade locations can be assigned. Moreover, the aerodynamic loads generation algorithm of Scheldbergen [25] was modified to apply for different airfoils along the blade span. Also, Blade Element Momentum (BEM) theory was used for the calculation of the aerodynamic loads and the software XFOIL was used for the aerodynamic analysis of the airfoils (pressure distribution on the airfoil at corresponding angles of attack and Re numbers). An initial HAWT blade design was created, matching the SANDIA 5 MW wind turbine blade [23] geometry and materials. Furthermore, the apwise/edgewise stiffness, moments of inertia, mass and mode shapes were also validated. Additionally, the SANDIA blade was analyzed in DNV GL Bladed in order to validate the aerodynamic loads on the blade. Following, the tool was designed to process the geometry, the materials and the gravitational/ centrifugal/aerodynamic loads of the blade and translate them to an input for the FEA software MSC Nastran for Linear Static Analysis (SOL 101), Buckling Analysis (SOL 105) and Modal Analysis (SOL 103). The post processing algorithm of Scheldbergen [25] was modified to apply for a HAWT (instead of a VAWT), transforming the results of the FEA analysis into optimization constraints (ultimate load, buckling, tip deflection and fatigue). The final part of the algorithm involved the minimization of the blade's mass by altering the thickness at various locations, using the MATLAB function fmincon. Concluding, a case study of a smart rotor blade equipped with trailing edge ap (TRF) was examined. A _ 2 flap was used at 90-100% of the chord and 78-98% of the span. Two kinds of optimization were performed for the HAWT and smart rotor scenarios; one that included ultimate stress, tip deflection and fatigue constraints (UL-TD-FA) and one that also included buckling constraints (UL-BU-TD-FA). It was found that the buckling constraint was the limiting factor of the optimization and the fatigue constraint was the least dominant. The initial design of the smart rotor blade showed a 16.5% decrease of the maximum fatigue damage and a 2% decrease in the maximum stress. The optimized smart rotor blade mass was 0.5 % lower in the UL-TD-FA scenario and 2.5% in the UL-BU-TD-FA scenario compared to the HAWT blade. The tool created is capable of creating a flexible and fairly accurate representation of a HAWT and smart rotor blade. It also provides the ability to structurally analyze the blade under the most significant structural criteria and minimize the blade's weight under specific loading conditions. The tool constitutes a good starting point for more detailed structural analysis of smart rotors and more complex structural optimization of HAWT and smart rotor blades.

As one of the carbon-free emission transportation method, fuel cell electric vehicles (FCEV) have become a very popular research topic for the recent years. However, as the fuel of FCEV, the hydrogen is usually produced by traditional steam reforming method, which is still not an environmentally friendly process.This report focuses on the study of infrastructure for hydrogen producing and refueling with zero carbon emission. An on-site water electrolysis hydrogen producing and refueling system powered by wind energy is designed and simulated in this study. The hydrogen is produced by on-site PEM electrolyzer powered by distributed wind turbine. First of all, the suitable petrol stations for such hydrogen refueling station modification are selected by GIS data analysis in Germany. By applying the constraints for safety and noise consideration, about 500 stations are selected from over 10000 petrol stations in Germany.Furthermore, the hydrogen producing and refueling system is designed and simulated by MATLAB modelling. The system is composed of five main components: wind turbine, PEM electrolyzer, compressors, storage tank and hydrogen dispenser. The technical and economic details for each of these devices are defined by a series of literature review. Besides, some parameters are from the real commercial products to make the system model more practical.A case study is built to validate the designed model for a 330kg/day H2 refueling station in Germany based on both current and future scenarios. The results show that more than 170 tons hydrogen can be produced annually. It can cover most of the hydrogen demand for the refueling throughout the year, which eliminates most of the hydrogen delivery cost from the other producer to the refueling station.In addition, by using the optimal pre-allocation control strategy, the system can become partially stand-alone with the grid. Only the high-pressure compressor system and cooling system for dispenser need energy supply from the grid, which is less than 1% of the system energy consumption. It means no extra grid reinforcement is needed. The wind energy can be used in a very efficient way. More than 95% of wind energy can be used for hydrogen producing while the other 5% supplies for the compressors as the electricity. The sensitivity research is also performed based on the climate data in a different year, which shows the stable operational behavior for the system.Last but not least, the economic analysis is carried out based on the case study. For the current scenario, the hydrogen production cost of the system is €6.1/kg and the overall dispensing price is €10.9/kg. It is expensive because the distributed wind turbine and on-site PEM electrolyzer are still costly technologies for now. However, with the R&D progress of these technologies, the production cost and the dispensed hydrogen fuel cost price for the future scenario will reduce to €2.6/kg and €5.1/kg respectively, which makes the hydrogen a very competitive fuel for the vehicles in the future.

