On planet Earth, fossil fuels are the most important sources of energy. However, these resources are limited and being depleted dramatically throughout last decades. Finding feasible substitutes of these resources is an essential duty for humanity. Fortunately, Mother Nature is providing us a number of good solutions for this crucial threat against our planet. Solar irradiance, wind blowing, oceanic and maritime waves are natural resources of energy that are capable of completely covering the annual consumption of all inhabitants on the Earth. In this research a set of components including “Northern Power NPS 100-24” wind generators, “Kyocera KD 145 SX-UFU” PV arrays, “Gildemeister 10kW-40kWh Cellcube” battery bank and HOMER bi-directional converter system were considered and successfully applied on HOMER tool and Particle Swarm Optimization (PSO) method. The main design goals of the presented hybrid system are to use 100% renewable energy resources in the commercial sector, where all power is produced in the immediate vicinity of the business place, adding strong advertising values to the setup. In order to supply hourly required load for a grocery store   (1000 ) in Malmö city with 115 kW peak load and 2002 kWh/d with maximum 0.1% unmet, the system was optimized to achieve minimum Levelized Cost of Energy (LCOE) and the lowest Net Present Cost (NPC). The HOMER simulation for quantitative analysis, along with a Particle Swarm Optimization (PSO) solution method is proposed and the results are compared. The results show that an optimized hybrid system with 3.12  LCOE, and power production of 28.5% by PV arrays and 71.5% by wind generators, is the best practice for this case study. / De fossila bränslena är idag de viktigaste energikällorna på jorden. Dessa resurser är dock begränsade och har utarmats i en allt högre takt under de senaste decennierna. Att hitta möjliga ersättare för dessa resurser är därför viktigt. Lyckligtvis tillhandahåller naturen ett antal bra lösningar för detta avgörande hot mot vår planet. Solstrålning, vind, havsströmmar och -vågor är naturliga resurser av energi som kan täcka hela den årliga globala förbrukningen. I den här rapporten studeras ett hybridsystem bestående av Northern Power NPS 100-24 vindkraftverk, Kyocera KD 145 SX-UFU solcellerspaneler, Gildemeister 10kW-40kWh Cellcube batteribank och HOMER dubbelriktad växelriktare. Detta modellerades och optimerades dels i mjukvaran HOMER, dels via optimeringsmetoden Particle Swarm Optimaization (PSO). Det övergripande designkravet för det presenterade hybridsystemet är att använda 100% förnyelsebar energi i en kommersiell verksamhet, där all elektricitet produceras i närhet av verksamheten, vilket kan ge tydliga marknadsföringsvärden till installationen. För att kunna möta energibehovet varje timme för en livsmedelsbutik (1000 ) i Malmö med 115 kW toppförbrukning och 2002 kWh/dag, med maximalt 0,1% ej mött behov, optimerades systemet för att uppnå minimal energikostnad (Levelized Cost of Energy, LCOE) och lägsta nettonuvärde (Net Present Cost, NPC). En HOMER-simulering för kvantitativ analys, tillsammans med en PSO-optimering, har genomförts och resultaten har jämförts. Resultaten visar att ett optimerat hybridsystem med LCOE på 3,12 SEK/kWh, där solceller står för 28,5% av kraftproduktionen och vindkraftverk för 71,5%, är den bästa lösningen för denna fallstudie.

