An enormous and urgent energy demand is predicted due to the growing global population, increase in power intensive industries, higher living standards, electrification of remote areas, and globalisation (transportation). Moreover, the global consciousness about the harmful effects of traditional methods of power generation on the environment. That, in turn, has created a need to strategically plan and develop renewable and sustainable energy generation systems. This study presents a wind resource assessment of seven locations proximate to the largest industrial hub in the Middle East, Jubail Industrial City, Kingdom of Saudi Arabia, and a Geographic Information System, GIS based model considering a multi-criteria wind farm site suitability approach for the entire Kingdom of Saudi Arabia and elsewhere. The hourly mean wind speed data at 10, 50 and 90 m above the ground level (AGL) over a period of five years was used for a meteorological station at the Industrial Area (Central) of Jubail. At the remaining six sites, the meteorological data were recorded at 10 m AGL only. Five years of wind data were used for five sites and three years of data were available for the remaining one site. At the Industrial Area (East), the mean wind speeds were found to be 3.34, 4.79 and 5.35 m/s at 10, 50 and 90 m AGL, respectively. At 50 and 90 m AGL, the availability of wind speed above 3.5 m/s was more than 75%. The local wind shear exponent, calculated using measured wind speed values at three heights, was found to be 0.217. The mean wind power density values at measurement heights were 50.92, 116.03 and 168.46 W/m2, respectively. After the assessment and comparison of wind characteristics of all seven sites, the highest annual mean wind speed of 4.52 m/s was observed at Industrial Area (East) and the lowest of 2.52 m/s at the Pearl Beach with standard deviations of 2.52 and 1.1 m/s, respectively. In general, at all sites, the highest monthly mean wind speed was observed in February/June and the lowest in September/October. The period of higher wind availability coincides with a high power demand period in the region attributable to the air conditioning load. The wind rose plots show that the prevailing wind direction for all sites was from the north-west. Weibull parameters for all sites were estimated using maximum likelihood, least-squares regression method (LSRM), and WAsP algorithm. In general, at all sites, the Weibull parameter, c, was the highest in the months of February/June and the lowest in the month of October. The most probable and maximum energy carrying wind speed was determined by all three methods. The highest value of most probable wind speed was found to be in the range of 3.2 m/s to 3.6 m/s at Industrial Area (East) and the highest value of maximum energy carrying wind speed was found to be in the range 8.6 m/s to 9.0 m/s at Industrial Area 2 (South) by three estimation methods. The correlation coefficient (R2), root mean square error (RMSE), mean bias error (MBE), and mean bias absolute error (MAE) showed that all three methods represent wind data at all sites accurately. However, the maximum likelihood method is slightly better than LSRM, followed by WAsP algorithm. The wind power output at all seven sites, from five commercially available wind turbines of rated power ranging from 1.8 to 3.3 MW, showed that Industrial Area (East) is most promising for wind farm development. At all sites, based on percentage plant capacity factor, PCF, the 1.8 MW wind turbine was found to be the most efficient. At Industrial Area (East), this wind turbine was found to have a maximum PCF of 41.8%, producing 6,589 MWh/year energy output. The second best wind turbine was 3 MW at all locations except the Al-Bahar Desalination Plant and Pearl Beach. At both of these locations, 3.3 MW was the next best option. The energy output from the 3 MW wind turbine at Industrial Area (East) was found to be 11,136 MWh/year with a PCF of 41.3%. The maximum duration of rated power output from all selected wind turbines was observed to be between 8 to 16.6% at Industrial Area 2 (South). The minimum duration of rated power output, less than 0.3% for all wind turbines, was observed at Pearl Beach. The maximum duration of zero power output of between 35 to 60% was also observed at Pearl Beach. / Thesis (PhD)--University of Pretoria, 2017. / Mechanical and Aeronautical Engineering / PhD / Unrestricted

An exponentially growing global population, power demands, pollution levels and, on the other hand, rapid advances in means of communication have made the public aware of the complex energy situation. The Kingdom of Saudi Arabia has vast open land, an abundance of fossil fuel, a small population but has always been among the front-runners where the development and utilisation of clean sources of energy are concerned. Several studies on wind, solar and geothermal sources of energy have been conducted in Saudi Arabia. Solar photovoltaic (pv) has been used for a long time in many applications such as cathodic protection, communication towers and remotely located oil field installations. Recently, a 2MW grid-connected pv power plant has been put online and much larger solar desalination plants are in planning stage. Wind resource assessment, hub height optimisation, grid-connected wind farm and hybrid power system design were conducted in this study using existing methods. Historical daily mean wind speed data measured at 8 to 12metres above ground level at national and international airports in the kingdom over a period of 37 years was used to obtain long-term annual and monthly mean wind speeds, annual mean wind speed trends, frequency distribution, Weibull parameters, wind speed maps, hub height optimisation and energy yield using an efficient modern wind turbine of 2.75MW rated power. A further detailed analysis (such as estimation of wind shear exponent, Weibull parameters at different heights, frequency distribution at different heights, energy yield and plant capacity factor and wind speed variation with height) was conducted using wind speed measurements made at 20, 30 and 40metres above ground level. As a first attempt, an empirical correlation was developed for the estimation of near-optimal hub height (HH = 142.035 * (α) + 40.33) as a function of local wind shear exponent (α) with a correlation coefficient of 97%. This correlation was developed using the energy yield from a wind turbine of 1 000kW rated power and wind speed and local exponent for seven locations in Saudi Arabia. A wind-pv-diesel hybrid power system was designed and specifications were made for a remotely located village, which is being fed 100% by diesel power generating units. The proposed system, if developed, will offset around 35% of the diesel load and therefore will result in decreased air pollution by almost the same amount. The developed wind speed maps, the frequency distributions and estimated local wind shear exponents for seven locations and energy yield will be of great help in defining the further line of action and policy-building towards wind power development and utilisation in the kingdom. The study also recommends conducting a wind measurement campaign using tall towers with wind measurements at more than one height and estimating the local wind shear exponents and developing a wind atlas for the kingdom. The study further states that a grid-connected wind farm of moderate capacity of 40MW should be developed using turbines of varying rated powers. The wind speed data was also analysed using wavelet transform and Fast Fourier Transform (FFT) to understand the fluctuation in wind speed time series for some of the stations. It is also recommended that policy-makers should take firm decision on the development of hybrid power systems for remotely located populations which are not yet connected with the grid. There are two challenges which need research: one is the effect of dust on the moving and structural elements of the wind turbines and the second is the effect of high prevailing temperatures on the performance and efficiency of the same. / Thesis (PhD)--University of Pretoria, 2012. / Mechanical and Aeronautical Engineering / PhD / Unrestricted