The reduction of the Levelised Cost of Electricity (LCoE) in wind energy, and offshore in particular, is among the main objectives of research in the academia nowadays, and a demanding task as well. Offshore wind farms are capital intensive investments and lowering uncertainties and costs throughout design, planning, installation and operational phases will offer cheaper electricity production and a more competitive nature against fossil fuel powered energy. Of course, a big part of the total cost of a wind farm is the wind turbines themselves. Innovations in the design and manufacturing processes are always welcome in order to further advance within the learning curve of the technology and achieve efficient economies of scale. Furthermore, the blades of the wind turbine rotor are its most important component because they express the most basic operation of the turbine, aerodynamics and energy capture. Yet they pose structural challenges. There are efforts to maximise energy output while keeping their mass low, which should subsequently drive down secondary costs. Additionally, another important factor is the increase of energy output in the farm level that can lead to a larger cost reduction. This thesis aims to investigate the performance and feasibility of lightweight, low power density rotors. This investigation is made by acquiring a performance baseline with the reference rotor of the 10 MW INNWIND machine and comparing it with the proposed alternative rotor designs by means of parametrical modifications. The reference machine rotor radius is 89.166 m, with a blade mass of 41.7 tn and a rated power output of 10 MW operating at an optimal lambda of 7.5. All the new designs include an increase in rotor radius to 103 m. They also include differences in operational parameters such as rated rotational speed, blade slenderness and tip speed, while rated power stays the same. These designs result in different blade masses and allocation of energy production...

With the growing offshore wind industry, ramp events, i.e., significant variation in wind speed (or power) within a short time period, have become of critical importance to the end-users. The analysis of wind power ramp events from the perspective of grid operators or energy traders is prevalent in the literature. Nonetheless, this area of research is still evolving. The criterion of a minimum of turbines and its effect on the detection of ramp events, thresholds, or smoothing of power differences have not been considered so far. Moreover, little research has been conducted on analyzing the impact of ramp events on ultimate wind turbine loads. To the best of the authors’ knowledge, the results have not yet been validated with measurements. Therefore, the primary objective of this report is to investigate the impact of wind-induced ramp events on offshore wind farm power and ultimate wind turbine loads by using offshore measurements. At first, a wind power ramp detection algorithm is developed by considering the suitable power normalization technique and the criterion of a minimum number of turbines. The detected ramp events followed a decreasing trend in a number of events with the increasing wind speed, turbulence intensity, ramp duration, and wind direction changes. This can be because of the strong dependence of the number of ramp events on the non-linearity of the power curve. However, the available measurement data sets were found to be insufficient to capture the correlation and travel time of ramp events within two wind farms. Therefore, detailed meteorological information with the high spatial and temporal resolution is necessary for thorough analysis. Following that, extreme wind speed fluctuations (ramp-like events) were found to be extreme load drivers for wind speed bins that fall under the inactive pitch or above rated wind speed region. The measured loads are further compared with the simulation results, which are obtained by following the International Electrotechnical Commission (IEC) guidelines of extreme turbulence load cases. In general, the measured loads associated with the extreme fluctuations did not outperform the simulations, except for the tower side-side moments. Besides, extreme loads around rated wind speed exceed the simulations, but the values are not related to the extreme fluctuations. Therefore, this study examined the high-frequency time series for the most interesting blade root flap-wise moments. Based on the investigation, extreme loads over the wind speed range, except near rated wind speed, were governed by extreme turbulence or ramp events involving a sudden pitch transition from the inactive to the active region. The extreme loads around rated wind speed, which exceeded the simulations, were associated with the standard deviations equivalent to the normal turbulence but with comparatively higher fluctuation frequency. In conclusion, for the ultimate load analysis, the wind speed time series should include a sudden transition of a pitch angle from the inactive to the active region.

