This is a feasibility study that examines various aspects of building a wind farm on Malmön in Norrköping. The feasibility study deals with interests of conflict, park design, electrical connections, production calculation, financial calculations and operating- and timetable. The report is divided into two distinct parts. First a theoretical part, which deals with conflicting interests, park design and electrical connections. Second a part with simulations dealing with production calculations, and financial calculations. Opposing interests are mapped so that problem areas can be found, and help put focus on the right places at a future environmental impact assessment (EIA). There are a number of areas where planners have to assess on an EIA, this thesis point on the most important areas. There are a few areas of national interest and the Natura 2000 protection. Part of the area of the planned park is also within Norrköping Airport area of influence and an assessment must be made by the civil aviation authority (CAA) to determine if a wind farm on the location would affect the air traffic and if so, what part of the location would be affected. Furthermore, there is the area of a flight route for birds as well as an area that is a common livelihood for birds. These should be examined to see if wind power in the area can become a problem for these birds. A production calculation has been implemented in the program WindPRO. This feasibility study has dealt with three different park designs with the wind turbine, Vestas V-126 3.3MW, which is the largest low wind turbine we found. Based on wind data, data for wind turbines, distance between turbines and other data we can do a calculation of how much energy the wind farm produces annually. Calculations were also made In WindPRO regarding sound levels and shadow creation. This is so that the wind farm will be designed so target values for noise and shadows are met. All park designs in this project has been designed so that the sound and shadow benchmarks for buildings nearby are met. Based on production estimates, an economic calculation been carried out. The different park designs have between 7 and 11 wind turbines with an annual energy production of between 58 and 91 GWh per year. The wind turbines have been estimated to cost approximately 25 Mkr each, plus about 10 % of turbine cost for foundations, roads, power lines and other similar expenses. One calculation was made for the case the electric connection could be done directly to some of the industries in the location, for this simulation the cost over the wind mill was about 15 %. Under all these conditions, the project should be financially sustainable, with a payback period of about 6-11 years and a return of investment of 1-7 %.

