With a growing world population, changing climate, and a greater reliance on electricity, global energy consumption is expected to continue to increase. Solar and wind energy are good options as they are renewable, safe and do not contribute to a lot of emissions as other energy sources. As both energy sources are growing in capacity, it is necessary that they are properly integrated in the planning processes, which should be reflected in the planning documents of municipalities. The aim of this thesis was to examine and compare how the municipalities of Linköping and Örebro integrate wind and solar energy into their planning documents. Additionally, to study the role of external actors and identify possible obstacles for the expansion of renewable energy production in the municipalities. The documents from both municipalities revealed that both municipalities integrate renewable energy through specific goals and plans for wind and solar energy. Linköping focuses on becoming a leader in solar energy production, while Örebro faces fewer obstacles in expanding both wind and solar energy. Both municipalities also work with energy companies and collaborate with various actors to achieve renewable energy goals, as the companies contribute with knowledge, finances, and innovation. The main challenges identified include prohibited areas designated by the armed forces, possible opposition from local communities, and long application processes. Although the research questions were responded to, the potential outcome of this thesis is recognised to have been enhanced and produced more substantial results and contributions, if a more comprehensive method approach was taken.

Transitioning to renewable energy is critical for reaching global sustainable development goals. As an oil-rich country, Azerbaijan has recognized the need to develop its renewable energy sector. It has set ambitious goals for increasing the share of renewables in its energy mix and establishing a green energy zone in the Karabakh region. The purpose of this master's thesis is to assess the potential of wind energy in Azerbaijan's Karabakh region and surrounding areas and identify the best scenario for its development. Four scenarios were evaluated via the PROMETHEE II Multi-Criteria Decision Analysis (MCDA) method based on their economic, environmental, technological, and social factors. Interviews with real stakeholders were undertaken to elicit weights for the criteria, and a sensitivity analysis was conducted to evaluate the robustness of the results. The findings were shared with the stakeholders, and their input was integrated into the final analysis. According to the findings, Scenario 4, which includes more installed capacity and increased investment, is best suited for the growth of wind energy in the Karabakh and surrounding areas from the perspective of developer and governmental body. In contrast, renewable energy expert and the public prefer Scenario 1, with less land use and less capacity. The findings indicate that for the effective development of wind energy in the area, a balanced approach taking into account the opinions of all stakeholders, is essential. This study contributes to Azerbaijan's long-term development by offering valuable insights into the potential of wind energy in the Karabakh region and surrounding areas and supporting informed decision-making for its expansion.

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A comparative study of two different approaches in wind energy simulations has been made where the aim was to investigate the performance of two commercially available tools. The study includes the linear model by WAsP and the computational fluid dynamic model of WindSim (also featuring an additional forest module). The case studied is a small wind farm located in the inland of Sweden featuring a fairly complex and forested terrain. The results showed similar estimations from both tools and in some cases an advantage for WindSim. The site terrain is however deemed not complex enough to manifest the potential benefits of using the CFD model. It can be concluded that estimating the energy output in this kind of terrain is done satisfyingly with both tools. WindSim does however show a significant improvement in consistency when estimating the energy output from different measurement heights when using the forest module compared to only using the standardized roughness length.

This thesis consists of a detailed analysis of different blade testing methods and improvements to a novel concept for tri-axial testing of large wind turbine blades. As the blades are one of the most critical components of the wind turbine, they have to be tested in order to ensure that their specifications are consistent with the actual performance of the blade. It must be demonstrated that the blade can withstand both the ultimate loads and the fatigue loads to which the blade is expected to be subjected during its design service life. There are basically two types of blade testing: static testing and fatigue testing. Testing of the blades statically and dynamically helps in improving the designs and the manufacturing processes. This thesis has two objectives. The first objective is to document the assumptions, calculations and results of an initial sizing of a bell crank system for testing blades 50m, 60m and 70m long. The second objective of this report is to document the modeling of one of the alternatives to bell crank system in SolidWorks. The thesis ends with conclusions and suggestions for future work. An advanced blade testing method which can be used for large wind turbine blades is developed and so are the system requirements. The concept is used to excite the blade in flapwise and edgewise direction simultaneously. The flap motion of the blade is caused by BREX resonant technology, which is already used by National Renewable Energy Laboratory (NREL) in Colorado, and edgewise motion is delivered by the use of two inclined hydraulic actuators and linear guide rail system is used to move the inclined actuators in the flapwise direction along the blade motion. The hydraulic system and linear guide rail requirements are analyzed and discussed. The design is discussed and analyzed in detail proving it to be feasible. The cost estimation is done for the design. It is recommended for implementation as it will serve as an efficient way of testing large wind turbine blades.