Traditionally a wind turbine’s power curve is used to model the long-term energy yield of the wind turbine and afterwards assess the performance of the turbine (power curve verification). But the current power curve is typically univariate: only dependent on the wind speed and slightly adjusted for site density, turbulence intensity and wind shear. This method limits the amount of atmospheric conditions taken into account, which (could) affect turbine performance. Therefore the Power Curve Working Group introduced the concept of an inner power curve (for common conditions) and an outer power curve (for all other conditions). While this is an improvement, it would be desirable to have not 1, not 2, but a multitude of power curves for different conditions. This multitude of power curves, for a range of atmospheric conditions, is the goal of this thesis. Using a non-parametric machine learning method, a neural network, the feasibility of modeling a wind turbine’s power curve from historical data is studied. This resulted in a model which provides a refinement on the warranted power curve (provided by the manufacturer) for certain conditions of 7 atmospheric parameters. These parameters are wind speed, turbulence intensity, wind shear, wind veer, temperature, pressure and humidity, but could in theory be extended to more parameters. This model resulted in three sub-models, which: 1) assess individual parameter impact/sensitivity on turbine performance, 2) provide for a company tool to continue power curve verification after a few years and 3) provide a general model to refine long-term energy yield estimations for future wind farms. Despite the somewhat limited model and currently available datasets to train the models from, both predictive models show improved accuracy compared to the traditional power curve. Besides validation with theory, the impact assessment model allowed for investigation of the impact of certain atmospheric conditions on the performance of certain wind turbines.

Wind turbine design is subject to load calculation standards. These determine material use which in turn affects wind turbine costs. Wind turbine cost reductions are important as they contribute to the economic feasibility of wind turbines. Therefore careful evaluation of the load standards is paramount for wind turbine design. This thesis offers an evaluation of 50-year ultimate load estimates described in the IEC 61400-1 standard and a tool for wind turbine designers to manage the estimates...

Measure Correlate Predict (MCP) is a method used to characterize the future wind resource at potential new wind farm locations. It finds a relationship between the wind data obtained at the target site and a nearby reference site over a short time period. This relationship is applied to long-term historical data from the reference site in order to predict the long-term wind resource at the potential wind farm location. Over the last few decades, new MCP techniques have been proposed, and modelled meteorological data in the form of reanalysis products have emerged. However, little research has been done regarding how the application of modelled data and different regression techniques in MCP affect the achievable wind resource prediction accuracy. This project set out to investigate the accuracy of the MCP procedure under different configurations. Three comparative studies have been done in this project. Firstly, the attainable accuracy with either nearby MET-station data or ERA5 reanalysis data as a long-term reference source is assessed. Secondly, the use of different regression types for forming the relationship between target and reference data in the MCP procedure is assessed. Lastly, the accuracy achieved with standard MCP is compared to that achieved with a new wind resource estimation method, the method of analogs. The accuracy of the different configurations is assessed through the ability to accurately predict a period of wind speed values measured at 35 sites located in different terrain types. The predictions are evaluated using metrics such as the coefficient of determination, the root mean square error, the mean absolute error and the mean bias error. This study found that ERA5 reanalysis data can serve as a reliable alternative to observed MET-station data. Generally, using ERA5 reanalysis data as a reference source always led to more accurate predictions then a MET-station reference source if the Pearson correlation between target and MET-station is lower than 0.8, and for offshore targets. If the Pearson correlation between target and MET-station reference is higher than 0.9, the achieved accuracy with either the MET-station or ERA5 data as a long-term reference is similar and depends on specific site conditions. In terms of regression methods it was found that the Matrix method, using the target site sectors for determining the regression parameters, generally outperforms other regression methods in terms of accuracy when determining the mean wind speed. Lastly, the method of analogs, a recently developed wind speed estimation method, yielded a similar prediction accuracy to standard MCP. It should be noted that the different regression methods in employed in MCP all exhibited very similar prediction outcomes, with an average absolute difference in the predicted mean wind speed between the best and worst performing regression methods of only 0.046 m/s. Furthermore, the performance of the method of analogs in terms of accuracy improves with a longer concurrent period during which the relationships are formed. This project employed relatively short concurrent periods for certain targets, which may have contributed to sub-optimal performances of the method of analogs.