This thesis focuses on providing the means to use vertical-axis wind turbines (VAWTs) in wind farms as an alternative form of harnessing wind energy in offshore and urban environments where both wake and acoustic effects of turbines are important considerations. In order for VAWTs to be used in wind farm layout analysis and optimization, a reduced-order wake model is needed to calculate velocities around a turbine quickly and accurately. However, a VAWT wake model has not been available to accomplish this task. Using vorticity data from computational fluid dynamic (CFD) simulations of VAWTs and cross-validated Gaussian distribution and polynomial surface fitting, a wake model is produced that can estimate a wake velocity deficit of an isolated VAWT at any downstream and lateral position based on nondimensional parameters describing the turbine speed and geometry. When compared to CFD, which takes over a day to run one simulation, the wake model predicts the velocity deficit at any location with a normalized root mean squared error of 0.059 in about 0.02 seconds. The model agrees with two experimental VAWT wake studies with a percent difference of the maximum wake deficit of 6.3% and 14.6%. Using the actuator cylinder model with predicted wake velocities of multiple turbines, aerodynamic loads can be calculated on the turbine blades to estimate the power production of a VAWT wind farm. As VAWTs could be used in urban environments near residential areas, the noise disturbance coming from the turbine blades is an important consideration in the layout of a wind farm. Noise restrictions may be imposed on a wind farm to limit the disturbance, often impacting the wind farm's power producing capability. Two specific horizontal-axis wind turbine farm designs are studied and optimized using the FLORIS wake model and an acoustic model based on semi-empirical turbine noise calculations to demonstrate the impact a noise level constraint has on maximizing wind farm power production. When a noise level constraint was not active, the average power production increased, up to 8.01% in one wind farm and 3.63% in the other. Including a noise restriction in the optimization had about a 5% impact on the optimal average power production over a 5 decibel range. By analyzing power and noise together, the multi-modality of the optimization problem can be used to find solutions were noise impact can be improved while still maximizing wind farm power production.

Cette thèse est consacrée à l'étude des instabilités du sillage tourbillonnaire des rotors, largement utilisés dans l'industrie pour la conversion d'énergie mécanique. Leur sillage peut être modélisé par un ensemble de vortex hélicoïdaux entrelacés, au sein duquel de nombreuses instabilités peuvent émerger. Ces mécanismes ont un impact significatif sur l'évolution intermédiaire du sillage et peuvent influencer les performances du rotor. Ce travail, plus particulièrement dédié aux hélicoptères, s'est tout d'abord attaché à caractériser expérimentalement l'écoulement derrière trois rotors conçus pour des régimes de vols différents. Ces conditions de bases ont ensuite servi à étudier les différents modes instables de grande longueur d'onde pouvant apparaître dans le sillage. Une bonne correspondance est trouvée entre les prédictions théoriques et les mesures expérimentales des taux de croissance associés. Une rapide analyse de l'évolution spatio-temporelle de ces perturbations a permis d'étudier la propagation d'une perturbation localisée dans le plan rotor. Il est en effet envisagé que dans certaines configurations de vol de descente, les instabilités provoquent la transition du sillage vers un état spécifique connu sous le nom d'état d'anneau tourbillonnaire, potentiellement dangereux pour l'appareil. Il se caractérise par une stagnation du sillage au voisinage du plan rotor qui en dégrade les performances. / This work studies the instabilities associated with the wake of a rotor. These devices are used in many applications such as energy harvesting or propulsion,and their optimisation is crucial for both industry and the environment. The wakebehind a rotor is broadly defined as a system of interlaced helical vortices, whose dynamics governs the transition from the near-wake to the far-wake regime. In our first study, we investigate the wake behind different small-scale rotors in their design operating condition. We use the resulting flows in a subsequent linear stability analysis, aiming at predicting long-wavelength instability modes in the helical vortex. We find that the theoretical prediction of the modes growth-rates matches our experimental measurements. We also show that the dynamics of helical vortex filaments can be predicted from simple two-dimensional theory. In more critical flow configurations, instabilities are suspected to promote the transition to hazardous regimes such as the so called Vortex-Ring State, characterised by large-scale recirculating structures.The second part of this work is thus dedicated to the spatio-temporal evolution of localised perturbations in the rotor plane, and their potential tendency to propagate upstream in the flow.