In order to achieve Net Zero emissions in the UK by 2050 and decarbonize the energy sector the integration of increased volumes of additional renewable wind energy is critical. Distribution network operators face challenges in increasing the capacity of this variable source of energy onto the electricity networks. Distribution network operators in Scotland have integrated more wind energy onto their networks to date and have learnings through experience that are worth investigating. The research conducted in this thesis is a comparative analysis of the Network Development Plans of three UK distribution Network Operators, Scottish Power Energy Networks in southern Scotland, Scottish and Southern Energy Networks in northern Scotland, and UK Power Networks in the southeast of England area.  The method used is a comparative analysis of the Network Development Plan documents using a set of pre-selected variables while also allowing for other new emergent variables to be included in the analysis and results. The pre-defined variables are grid capacity, flexibility, grid integration technologies, market structures, planning and regulatory framework, operational experience, efficiency, and location / wind availability. Variable codewords were used to perform the document search and related keywords were used where returns were insufficient. Two further variables emerged frequently in the texts as a result of keyword searches which were transmission links and energy storage and were also included in discussions. Results of the research reveal that Scottish Hydro Electricity Power Distribution, who operate in the north of Scotland, and Scottish Power Energy Networks who operate in the south of Scotland, appear to have a more innovative and proactive approach to grid integration technologies, stakeholder engagement, and innovation projects for increased wind energy integration. UK Power Networks have a larger investment plan approved by the UK electricity and gas markets regulator, Ofgem, but lack of experience in integration of large volumes of wind energy leaves it lagging behind its counterparts when it comes to integration and management of wind energy. Findings from analysis of the Network Development Plans is backed up in literature which claim that energy storage, smart grid technologies, and infrastructure upgrades are critical for integration of wind energy to transform it into a reliable and predictable energy source and manage its integration on to the electricity networks.

Wind energy is an appropriate solution to reduce carbon emissions and climate change. The expansion of wind energy developments in Sweden in recent years has created substantial opposition which makes wind energy tougher to develop. The landscape and visual constraints associated with wind energy developments has become the critical reason for local opposition and protest. Planning information relating to the visual and landscape impacts of a proposed wind energy development are often brought forward through a landscape analysis. Digital tools are used in a landscape analysis to identify the proposed visual effects associated with a development. These tools provide visual aid of the proposed development through 2-dimentional and 3-dimentional images, identify constraint areas on a map as outlined in the respective development plans and identifies where visibility is likely to occur. This thesis uses a quantitative assessment by the example of a potential wind farm in Sundsvall Municipality in Sweden and theoretical research on landscape connotation. The motivation of this thesis is to outline the opportunities and limitations associated with the digital tools used to conduct a landscape analysis, promote a standardised approach to practice and implement suggestions to improve digital tools to allow for more public participation and to limit opposition towards wind farm developments. The results of this thesis suggest that the social issues and visual perceptions of turbines can be reduced through the inclusion of digital tools, but radical changes are needed within the planning process to recognise the benefits of digital tools and provide a standardised framework.

Airborne Wind Energy is an emerging technology that harnesses the power of the wind by using tethered wings. Among the flying devices are ram-air wings made from coated textiles that utilize dynamic pressure to gain their shape. During flight operation, the textiles are subject to long-term weathering exposure and high aerodynamic loads, leading to degradation processes and the ultimate loss of functional properties. Therefore, a key challenge in the Airborne Wind Energy industry is the improvement of the textile durability of ram-air kites. This thesis contributes to solving this problem by investigating the effects of 200 hours of artificial weathering and 36 weeks of natural weathering on the mechanical properties of selected state-of-the-art kite textiles and the underlying principles of degradation. The tested materials involve two polyamide 6.6 rip-stop weaves coated with polyurethane and silicone, as well as a coated plain weave and a flexible laminate made from high-modulus polyethylene. The results show that all materials are clearly affected by the exposure to weathering, but the implications on the mechanical properties and the rate of degradation vary significantly. The high-modulus polyethylene textiles demonstrate superior tensile properties, but severe coating degradation causes a significant rise in air permeability. Consequently, the high-modulus polyethylene textiles are considered unsuitable for application in ram-air kites, as the high permeability prevents the kite from maintaining sufficiently high pressure. In contrast, the silicone coated polyamide 6.6 textile exhibits superior air permeability after long-term exposure to weathering conditions. FTIR spectroscopy and TGA indicate that the reduced permeability could arise from curing processes in the silicone coating.