Syftet med detta examensarbete är att optimera produktionen för högst lönsamhet för den planerade vindkraftsparken Hästkullen i Härnösand och Timrå kommuner. Arbetet har utförts för SCA Energy i Sundsvall. SCA projekterar vindkraftsparken Hästkullen i samarbete med EON. Vid en satsning för etablering av en vindkraftspark krävs investering på miljardbelopp. Det är därför viktigt att säkerställa att investeringen på sikt blir lönsam. För att kunna göra denna uppskattning krävs det noggranna produktionsberäkningar med tillgång till ett års komplett vinddata. Det program som använts för att simulera produktionsberäkningarna är WindPRO. Beräkningsprogrammet Wasp har använts för att simulera vindens energiinnehåll och strömningsdynamik. Flera olika vindkraftsparkutformningar byggdes upp i WindPRO för tre scenarion. Scenarierna har olika antal vindkraftverk och varierad tornhöjd. Den ekonomiska analysen har gjorts i kalkylblad där den viktigaste ekonomiska förutsättningen var att uppnå en kalkylränta på sju procent. Framtidens elpris är en viktig, men osäker, faktor och i olika scenarier erhålls olika elpris för att uppnå den önskade kalkylräntan. I simulering av scenario 1 då parkutformning med 50 till 70 vindkraftverk med tornhöjd på 119 meter undersöktes framgick det att förslaget till parkutformning innehöll 61 vindkraftverk. Medelproduktionen för vindkraftverken i parkutformningen med 61 vindkraftverk var 10260 MWh per år. För att en parkutformning med 70 vindkraftverk ska generera en avkastning på sju procent krävs det att elpriset ökar från 331 kr/MWh till 340 kr/MWh. I simulering av scenario 2 då parkutformning med 50 till 100 vindkraftverk med blandade tornhöjder mellan 119, 139 och 159 meter undersöktes framgick det att förslaget till parkutformning innehöll 94 vindkraftverk. Medelproduktionen för vindkraftverken i parkutformningen med 94 vindkraftverk var 10920 MWh per år. För att en parkutformning med 100 vindkraftverk ska generera en avkastning på sju procent krävs det att elpriset ökar från 343 kr/MWh till 347 kr/MWh. I simulering av scenario 3 ändrades tornhöjden för samtliga vindkraftverk från scenario 2 till 159 meter. Då höjdes parkens medelproduktion till 11140 MWh per år. Det betyder att medelproduktionen ökade med 2 %. Resultatet visar att Hästkullen är ett lämpligt område för etablering av vindkraft. De viktigaste parametrarna som påverkar resultatet är elpris och vindens energiinnehåll. / The purpose of this master thesis is to optimize the electricity generation to reach as high viability as possible for the planned wind farm Hästkullen in Härnösand and Timrå municipalities. The project has been made at SCA Energy in Sundsvall. SCA is developing the wind farm Hästkullen in cooperation with EON. Investments in wind farms demands billions of Swedish crowns. Therefore, careful considerations have to be made to ensure future gains. Electricity generation calculation has to be made to make an economical assessment. At least one year´s data of wind measurements is necessary to reduce the uncertainty of the data to an acceptable level. The program WindPRO has been used to simulate the electricity generation calculations. The program Wasp has been used to simulate the energy content in the wind and fluid dynamics. Several different wind farm layouts have been implemented in three scenarios. The wind power plants have different hub heights and varying amounts in the different scenarios. The economic analysis has been made in a spreadsheet where the most important economic requirement was to gain an interest rate of seven percent. The price of electricity in the future is an important, yet uncertain, factor and different prices are obtained in various scenarios to achieve desired interest rate. In the simulation of scenario 1 when the wind farm layout with 50 to 70 wind power plants and hub height 119 meter were investigated the result showed that the suggested wind farm formation contained 61 wind power plants. The average electricity generation for the wind power plant in the layout with 61 wind power plants was 10260 MWh per year. The electricity price has to increase from 331 SEK/MWh to 340 SEK/MWh to maintain the economical requirements with a layout with 70 wind power plants. In the simulation of scenario 2 when the wind farm layout with 50 to 100 wind power plants and mixed hub heights 119, 139 and 159 meter were investigated the result showed that the suggested wind farm formation contained 94 wind power plants. The average electricity generation for the wind power plant in the layout with 94 wind power plants was 10920 MWh per year. The electricity price has to increase from 343 SEK/MWh to 347 SEK/MWh to maintain the economical requirements with a layout with 100 wind power plants. The hub height for all wind power plants that was used in scenario 2 was changed to 159 meter in scenario 3. The average electricity generation increased to 11140 MWh per year or 2 percent increase of production. The result shows that Hästkullen is a suitable location for a wind farm. The most important parameters that affect the result are the electricity price and wind energy content.

<p>Along with the rapid expansion of wind power in Sweden during the last decades the competition about favorable areas has hardened. This among other reasons has caused the projectors to look into development of wind power in forests. There are several aspects regarding fatigue loads on the constructions that are severe in complex terrain, among which turbulence is one. The levels of turbulence which are accepted in order for the turbines to face a life length exceeding 20 years are regulated by the International Electrotechnical Commission, (IEC). In order to keep the turbulence below these levels there are three major steering tools to use: The ambient turbulence decreases with height and can therefore be regulated by the hub height of the turbines. The wake-induced turbulence differs with the mutual placement of the turbines and is regulated by the layout of the park. One can also choose a turbine which is of a higher class regarding turbulence. The aim of this Master´s Degree Project is to investigate how these tools can be combined in order to keep the turbulence levels below the recommendations from IEC. The results are then to be applied to Wallenstams planned park in Skuggetorp. The results from the investigation are that the turbulence levels in forests generally are too high, even with sparse layouts and high towers. The problem is increasingly severe in large parks where the need for large separations between the turbines is evident. There is no use in increasing the separation along the dominant wind direction. The examination of Skuggetorp gives incentive to keep the distance between the turbines over 6 rotor diameters in all directions. The recommendations are to build the towers as high as technical and economical aspects can allow. The turbines should preferably be of IEC class A. There are no large wind power farms in forests that are running in Sweden at present, and the Swedish conditions cannot be compared with terrains in other countries. Whether or not wind turbines that are placed in high turbulence areas will survive for 20 years is a question to be answered in 20 years from now.</p>