A primary motivation for this research comes from the need to improve the ability of polymer-matrix composites to withstand lightning strikes. In particular, we are concerned with lightning strike damage in composite wind turbine blades. The direct effects of lightning strike on polymer-matrix composites often include rapid temperature rise, melting or burning at the lightning attachment points, and mechanical damage due to lightning-induced magnetic force and acoustic shock wave. The lightning strike damage accumulation problem is essentially multiphysic. The lightning plasma channel discharges an electric current up to 200 kA, inducing a severe heat flux at the surface of the composite structure, as well as generating Joule heating through the composite structure. The resulting electro-thermo-mechanical response of the composite structure may include matrix degradation and decomposition, delamination, and fiber breakage and sublimation, thus leading to catastrophic failure. The existing studies related to the lightning strike damage in composites ignored the lightning channel radius expansion during the initial lightning discharge and lacked adequate treatment of material phase transitions. These assumptions significantly simplify the mathematical treatment of the problem and affect the predictive capabilities of the models. Another common feature of these limited studies is that they all focused on carbon-fiber-reinforced polymer-matrix (CFRP) composites, which are electrically conductive. In the present thesis, the thermal responses and thermal ablations in a non-conductive glass-fiber-reinforced polymer-matrix (GFRP) composite wind turbine blade and in a conductive CFRP composite wind turbine blade are studied, respectively. In the case of non-conductive GFRP composite wind turbine blade, prior to the thermal response and thermal ablation analysis, a finite element analysis is performed to calculate the electric field due to lightning stepped leader to estimate the dielectric breakdown of the non-conductive composite wind turbine blade. The estimation of dielectric breakdown is used to determine whether Joule heating needs to be included in the problem formulation. To predict the thermal response and thermal ablation in the composite structure due to lightning strike, a physics-based model describing surface interaction between the lightning channel and the composite structure has been developed. The model consists of: (i) spatial and temporal evolution of the lightning channel as a function of the electric current waveform; (ii) temporary and spatially non-uniform heat flux and current density (in the case of electrically conductive CFRP composite or if dielectric breakdown occurs in the case of non-conductive GFRP composite) generated at the composite structure; and (iii) nonlinear transient heat transfer problem formulation for layered anisotropic composites that includes the moving boundary of the expanding lightning channel and the phase transition moving boundary associated with instantaneous material removal due to sublimation. The model has been employed to investigate the thermal responses and thermal ablations in a GFRP composite laminated panel used in a Sandia 100-meter all-glass baseline wind turbine blade (SNL 100-00) and a typical CFRP composite laminated panel subjected to lightning strike. The temperature-dependent directional material properties for both the GFRP and CFRP composites have been determined in this thesis using a micromechanics approach based on the experimental data for fibers and resin. An integrated Matlab-ABAQUS numerical procedure features the aforementioned aspects (i), (ii), and (iii) of the developed model. The obtained results include the evolution of temperature fields in the composite laminated panel and the progressive shape change of the composite laminated panel due to thermal ablation. The predictions of thermal ablation in the CFRP composite laminated panel are validated by reported experimental results.

Vibrations of a wind turbine have a negative impact on its performance and therefore approaches to effectively control turbine vibrations are sought by wind industry. The body of previous research on wind turbine vibrations has focused on physics-based models. Such models come with limitations as some ideal assumptions do not reflect reality. In this Thesis a data-driven approach to analyze the wind turbine vibrations is introduced. Improvements in the data collection of information system allow collection of large volumes of industrial process data. Although the sufficient information is contained in collected data, they cannot be fully utilized to solve the challenging industrial modeling issues. Data-mining is a novel science offers platform to identify models or recognize patterns from large data set. Various successful applications of data mining proved its capability in extracting models accurately describing the processes of interest. The vibrations of a wind turbine originate at various sources. This Thesis focuses on mitigating vibrations with wind turbine control. Data mining algorithms are utilized to construct vibration models of a wind turbine that are represented by two parameters, drive train acceleration and tower acceleration. An evolutionary strategy algorithm is employed to optimize the wind turbine performance expressed with three objectives, power generation, vibration of wind turbine drive train, and vibration of wind turbine tower. The methodology presented in this Thesis is applicable to industrial processes other than wind industry.

