During the last three decades, the hub height of wind turbines has increased from 24 to 162 meters and with an increasing demand for break-through innovations in green energy production it seems likely that this trend will continue. The meteorological preconditions for extreme-scale wind turbines are investigated for Scandinavia using 33 years of reanalysis data from MERRA (Modern-Era Retrospective Analysis for Research and Applications). Second degree polynomials are fitted to the wind and temperature profiles and evaluated at 100, 200 and 300 m above ground level (AGL). The spatial and temporal variation of average wind speed and median wind power density is studied. Simple metrics such as the wind shear and risk of icing, measured as occasions with temperature below freezing, are used to give an idea of the loads on the wind turbines. Winter is the windiest season, and generally the wind speed is highest over sea and in the Scandinavian mountain range. Going from 100 to 300 m AGL the average wind speed increases with 1 m/s over sea and 2 m/s over land. During night the wind speed increases over land but decreases over sea compared to daytime values. On average the wind shear is about 3.6 times larger in the 50-100 m layer than in the 100-300 m layer. The calculated wind field at 100 m AGL has been compared with results from the MIUU-model, developed at the Department of Meteorology, Uppsala University. The general features are captured but there are important discrepancies between the coast and the mountains in the northern part of Sweden. MERRA data has been validated in different ways, for example by comparing with measured wind speed and temperature profiles. The temperature profiles are in good agreement while the wind profiles differ significantly. It is also shown that MERRA data is not internally consistent in the mountain range, causing a large uncertainty. In future studies, the risk of icing could be explored further. Also, the distribution of sound from extreme-scale wind turbines could be investigated. / Under de senaste tre decennierna har navhöjden för vindkraftverk ökat från 24 till 162 meter och med en ökande efterfrågan på banbrytande innovationer inom produktion av grön energi är det troligt att denna trend kommer att fortsätta. De meteorologiska förutsättningarna för extremskaliga vindkraftverk i Skandinavien undersöks baserat på 33 års återanalysdata från MERRA (Modern-Era Retrospective Analysis for Research and Applications). Andragradspolynom anpassas till vind- och temperaturprofilerna och evalueras på höjderna 100, 200 och 300 meter över markytan. Variationen i rummet och med tiden av medelvindhastigheten och medianen av vindenergiintensiteten studeras. Enkla mått som vindskjuvningen och risken för nedisning, mätt som antalet tillfällen då temperaturen understiger fryspunkten, används för att ge en uppfattning om risken för belastningarna på vindkraftverken. Vintern är den årstid då det blåser mest och i allmänhet är vindstyrkan högst över hav och i fjälltrakterna. Förflyttar man sig från 100 till 300 m över markytan ökar medelvindhastigheten med 1 m/s över hav och med 2 m/s över land. Under natten ökar vinden över land men minskar över hav i jämförelse med värdena under dagen. I medeltal är vindskjuvningen 3.6 gånger större i 50-100 m skiktet jämfört med 100-300 m skiktet. Det beräknade vindfältet på 100 m över markytan har jämförts med resultat från MIUU-modellen, utvecklad vid institutionen för meteorologi, Uppsala universitet. De allmänna dragen är samma men det finns viktiga avvikelser mellan kusten och fjälltrakterna i norra Sverige. MERRA-data har validerats på olika sätt, till exempel genom att jämföra med uppmätta vind- och temperaturprofiler. Temperaturprofilerna visar god överensstämmelse men det är signifikanta skillnader mellan vindprofilerna. Det visas också att MERRA-data inte är konsistent i fjälltrakten, vilket medför en stor osäkerhet. I framtida studier kan risken för nedisning studeras utförligare liksom ljudutbredningen från extremskaliga vindkraftverk.

