Thesis supervisor: Andrew Kusiak. Includes bibliographic references (p. 141-147).

Thesis (Ph.D.)--Aberdeen University, 2009. / Title from web page (viewed on Feb. 18, 2010). Includes bibliographical references.

Thesis (M.A.) in History--University of Maine, 2003. / Includes vita. Includes bibliographical references (leaves 69-71).

Thesis (Ph. D.)--Aerospace Engineering, Georgia Institute of Technology, 2007. / Samual V. Shelton, Committee Member ; P.K. Yeung, Committee Member ; Lakshmi N. Sankar, Committee Chair ; Stephen Ruffin, Committee Member ; Marilyn Smith, Committee Member.

Thesis (MScIng)--Stellenbosch University, 2003. / ENGLISH ABSTRACT: The effect of topography and terrain on wind is examined in order to ensure that the wind turbine positioning will encourage a greater availability of wind energy to it. Maximum power point tracking methods are presented whereby the loading on the wind turbine is controlled to ensure that the maximum available energy from the wind is captured. The wind turbine system is modelled and used in simulations to evaluate the three proposed maximum power point trackers, named anemometer control, calculation control and constant step control for the purpose of this thesis. An additional analog system is also created whereby the complete wind turbine system is able to be simulated. An inverter is used to replicate the generator and the loading is controlled using an active rectifier since this will be used on the practical system. The results from the simulations and analog system are presented whereby one of the trackers is shown to be inadequate and the other two trackers are shown to be close to ideal. The appeal of the calculation method is in the redundancy of an anemometer making it attractive to less expensive, small-scale systems. / AFRIKAANSE OPSOMMING: Die invloed van die topografie en die terrein op die dinamika van wind word ondersoek om sodoende te verseker dat die posisionering van wind turbienes 'n beter effektiwiteit van wind energie oordrag sal bewerkstellig. Maksimum drywingspunt volger metodes word bespreek sodat die lading op die wind turbiene beheer kan word om sodoende te verseker dat die maksimum wind energie oorgedra kan word. Die wind turbiene stelsel word gemodeleer en geimplimenteer om die drie voorgestelde maksimum drywingspount volgers te evalueer, naamlik windspoedbeheer, berekening-beheer en konstantestap-beheer vir die doeleindes van hierdie tesis. 'n Adissionele analoog stelsel is ontwerp waarmee die volledige wind turbiene stelsel gesimuleer kan word. 'n Omsetter word gebruik om die generator na te boots en die belading word beheer deur middel van 'n aktiewe gelykrigter soos gebruik 'n praktese stelsel. Resultate van die simulasies en die analog stelsel is verskaf om te bewys dat een van die volg-metodes onvoldoende volging bewerkstellig, en die ander twee nabyaan ideale volging bewerkstellig. Dit is getoon dat die berekening metode meer aantreklik is vir kleinskaal stelsels, aangesien 'n windspoedsensor onnodig is.

Energy is integral to the quality of life of any society. However, meeting the demand for energy sustainably is the main challenge facing humanity. In general, non-renewable energy resources are used to supply the ever increasing energy demand. However, the extraction and processing of these resources is accompanied by the production of wastes which are a health hazard and impact negatively on climate change. Considering the finite nature of non-renewable sources, the environmental concerns which are associated with their usage and ensuring energy security, renewable energy sources have been brought in the energy supply chain. Wind energy is one of the renewable energy sources which has been supplying electrical energy to the ever increasing energy demand of humanity. Wind energy technology is a mature technology which over and above the bare (conventional) wind turbine technology has seen the development of duct augmented wind turbines. Ducts are used to encase wind turbine rotors to augment the power output of wind turbines especially in low wind speed areas. Though the technology has been under study for decades now, research indicates that there is no known model to estimate the power output of a diffuser augmented wind turbine. This thesis presents the development of the conical Diffuser Augmented Wind Turbine (DAWT) power output estimation model and its validation.