The rapid growth of wind turbines in terms of turbine size, number of installations and rated capacity has a huge impact on its operations and maintenance costs. Monitoring the performance of wind turbines and early fault prediction is highly desirable. To date, traditional maintenance strategies such as reactive maintenance, periodic maintenance etc. are more prevalent in wind industry. However, over the last couple of years, the research pertaining to wind turbine has been shifted towards the condition monitoring and maintenance. Condition monitoring approaches have shown their potential in wind industry by providing continuous monitoring of the wind turbines, and identifying fault signatures in the event of faults. However, most of the studies reported in literature are based on the simulated dataset, or in constrained experiments. In reality, the external environment plays an important role in governing the turbine operations. Moreover, the cost associated with condition monitoring cannot be justified as it often requires installations of specific sensors, equipment. Another stream of research focuses on utilizing historical turbine data for turbine performance assessment in real time. The cost associated with such approaches is almost negligible as most of the wind farms are equipped with SCADA systems which records turbine performance data in regular time-interval. Such approaches are called as performance monitoring. In this dissertation, the performance monitoring of wind turbines is accomplished using the historical wind turbine data. The information from SCADA operational data, and fault logs is used to construct accurate models predicting the critical wind turbine faults. Depending upon the nature of turbine faults, monitoring wind turbines with different objectives is studied to accomplish different research goals. Two research directions of wind turbines performance are pursued, (1) identification and prediction of critical turbine faults, and (2) monitoring the performance of overall wind farm. The goal of predicting critical faults is to facilitate planned maintenance, whereas, monitoring the performance of overall wind farm provides the status-quo of all wind turbines installed in a wind farm. Depending on the requirement, the performance of overall wind farm can be assessed on a daily, weekly, or monthly basis. Solution methodologies presented in the dissertation are generic enough to be applicable to other industries such as wastewater treatment facilities, flood prediction, etc.

Improving performance of wind turbines through effective control strategies to reduce the power generation cost is highly desired by the wind industry. The majority of the literature on performance of wind turbines has focused on models derived from principles versed in physics. Physics-based models are usually complex and not accurate due to the fact that wind turbines involve mechanical, electrical, and software components. These components interact with each other and are subjected to variable loads introduced by the wind as well as the rotating elements of the wind turbine. Recent advances in data acquisition systems allow collection of large volumes of wind energy data. Although the prime purpose of data collection is monitoring conditions of wind turbines, the collected data offers a golden opportunity to address most challenging issues of wind turbine systems. In this dissertation, data mining is applied to construct accurate models based on the turbine collected data. To solve the data-driven models, evolutionary computation algorithms are applied. As data-driven based models are non-parametric, the evolutionary computation approach makes an ideal solution tool. Optimizing wind turbines with different objectives is studied to accomplish different research goals. Two research directions of wind turbines performance are pursued, optimizing a wind turbine performance and optimizing a wind farm performance. The goal of single wind turbine optimization is to improve wind turbine efficiency and its life-cycle. The performance optimization of a wind farm is to minimize the total cost of operating a wind farm based on the computed turbine scheduling strategies. The methodology presented in the dissertation is applicable to processes besides wind industry.

Sustainable energy solutions are aimed to reduce the consumption of fossil fuels by using renewable energy sources and energy efficiency techniques. This thesis presents two new sustainable energy applications in the field of electrical machines.Polyphase induction motors dominate the energy usage spectrum for industrial and commercial applications. The conventional winding structure used in both synchronous and induction machines has a basic unit of the winding with a 60 degree phase belt and a three phase connection either in star or delta. A new winding structure using an innovative Star-Delta Series Connection (SDSC) which has a high winding coefficient and low harmonic content is presented in this thesis. The principle of the SDSC winding is described. The Electro-Magnetic Belt and Electro-Magnetic Space diagram are two important means to be used for optimization of the new winding. Experimental results from two prototypes confirm the theoretical analysis. The efficiency of the new machine at rated load increased by about 3.8% as compared to the standard machine with a conventional winding structure.Wind energy is one of the most attractive renewable energy options. Wind turbines are designed to couple either synchronous or asynchronous generators with various forms of direct or indirect connection with grid or diesel generators. Permanent magnet (PM) generators using high energy Neodymium- Iron-Boron magnets offer advantages such as direct coupling without gear box, absence of excitation winding and slip rings, light weight and smaller size. This thesis presents the design and development of an outer-rotor PM generator suitable for wind energy conversion. The initial electromagnetic design followed by a Finite Element Analysis is presented in detail. A 20 kW prototype machine was built and extensively tested. It was found that the machine could maintain an ++ / efficiency of about 85% for a wide operating range. Equivalent circuit models were developed. The results of the Finite Element analysis matches closely with the experimental and the designed values.