Recently wind resource assessment studies have become an important research tool to identify the possible wind farm locations.  In this thesis work technical analysis was carried out to determine the wind resource potential of two candidate sites in Eritrea with help of suitable software tools. The first site is located along the Red Sea cost which is well known for its wind resource potential, whereas the second site is located in the central highlands of Eritrea with significant wind resource potential. Detailed wind resource assessment, for one year hourly weather data including wind speed and wind direction, was performed for the two candidate sites using MS Excel and MATLAB. The measured wind data at Assab wind site showed that the mean wind speed and power density was 7.54 m/s and 402.57 W/m2 , whereas the mean wind speed and mean power density from Weibull distribution was 7.51 m/s and 423.71 W/m2 respectively at 80m height. Similarly, the measured mean wind speed and mean power density at Dekemahre wind site was obtained to be 5.498 m/s and 141.45 W/m2, whereas the mean wind speed and mean power density from Weibull distribution was 5.4859m/s and 141.057W/m2 respectively. Based on the analysis results Assab wind site classified as wind class-III and Dekemhare as wind class-I.  Wind farm modeling and Annual Energy Production (AEP) estimation was performed for E-82 & E-53 model turbines from Enercon Company with the help of MATLAB and Windpro software. The analysis revealed that Assab wind farm was an ideal site for wind energy production with capacity factor (CF) 53.4% and 55% for E-82 and E-53 turbines respectively. The gross and net AEP for turbine E-82 at Assab wind farm was 469.5 GWh and 446.025 GWh respectively with 95% park efficiency. Similarly, the analysis showed that the CF in Dekemhare site was very low with typical value 14.2% and 15.26% for E-82 and E-53 turbines respectively. The gross and net AEP of that site for model turbine E-53 was 53.5 GWh and 50.825 GWh respectively with 5% wake loss. Finally, a simplified economic analysis was carried out to determine the economic feasibility of possible wind power projects in both sites by assuming investment cost 1600 €/kW for E-82 turbine and 2000 €/kW for E-53 turbine. The total wind farm investment cost was found to be 215.85 and 107.93 Million Euro for E-82 and E-53 model turbines respectively. The levelized cost of energy at Assab and Dekemhare wind farm for E-82 model turbine was 0.0307 €/kWh and 0.5526 €/kWh respectively. The analysis result show that the levelized cost of energy in Dekemhare wind fasrm was much higher than that of Assab wind farm.

Wind power presently plays a minor role in Western Canada as compared to hydroelectric power in British Columbia and coal and natural gas thermal power generation in Alberta. However, ongoing reductions in the cost of wind power generation facilities and the increasing costs of conventional power generation, particularly if the cost to the environment is included, suggest that assessment of the present and future wind field in Western Canada is of some importance. To assess present wind power, raw hourly wind speeds and homogenized monthly mean wind speeds from 30 stations in Western Canada were analyzed over the period 1971-2000 (past). The hourly data were adjusted using the homogenized monthly means to attempt to compensate for differences in anemometer height from the standard height of 10m and changes in observing equipment at stations. A regional reanalysis product, the North American Regional Reanalysis (NARR), and simulations conducted with the Canadian Regional Climate Model (CRCM) driven with global reanalysis boundary forcing, were compared to the adjusted station wind-speed time-series and probability distributions. The NARR had a better temporal correlation with the observations, than the CRCM. We posit this is due to the NARR assimilating regional observations, whereas the CRCM did not. The NARR was generally worse than the CRCM in reproducing the observed speed distribution, possibly due to the crude representation of the regional topography in NARR. While the CRCM was run at both standard (45 km) and fine (15 km) resolution, the fine grid spacing does not always provide better results: the character of the surrounding topography appears to be an important factor for determining the level of agreement. Multiple simulations of the CRCM at the 45 km resolution were also driven by two global climate models (GCMs) over the periods 1971-2000 (using only historic emissions) and 2031-2060 (using the A2 emissions scenario). In light of the CRCM biases relative to the observations, these simulations were calibrated using quantile-quantile matching to the adjusted station observations to obtain ensembles of 9 and 25 projected wind speed distributions for the 2031-2060 period (future) at the station locations. Both bias correction and change factor techniques were used for calibration. At most station locations modest increases in mean wind speed were found for most of the projected distributions, but with a large variance. Estimates of wind power density for the projected speed distributions were made using a relationship between wind speed and power from a CRCM simulation for both time periods using the 15km grid. As would be expected from the wind speed results and the proportionality of wind power to the cube of wind speed, wind power at the station locations is more likely than not to increase in the 2031-2060 period from the 1971-2000 period. Relative changes in mean wind speeds at station locations were found to be insensitive to the station observations and choice of calibration technique, suggesting that we estimate relative change at all 45km grid points using all pairs of past/future mean wind speeds from the CRCM simulations. Overall, our results suggest that wind energy resources in Western Canada are reasonably likely to increase at least modestly in the future. / Graduate / 0725 / 0608 / jtdaines@uvic.ca