Along with the rapid expansion of wind power in Sweden during the last decades the competition about favorable areas has hardened. This among other reasons has caused the projectors to look into development of wind power in forests. There are several aspects regarding fatigue loads on the constructions that are severe in complex terrain, among which turbulence is one. The levels of turbulence which are accepted in order for the turbines to face a life length exceeding 20 years are regulated by the International Electrotechnical Commission, (IEC). In order to keep the turbulence below these levels there are three major steering tools to use: The ambient turbulence decreases with height and can therefore be regulated by the hub height of the turbines. The wake-induced turbulence differs with the mutual placement of the turbines and is regulated by the layout of the park. One can also choose a turbine which is of a higher class regarding turbulence. The aim of this Master´s Degree Project is to investigate how these tools can be combined in order to keep the turbulence levels below the recommendations from IEC. The results are then to be applied to Wallenstams planned park in Skuggetorp. The results from the investigation are that the turbulence levels in forests generally are too high, even with sparse layouts and high towers. The problem is increasingly severe in large parks where the need for large separations between the turbines is evident. There is no use in increasing the separation along the dominant wind direction. The examination of Skuggetorp gives incentive to keep the distance between the turbines over 6 rotor diameters in all directions. The recommendations are to build the towers as high as technical and economical aspects can allow. The turbines should preferably be of IEC class A. There are no large wind power farms in forests that are running in Sweden at present, and the Swedish conditions cannot be compared with terrains in other countries. Whether or not wind turbines that are placed in high turbulence areas will survive for 20 years is a question to be answered in 20 years from now.

<p>The aim with this study was to collect fundamental information, and to plan, a wind</p><p>power farm in Juddhult , Småland in southern Sweden. The goal is to collect the best</p><p>available projecting planning support. The pieces of this projecting planning support</p><p>that will be presented is; Environmental Consequence Description (MKB), production</p><p>calculations, comparisons between different plant types, economic calculations, evaluate</p><p>the economy and give some farm design suggestions. The imagined wind farm will be</p><p>located in forest environment and which may cause a number of new problems. Special</p><p>interest that will be affected, where special consideration because of the forest</p><p>environmental is requested is, hunting, wetlands, ancient monuments and wind</p><p>turbulence. To perform calculations of expected energy transformation, sound-, shadowand</p><p>landscape influence the program WindPro has been used for these calculations. The</p><p>economic calculation methods used in this project is the annual method and electricity</p><p>price prognosis. Among the results some interesting KPI (Key Performince Indicator) for</p><p>the wind farm is presented. To be able to do a risk analysis three scenarios has been</p><p>created, the worst case scenario, the most likely scenario and the best possible scenario.</p>

The aim with this study was to collect fundamental information, and to plan, a wind power farm in Juddhult , Småland in southern Sweden. The goal is to collect the best available projecting planning support. The pieces of this projecting planning support that will be presented is; Environmental Consequence Description (MKB), production calculations, comparisons between different plant types, economic calculations, evaluate the economy and give some farm design suggestions. The imagined wind farm will be located in forest environment and which may cause a number of new problems. Special interest that will be affected, where special consideration because of the forest environmental is requested is, hunting, wetlands, ancient monuments and wind turbulence. To perform calculations of expected energy transformation, sound-, shadowand landscape influence the program WindPro has been used for these calculations. The economic calculation methods used in this project is the annual method and electricity price prognosis. Among the results some interesting KPI (Key Performince Indicator) for the wind farm is presented. To be able to do a risk analysis three scenarios has been created, the worst case scenario, the most likely scenario and the best possible scenario.