Numerical simulations of the Navier-Stokes equations are performed to achieve a better understanding of the behaviour of wakes generated by wind turbines. The simulations are performed by combining the in-house developed computer code EllipSys3D with the actuator line and disc methodologies. In the actuator line and disc methods the blades are represented by a line or a disc on which body forces representing the loading are introduced. The body forces are determined by computing local angles of attack and using tabulated aerofoil coefficients. The advantage of using the actuator disc technique is that it is not necessary to resolve blade boundary layers. Instead the computational resources are devoted to simulating the dynamics of the flow structures. In the present study both the actuator line and disc methods are used. Between approximately six to fourteen million mesh points are used to resolve the wake structure in a range from a single turbine wake to wake interaction in a farm containing 80 turbines. These 80 turbines are however represented by 20 actuator discs due to periodicity because of numerical limitations. In step one of this project the objective was to find a numerical method suitable to study both the flow structures in the wake behind a single wind turbine and to simulate complicated interaction between a number of turbines. The study resulted in an increased comprehension of basic flow features in the wake, but more importantly in the use of a numerical method very suitable for the upcoming purpose. The second objective of the project was to study the basic mechanisms controlling the length of the wake to obtain better understanding of the stability properties of wakes generated by wind turbine rotors. The numerical model was based on large eddy simulations of the Navier-Stokes equations using the actuator line method to generate the wake and the tip vortices. To determine critical frequencies the flow is disturbed by inserting a harmonic perturbation. The results showed that instability is dispersive and that growth occurs only for specific frequencies and mode types. The study also provides evidence of a relationship between the turbulence intensity and the length of the wake. The relationship however needs to be calibrated with measurements. In the last project objective, full wake interaction in large wind turbine farms was studied and verified to measurements. Large eddy simulations of the Navier-Stokes equations are performed to simulate the Horns Rev off-shore wind farm 15 km outside the Danish west coast. The aim is to achieve a better understanding of the wake interaction inside the farm. The simulations are performed by using the actuator disc methodology. Approximately 13.6 million mesh points are used to resolve the wake structure in the park containing 80 turbines. Since it is not possible to simulate all turbines, the 2 central columns of turbines have been simulated with periodic boundary conditions. This corresponds to an infinitely wide farm with 10 turbines in downstream direction. Simulations were performed within plus/minus 15 degrees of the turbine alignment. The infinitely wide farm approximation is thus reasonable. The results from the CFD simulations are evaluated and the downstream evolution of the velocity field is depicted. Special interest is given to what extent production is dependent on the inflow angle and turbulence level. The study shows that the applied method captures the main production variation within the wind farm. The result further demonstrates that levels of production correlate well with measurements. However, in some cases the variation of the measurement data is caused by the different measurement conditions during different inflow angles. / QC 20100720

Complex systems can be divided into simpler substructures. Determining the properties of each subcomponent by experimental procedures is practical and can serve to verify or calibrate finite element models. In this work, an existing model of a wind turbine blade was improved by use of experimental data. Such a blade is a subpart of a complete wind turbine. For calibration purpose, several material tests were made in order to determine the stiffness and mass properties. Later on, vibration tests of the blades were conducted and compared with simulation results of the improved model. Geometry variability within sets of blades was also studied. The blade twist angles and the center of gravity positions were found to vary moderately, which accounts for differences in blades’ dynamic behavior. Correlations between experimental data and analytical model results were very high for the first eight modeshapes. That is, according to the Model Assurance Criterion the calibrated model achieves a high-quality representation of reality. However, torsional modes in the computer model occur at a higher frequency than the experimental ones. Substructuring of the turbine allows the blades to be modeled and validated independently of the other substructures and can later be incorporated into a complete model of the turbine.