Since the last decade the world energy supply is shifting from fossil- to renewable energy resources. Wind energy is one of the main resources of this new type of energy. However, a lot of work still needs to be done on the e_ciency improvements. This mainly results in increased rotor diameters. These large wind turbines are highly subjected to the vagaries of the atmosphere. Therefore a lot of research is being performed to the inuence of atmospheric conditions on the aerodynamic and structural behavior of wind turbines. Typical atmospheric conditions that are relevant for wind turbine design are gusts, vertical velocity shear, direction change and turbulence. The highly unsteady character of these atmospheric conditions make most of available empirical models inadequate for predicting the ow behavior around wind turbine parts. CFD can be a good alternative. However, wind engineering is a relatively new part in CFD and a lot of investigations still need to be done.

Offshore wind is a rapidly maturing renewable energy technology and is expected to play a central role in future energy systems. It has the potential to generate more than 420,000 TWh per year worldwide, an amount approximately equal to eighteen times the global electricity demand today. While many of the most abundantly resourceful sites are at water depths too extreme for fixed-base solutions, current floating turbine technologies suffer with high-costs and inefficiencies. Seawind Ocean Technology B.V., a Netherlands based company, is a manufacturer of fully integrated floating wind turbine systems. They have designed an innovative set of low-cost, low-weight, upwind two-bladed wind turbines, with teetering hinge and yawed power control. This teetering hinge decouples the shaft from rotor, by adding an extra degree of motion, and protects the turbine from harmful aerodynamic and gyroscopic loads, as well as the rotor from hydrodynamic loads. The innovative active yaw control eliminates the need for complex pitching systems to regulate power output, in turn reducing turbine head weight and turbine costs. There are a number of aims and objectives for this thesis project. The first, and most fundamental, was to investigate two-bladed and floating offshore turbine technology and share these findings with the hope that they make their way into the hands of change-makers who can promote the technology and consequently accelerate the green transition. The second was to optimise the loading analysis models of the Seawind 6 turbine using DNV GL’s wind turbine design software, Bladed. This is a 6 MW two-bladed floating offshore turbine and is intended for commercialisation by 2024. Seawind have extensive operational data from the Gamma 60’s deployment (the world’s first variable speed, two-bladed, wind turbine with a teetering hinge) in the 1990s. The Gamma 60 was modelled and compared to this operational data, with the calibrations in turn applied to the Seawind 6 models to improve its accuracy. Once achieved, the third goal was to carry out a thorough ultimate and fatigue load analysis of the optimised Seawind 6 model for various design load cases at extreme water depths. This investigation proved that the various investigated turbine components have been adequately sized and that suitable construction materials have been selected considering the loads they are expected to withstand. Following this large body of work, the fourth objective was to verify the theory that teeter motion is aerodynamically damped when the blades of a two-bladed, teetered turbine, are vertically oriented due to differences in angles of attack of the oncoming and retreating blades when yawed out of the wind. The fifth and final goal of this thesis work was to pull everything together and compare the floating offshore two-bladed Seawind 6 to a conventional floating three-bladed state-of-the-art turbine competitor. This was in terms of ultimate and fatigue loads experienced, capital and operational expenses (CAPEX and OPEX), lifetime carbon abatement, levelised cost of energy (LCOE), ease of manufacture and deployment, and operational performance.

The Ekman spiral is described by a coupled system of differential equations originally discussed by Walfrid Ekman (Ekman, 1905). This system is a simplified version of the Navier­Stokes equations. The differential equations, as discussed in Ekman’s paper, concern the currents of the ocean. However, it is also possible to interpret these equations so as to describe and predict the flow of wind. The research as presented is not only inspired by Walfrid Ekman’s original paper, but also by the master thesis from de Jong (2021). The main contribution of this thesis is to include the influence of a constant vertical wind speed on the classical Ekman spiral. After stuyding the classical Ekman spiral, the inclusion of a constant vertical wind speed is done step­wise. First, the vertical wind speed is discussed without having any vertical Coriolis forces. The classical Ekman spiral and the Ekman spiral with vertical wind, but no vertical Coriolis force, were solved exactly. Then, the vertical wind speed is included fully, giving rise to a non­linear coupled system of differential equations. For the non­linear system, an algorithm for solving it analytically using a general perturbation method is proposed. Next, the hodograph of the non­linear equations of motion including a constant vertical wind speed, is made using Euler’s Explicit numerical method and a shooting problem is solved.