An accurate wind resource assessment (WRA) is crucial in energy prediction as the power is directly proportional to the wind speed cubed. This thesis analyses the discrepancy between operational assessment and WRA for a wind farm located on a moderately complex terrain in Ireland. As part of this research, a WRA was undertaken and the results were input to two wind farm design tools, WindPro and WindSim, to estimate the annual energy production. Two and a half years of data was available from a 50m met mast. The data was analysed and filtered to ascertain and limit the usage of erroneous data. The dataset was then correlated with an available online dataset utilising the Measure Correlate Predict (MCP) module in WindPro in order to estimate the long term wind resource at the site. The wind resource was then used to determine the annual energy produced at the site using both WindPro and WindSim. A loss of 8% was applied to the energy calculations for comparison with the original WRA. The results demonstrate the energy production from the original energy prediction, undertaken by a leading wind consultancy prior to construction, was overestimated by an average 10.19% over the three years of operation. The averaged wind speed at hub height in the original WRA was 8.2m/s. However, the prediction undertaken using WindPro in this study estimated an average hub height wind speed of 8.0m/s while WindSim estimated an average of 7.36m/s. These differing results had a significant contribution to the difference in Annual Energy Production (AEP). The calculated annual energy results were an overestimation of energy production by an average of 8.10% utilising WindPro, while WindSim underestimated the energy output by just 0.11%.

The aim of this study is to compare the performance of a linear model to a nonlinear model focusing on flow separation based on a critical slope value. Specifically, the WindPRO WAsP model will be compared with the WindSIM CFD model over a simulated terrain to determine the point the two models differ in relation to the inclination of the terrain. The results of this study will verify if the proposed critical slope value of roughly 17 degrees is truly representative of the limitation of the WAsP model in producing accurate results as compared to a CFD model.  Multiple similar studies have been performed using existing sites with actual met mast data as a comparison to the model outputs. Many of these cases have come up with varying results due primarily to the large number of uncontrolled factors influencing the data. This study will be designed in a fully simulated environment where all variables can be controlled, allowing for the manipulation of a single variable to understand its’ specific influence over the model. The primary variable being tested in this study will be the slope of the terrain with all other factors held constant.   Based on the outcome of 7 alternative runs with ridge heights of 100, 120, 140, 160, 180, 200, and 300 meters and respective maximum slope values of 10.31, 12.32, 14.29, 16.23, 18.14, 20, and 28.63 degrees a defined separation point at a hub height of 94 meters could not be found. Each run demonstrated correlation between wind speeds and terrain slope variations but a considerable difference in estimated wind resources was present between the linear and non-linear CFD models where any slope in terrain is present. This, as expected, increases where terrain inclination increases, but a clearly defined difference between the two models is not evident at the previously established critical slope value of approximately 17 degrees (30%).

As wind power is one of the main contributions to the energy transition, conducting the necessary production simulations during the development stage of a wind project can provide developers with an initial idea of its power generation potential. Existing wind farm production simulation studies have focused on data sources and time scales based on actual measurement wind data and annual production. This study analyses the accuracy of production simulations for two small wind farms using publicly available mesoscale wind data (NEWA, NORA3, CERRA) in WindPro software. A total of three simulations with different mesoscale data were performed for each wind farm. Annual energy production (AEP) and 12 monthly energy production (MEP) were compared to the actual data and AEP deviations and MEP root mean square error (RMSE) were calculated. Finally, the differences in accuracy between the three mesoscale data for the production simulations are discussed, as well as the consistency of the accuracy on the annual and monthly scales. The results show that the accuracy of all three mesoscale data for the Grollingbo wind farm is weak, with the AEP and MEP simulations from CERRA having the highest relative accuracy (+25.4%; 45.3). For the Räpplinge wind farm, NORA3 has the highest accuracy for both AEP and MEP simulations (+6.3%; 95.2).

Germany is one of the pioneer countries in wind turbine technology. They installed many wind turbines during the last decades and are now confronted with a shortage of land suitable for new wind parks. Now, with an estimated wind turbine service life of 20 – 25 years whole wind parks are becoming obsolete and owners have to decide whether do decommission, repower or to continue the operation of their parks. The advantages of repowering as well as the bureaucratic hurdles are outlined and evaluated. This thesis deals with the repowering potential in North Rhine-Westphalia and is analysing the technical and economical possibilities of repowering. The main objectives are to identify wind turbines eligible for repowering and also to develop repowering scenarios in order to determine their techno-economic feasibility.  The designed steps of the methodology allow the census and the subsequent implementation of the results in WindPro and RETScreen.