The world energy needs increasing in a significant number and currently it is mainly sourced from the finite fossil fuel. Other than that, fossil fuel is the main source of CO2 emissions that leads to the increasing rate of global warming that will ultimately change the earth's climate. Thus, researcher began to look for alternative energy that is renewable and has the least impact to the world's climate; one example is wind energy. Sweden has experienced a significant increase in wind energy generation, where the wind production constantly grows in the double-digit rates since 2010. However, developing a wind energy requires a significant research and feasibility study in order to provide an economically sustainable operation. Wind farm needs to be located in areas with a good wind potential, however there are several technical and economic limitation on where the wind farm should be located. On top of that, social rejection might also hinder the development of wind energy. Audio-visual obstruction and disturbance to the natural state of the environment are the main arguments that were used to challenge the development of wind farm. Therefore, a multi-disciplinary study needs to be conducted in order to find the perfect balance; which is exactly what this study is all about. The result of this study shows that despite the threat of climate change, wind farm in Sweden could thrive due to the increasing wind speed across the country. It was also discovered that around 30% of the country is suitable, from the social, technical, and economic point of view, as a new location for wind farms. This study also reveals that most of the canceled / rejected wind farms were probably caused by the social rejection due to their proximity to population center or conservation areas. This study also discussed the concept of place attachment and identity that leads to the NIMBY attitude and reflects the concept of the social acceptance issue that happened in Sweden and on how to localize the wind farm concept to the local residence.

In recent years, wind and other variable renewable energy sources have gained a rapidly increasing share of the global energy mix. In this context the greatest concern facing renewable energy sources like wind is the uncertainty in production volumes as their generation ability is inherently dependent on weather conditions. When providing forecasts for newly commissioned wind farms there is a limited amount of historical power production data, while the number of potential features from different weather forecast providers is vast. Bayesian regularization is therefore seen as a possible technique for reducing model overfitting problems that may arise. This thesis investigates Bayesian Neural Networks in one-hour and day-ahead forecasting of wind power generation. Initial results show that Bayesian Neural Networks display equivalent predictive performance to Neural Networks trained by Maximum Likelihood in both one-hour and day ahead forecasting. Models selected using maximum evidence were found to have statistically significant lower test error performance compared to those selected based on minimum test error. Further results show that the Bayesian Framework is able to identify irrelevant features through Automatic Relevance Determination, though not resulting in a statistically significant error reduction in predictiveperformance in one-hour ahead forecasting. In day-ahead forecasting removing irrelevant features based on Automatic Relevance Determination is found to yield statistically significant improvements in test error. / Under de senaste åren har vind och andra variabla förnybara energikällor fått en snabbtökande andel av den globala energiandelen. I detta sammanhang är den största oron förförnybara energikällors produktionsvolymer vindosäkerheten, eftersom kraftverkens generationsförmåga i sig är beroende av väderförhållandena. Vid prognoser för nybyggdavindkraftverk finns en begränsad mängd historisk kraftproduktionsdata, medan antaletpotentiella mätvärden från olika väderprognosleverantörer är stor. Bayesian regulariseringses därför som en möjlig metod för att minska problem med den överanpassning avmodellerna som kan uppstå.Denna avhandling undersöker Bayesianska Neurala Nätverk (BNN) för prognosticeringen timme och en dag framåt av vindkraftproduktion. Resultat visar att BNN gerekvivalent prediktiv prestanda jämfört med neurala nätverk bildade med användandeav Maximum-likelihood för prognoser för en timme och dagsprognoser. Modeller somvalts med användning av maximum evidence visade sig ha statistiskt signifikant lägretestfelprestanda jämfört med de som valts utifrån minimaltestfel. Ytterligare resultatvisar att ett Bayesianskt ramverk kan identifiera irrelevanta särdrag genom automatiskrelevansbestämning. För prognoser för en timme framåt resulterar detta emellertid intei en statistiskt signifikant felreduktion i prediktiv prestanda. För 1-dagarsprognoser, närvi avlägsnar irrelevanta funktioner baserade på automatisk relevans, fås dock statistisktsignifikanta förbättringar av testfel.