The growth of renewable energy technologies is leading to energy systems that are more reliant than ever on renewables such as Wind and Photovoltaic (PV) power. Despite their benefits in terms of sustainability, their ubiquity poses challenges in maintaining grid stability given their intermittency, emphasising the prediction of power fluctuations. Physical models and statistical approaches, especially for nowcasting (forecasting for 0-6 hours in the future), have been superseded by Machine Learning (ML) methods in terms of forecast accuracy (below 3% Root Mean Squared Error (RMSE)). Within ML, Artificial Neural Network (ANN) methods seem to perform particularly well for nowcasting. This project focuses on predicting solar and wind meteorology with that level of accuracy, and on how to best use the prediction to minimize the cost of maintaining a balanced energy system, i.e. one where power consumption matches production at any moment. Producing accurate power predictions based on Multi-Modal (MM) data and the extent to which prediction accuracy reduces system cost are challenges to be addressed in this thesis. MM and End-to-End (E2E) training (with the system cost as the task of an ANN based algorithm) are investigated to this end. MM learning involves handling information from multiple types of input (audio and visual, for example) for performing a ML task such as regression or classification. It is of interest for this project because it has been shown to outperform other NN approaches in predicting sudden changes in solar irradiance. E2E learning entails an algorithm design which predicts the end goal of a ML process directly from the inputs. This is pursued because it addresses the true task (cost minimization) of system operators as the focus of the ML algorithm. The proposed method consists of a NN architecture that learns to fuse features from MM data (sky imagery and meteorological sensor data) at intermediate layers of the network in order to predict PV or Wind generation. This prediction is then used as an input to an Optimal Power Flow (OPF) problem (which seeks to minimize generation costs in a power system, considering power balance and transmission network constraints to ensure the twin goals of economic and secure system operation). The proposed model is trained E2E, therefore it is informed by the minimized cost solved by the optimization, rather than the intermediate power prediction (as conventional approaches would involve). In an IEEE 6-bus system with PV generation, a sequential training baseline results in costs 10% higher than a perfect forecast, while our proposed MM4-E2E approach achieves costs only 7% higher, a significant improvement. The intermediate prediction of PV power by MM4-E2E is also improved, with 18% lower RMSE by the proposed model compared to the baseline, explained by the enhancement of one modality by the other through MM learning. In a power system with two renewable sources, costs are reduced through the proposed model compared to a conventional approach (4% excess cost compared to 7%, measured against a perfect forecast), but power prediction accuracy is worse, sue to convergence to local minima.

In this research work, the phenomenon of extreme wind events or gusts has been studied in detail and different aspects related to the nature of gusts are explored. In order to detect wind gusts from a stochastic time series different gust detection techniques collected from previous research works and literature studies were compiled, refined, verified and compared against each other. In addition some important insight is also given regarding the setting up of appropriate values for various gust defining parameters. The gust detection techniques are developed into computational codes and applied over different data sets. A comparison between these techniques highlights the pros and cons of each one of them. The peak to peak method and the velocity increment method provides accurate information about the maximum wind speed acceleration within a small time interval. Other methods like peak over threshold and the acceleration over threshold methods are useful to detect specific type of wind gusts above a certain threshold. Wind data sets sampled at high frequency resolution and from different geographical locations were obtained and analyzed through these gust detections algorithms. Among these locations are the offshore wind farm at Egmond aan Zee (OWEZ), IJmuiden and the Cabauw Experimental Site for Atmospheric Research (CESAR) which are a representative of a near offshore, far offshore and an onshore location respectively. By using a uniform gust threshold criteria for peak over threshold and acceleration over threshold methods, a comparison between different locations reveal that the maximum gusts were detected for IJmuiden which generally has higher wind speeds throughout the year. For each location, the total number of gusts detected have been combined to obtain a mean gust shape. Furthermore, the maximum wind gusts are selected from each month and compared with the standard IEC gust shapes. The available high resolution wind data is for a duration of 1 year only which is not sufficient for the prediction of a maximum 50 year gust. However two different approaches are discussed to demonstrate the procedure. A statistical approach involving the extrapolation of data to predict the amplitude of maximum 50 year gust highlights the need for the availability of long term wind data. The analytical approach involving the calculation of the return period of different gusts is also explained and the results presented within this report are promising to continue further research within this domain. The techniques, findings and conclusions obtained through this research work can be further tested and eventually utilized to compliment or improve upon the existing extreme load cases of the wind turbine design standards.