Marine renewable energy developments (MREDs) are becoming an increasing feature of the marine environment. Scotland has considerable potential for generating energy from the marine environment in the form of extensive wind, wave and tidal-stream resources. Scotland also hosts numerous internationally important breeding populations of seabirds and Scottish territorial waters represent a key overwintering area for many species. EU legislation requires that MREDs do not damage the integrity of protected seabird populations but potential effects of MREDs on seabirds are not yet fully understood. This thesis aims to address gaps in knowledge regarding how MREDs may affect seabird populations. I generate vulnerability and confidence indices to predict the effects of offshore wind, wave and tidal-stream renewable energy developments on Scottish seabird populations; track the movements of a seabird species identified as lacking in data to better understand overlap with MREDs; and investigate seabird use of a high current flow environment leased as a tidal-stream energy development site. Overall, this thesis indicates that seabird responses to MREDs are likely to be species-specific and will vary dependent on the development location and design of the energy generating technology. My findings indicate that effects of MREDs will differ dependent on individual foraging strategies, age and life stage of individuals, which implies that MREDs are likely to differently affect subsections of seabird populations.

Horizontal axis wind turbines are by far the most common and well understood forms of wind turbine. Typically a large amount of research and development has been invested in the technology of large scale wind turbines. Unfortunately, development of small machines (rotor diameter smaller than 10 metres) has not been as forthcoming. The advantages of small turbines are that they are accessible to the individual consumer and they are a very attractive project for the home builder. The disadvantage of small turbines is that due to the negative influence of economies of scale, they tend to be costly in relation to their power output and suffer from a long-term return on investment. Furthermore, trends in the wind industry have shown that smaller machines tend to be relatively simple devices that have been developed with very little research and development. As a result, small turbines can be inefficient, unreliable and expensive to maintain. In many cases rotor design is less than optimal, with very little blade refinement. This is especially critical for small rotors due to low Reynolds Number operation. Further exacerbating the problem is that the rotors are typically not well matched to the generator. In many cases the machines are not suited to the wind speed range in which they are designed to operate, reducing the financial viability due to poor performance. It is envisaged that by applying optimising techniques and automating some of the design complexities into a software design tool, more cost-effective and viable machines can be developed that will deliver improved performance and therefore become more financially viable.

In this study we conduct wind resource assessment to evaluate the annual energy production of a wind turbine. To estimate energy production of a wind turbine over a period of time, the power characteristics of the wind turbine are integrated with the probabilities of the wind speed expected at a chosen site. The first data set was obtained from a wind farm in Denmark. We propose several probability density functions to model the distribution of the wind speed. We use techniques from nonlinear regression analysis to model the power curve of a wind turbine. The best fit distribution model is assessed by performing numeric goodness–of–fit measures and graphical analyses. Johnson’s bounded (SB) distribution provides the best fit model with the smallest Kolmogorov–Smirnov (K-S) test statistic . 15. The four parameter logistic nonlinear regression (4PL) model is determined to provide the best fit to the power curve data, according to the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). The estimated annual energy yield is compared to the actual production of the wind turbine. Our models underestimate the actual energy production by a 1 difference. In Chapter Six we conduct data processing, analyses and comparison of wind speed distributions using a data set obtained from a measuring wind mast mounted in Humansdorp, Eastern Cape. The expected annual energy production is estimated by using the certified power curve as provided by the manufacturer of the wind turbine under study. The commonly used Weibull distribution is determined to provide the best fit distribution model to our selected models. The annual energy yield is estimated at 7.33 GWh, with a capacity factor of 41.8 percent.

The wind industry has arrived at a state of technological maturity and is occasionally already today cost-competitive to conventional sources of energy. This thesis investigates the process of innovation that took place within the industry. A theoretical background into economical theory of innovation together with a status quo assessment of today's wind industry serves as introduction to the topic. In the analytical part, inducement mechanisms and functions of technological development will be identified as crucial drivers for innovation within the sector. The key findings of this thesis lead to conclude that it is now the responsibility of the industry to becoming fully cost-competitive to conventional sources. The advancement of technological lifecycle will primarily depend on turbine manufacturers and their capability to drive innovation more independently from governments.