Our present-day society is utterly dependant on electricity. This dependence will only grow as electrification of sectors such as manufacturing, transportation and building heating takes off. Most of the electricity these days comes from conventional plants running on coal and natural gas. Despite that these are reliable and cheap, the disadvantage of emitting greenhouse gases is no longer acceptable. Sustainable alternatives such as solar PV and wind have the highest potential. However, the replacement of conventional power plants by sustainable alternatives is subject to understanding the intermittent and unpredictable behaviour of both wind and solar PV and thereby ensuring that generation equals demand at all times. Energy storage technologies allow for separation between generation and supply to the grid. The aforementioned makes the large-scale integration of wind and solar PV more difficult. This study lays the foundation for an interconnected system model where solar PV, wind, and battery storage is combined. This study is therefore deliberately different than existing studies focussing on small, already severely constrained systems, such as island systems. The problems experienced and possible solutions are first identified by conducting a literature review and simultaneity analysis of wind and solar PV power. It turns out that it is possible while being self-reliant, using all the potential renewable energy and shifting the generation by arbitrage on the APX market to design a system with an increasing rate of income. The simulations showed that when the combined generation (of both wind and solar PV) during peak availability is higher than the grid connection capacity, the computed battery size [MWh] increases rapidly, causing a swift decrease in rate of return. This research also shows that with current imbalance settlement prices and battery installation cost minimizing imbalance is less viable than arbitrage on the APX market. The presented results are consistent with how the electricity system currently operates. At last, the results indicate that curtailing ’cheap’ solar PV energy with significant overplanting on the existing limiting grid connection is beneficial. In this research some important steps have been taken towards the design for a grid-connected optimal system. The method proposed should be tested with more wind and solar PV generation data. Further research should consider longer periods with real generation data making the results presented more accurate.

The development of offshore wind technology has progressed rapidly since the first offshore wind farm came to birth in 1991. During the last three decades, offshore wind has become an economically attractive option of renewable energy source for many countries to fulfill their commitment to combat the climate crisis. However, an open challenge remains in offshore wind, namely the aerodynamic interactions between multiple turbines, referred to as wake effects. When the upstream turbines extract energy from wind, they generate the wake with low velocity and high turbulence level on the downstream turbines, which substantially reduces the overall wind farm performance. The annual power production loss due to wake effects is generally 10 - 40%, which limits the reduction of the levelized cost of electricity for offshore wind energy. Therefore, developing effective wind farm control strategies which could mitigate the wake effect has become an emerging research area in the past decade. Recently, a novel wind farm control strategy called the Helix approach is proposed. The Helix approach adopts the individual pitch control technique to dynamically deform the wake into the helical shape, which induces wake instability and thereby stimulates wake recovery. This control strategy has demonstrated promising potential to mitigate the wake effect and to enhance the wind farm performance. To date, the Helix approach employs single harmonic pitch signals. However, more complex and higher-harmonic signals to potentially improve the effectiveness of the Helix approach have never been explored. Therefore, the purpose of this master thesis is to explore the potential of using multi-sine pitch profiles to further enhance the wake mixing. The high-fidelity aeroelastic simulator OpenFAST with its recent free vortex wake code is adopted to simulate the dynamic wake evolution. A Fourrier stability analysis is used to quantitatively identify the wake breakdown position. According to the simulation results for the multi-sine pitch profiles, the wake breaks down at 1.75 D, which is earlier than the one at 2.50 D for the original single-sine Helix strategy. The earlier wake breakdown indicates the potential of faster wake recovery, which is required to be validated by the higher-fidelity model in the future studies.

The height of wind turbines continues to increase, making the need for more and higher wind measurements for wind turbine model calibrations also increase. The Energy-research Centre of the Netherlands (ECN) and the Danish Technical University (DTU) have conducted the ScanFlow campaign in the winter of 2016/2017 to study the inflow wind field of one of ECN's research turbines by deploying multiple lidar instruments. One of the instruments used in this campaign was a SpinnerLidar. A SpinnerLidar is a forward looking, nacelle-mounted, continuous wave wind lidar system. It measures Line-of-Sight components of the wind in a plane 60 meters in front of the turbine, which need to be transformed into 3D wind vectors. To do so necessary assumptions were made about the free inflow periods, namely that a vertical shear is present and that a wind direction misalignment is more likely than horizontal deviations in wind speed. With these applied assumptions the 3D wind components were determined and used in a validation study with a pulsed lidar instrument, the WindCube V2. The proposed method seems robust as a high correlation in wind speeds at hub-height between two distinctly different lidar systems was found. Using the validated SpinnerLidar measurement to find the turbulent characteristics of the free inflow wind field resulted in turbulence intensity plots showing a higher turbulent component in the lower regions of the measurement plane. Also indications for a induction zone are visible in the SpinnerLidar measurements when compared to the WindCube measurements.

The Kite Power Group of the Wind Energy Department of Delft University of Technology has developed a pumping kite system to harvest high altitude wind energy (HAWP). HAWP technology is one of many renewable energy solutions that are emerging in a time at which Earth’s non-renewable energy resources are becoming scarce. The kite power system operates in periodic pumping cycles, alternating between reel-out and reel-in of the main tether from a drum, which in turn drives a generator. Electricity is generated during reel-out and only a small portion of the produced energy is reused during the reel-in process, which gives a positive end result. The current system has a movable ground station and contains all basic elements required to operate the kite in flight. The technology of the kite control unit is still is at an early stage of development and is being further developed and extensively tested at this moment. The future of the kite power technology depends heavily on the possibility of the kite power system to be fully automated and autonomous. In the current state of development of the system, a ground crew of at least three people is needed to operate the system which makes it highly inconvenient and costly in practice. As part of the Design Synthesis Exercise (DSE) a group of nine students was given the task to develop an automated launch, landing, and storage system for an upscaled version of the specific pumping kite power system which uses a kite of 70m2. Automation of the entire operation will enable the technology to be implemented on a larger scale and as such become economically profitable. Going through a full design process that ended with a detailed design of a launch, landing, and storage system in a period of 10 weeks required a well structured planning. Systems engineering methods were used which divide the design process in three main parts marking their respective completion in specific milestones. The first part covered the entire project planning and the preliminary design phase with a baseline report as the first milestone in the design process. In a highly creative manner a large number of ideas was produced. Subsequently, each one of them was evaluated by means of a trade-off and obvious losers faced immediate elimination. The second part of the design process was focused on the conceptual design of a limited number of concepts. At the start of this phase all ideas from the first part of the design process were integrated into full-system concepts. The feasibility of each of the integrated concepts was evaluated on a limited number of criteria after which another trade-off was performed. Four different concepts were chosen and were further developed in the remainder of the conceptual design phase. Multiple analyses were performed on topics such as functionality, technical details, sustainability and finance to obtain a good overview of the overall performance of each concept. After extensive research on all four concepts another trade-off was carried out and the final selection of one definite concept was made. At this point the conceptual design phase reached its milestone. Both the clients and kite power experts have confirmed the decision to take this concept into the detailed design phase. The third and final part of the systems engineering approach is the detailed design phase. In this phase the chosen concept was extensively researched and upgraded to a detailed design over a period of three weeks, and the results are contained in this technical report. Prior to research on the technical properties of the detailed design a detailed design overview was produced. The functionalities of the system were fully explored and put on paper. Furthermore the automated system was divided into subsystems and corresponding mechanisms. This enabled performing detailed research on specific elements of the system in subsequent steps of the design process. At the start of this third phase, pertinent background studies were performed to acquire a thorough understanding of both the aerodynamics and the commercial, environmental, and legal frameworks. The detailed research was first performed on all the subsystems, whereafter the integrated system got a closer look. The analytical approach was hereby always set prior to any calculations. The analysis of the subsystems was divided into structural integrity, energy consumption, actuators and sensors, operation time and cost. The integrated system analysis comprised research on the operations and maintenance, sustainability, soft- and hardware, and RAMS characteristics as a few examples. During this process many challenges arised. To resolve these challenges and optimize the design an iteration phase was implemented after the research was finished. In this phase the compliance matrix was used as a guide and solutions that improve compliance of the detailed design with the requirements were implemented. The detailed design phase ended with an investigation on post-DSE topics such as a financial analysis including profitability and Return on Investment (RoI), verification and validation and a project design and development logic. As a final result of the design process a solution for automated launch, landing, and storage of the kite power system has been produced on a detailed level. This system is based on a tall vertical boom of 35m (comparable to the length of a Boeing 737) on which a horizontal beam can slide up and down. The kite is launched from and landed upon this horizontal beam, when it is positioned at the top of the vertical boom. Both the horizontal beam and vertical boom can be tilted to put the system at an optimal angle for the launch and landing process. A storage unit has also been designed on a ground level. The horizontal beam can slowly lower the kite into the storage, in which a folding mechanism has been added to prevent entanglement of the tethers and the bridle system. The system has been designed in such a way that it can operate automatically and autonomously for a period of three months; a decision-making tool has been produced that ensures operation only within the kite’s operating limits (no lightning and a limited range of wind speeds). The research and development process as described in the above paragraphs have ensured that the detailed design has been explored on a widespread range of topics and has pushed to project group to achieve a sound level of depth within the available resources. The various results that are produced in this report lead the way for several conclusions. The most important conclusion is that the performance of the automated launch, landing and storage system is considered to be a success. It was shown that the the design can autonomously operate a pumping kite system within the boundaries of the requirements. Furthermore, it was shown that the system can land the kite in a wind speed range of 4 to 25m/s and launching can be performed between 5 and 25m/s. However, this performance fully relies on the capabilities of the control unit. The system was required to not exceed the limit of using 0.1% of the energy produced by the kite for the launch, landing, and storage procedure. As the system uses 0.036% of the average produced energy, it is considered to have met this requirement. As the team aimed to develop a sustainable design, recyclable materials were implemented. Besides the beam subsystem, steel is used in the design of the automated launch, landing and storage system. Steel is found to be recyclable for 93% and has highly convenient properties in case of structural application as well as costs. As for some parts no renewable materials could be used for structural or durability reasons, the goal to make the system 100% recyclable is not met. The client has stated a maximum cost requirement of Euro 20,000. Unfortunately this requirement is exceeded by 167% as the total estimated costs were estimated to be about Euro 53,500. If the client would reach break even after 20 years of operation, the energy price of 1kWh will have to reach an average price of Euro 0.285, which is unfeasible in comparison with the current price of Euro 0.06. The main reason for this is the replacement of the kite and main tether after each three months. The most important recommendations that follow from the conclusions are related to cost reduction, profitabilityand funding. The currently designed system increases its cost budget of Euro 20,000, reaching a total of Euro 53,451. It is suggested to use cost estimation relationships for assembly to obtain a more accurate representation of the total cost. A second point of interest is to investigate the need for storage of the kite. Possibly this need can be eliminated or reduced to a partial-cover if the kite and tether durability are increased. The regular kite and tether replacement (every three months) are the largest cost drivers of the entire system and an increase of their durability and lifespan will most certainly help the system to move towards a commercially feasible state. Other recommendations to improve the profitability of the system are related to upscaling the existing model and exploration of an offshore implementation, such that the system can generate more power. The last two propositions on the financial area are focussed on funding. The Kite Power Group is advised to start with the acquisition of subsidies as soon as possible and also look into the prospects of attracting business partners and sponsorships. A second set of recommendations is related to sustainability. On one hand hand the amount of recycled and/or recyclable materials can be further increased. A second suggestion poses the idea of promoting the kite power system as the true symbol of renewable energy and innovation to increase public interest. The kite power generation could be combined with a wind turbine on top of the tall vertical boom and a storage roof that is covered with solar panels. One final recommendationn follows from the contact with SkySails during this project. At this point such company is already commercially active on the energy market with a kite power system that has comparable features to the proposed detailed design in this technical report. The company has informed that they would gladly support the research with technical feedback and as such it is recommended to keep close contact with this company in further development stages.