This paper presents the role of alternative energy technologies in displacing fossil fuels as the world's primary energy source. To that end, a CAPM-GARCH multi-factor market model is used to investigate the relationship between returns on oil and alternative energy stocks. Results show that an increase in oil prices and the broad market have a statistically significant and positive impact on alternative energy stock returns. Furthermore, the alternative energy sector is substantially more risky than the broad market but has the potential for higher returns. This highlights the infancy and inherently risky nature of the alternative energy sector today, but demonstrates the potential for substantial future investment gain as alternative energy technologies become more mature and widely available. Interestingly, estimation of the alternative energy index model indicated the presence of abnormal returns which was not the case for the solar index model, implying that the abnormal returns were generated from a different sectoral component of the alternative energy index.

The increasing demand for energy and the increased depletion rate of nonrenewable energy resources call for research on renewable alternatives. Mapping the availability of these resources is an important step for development of energy conversion projects. For this purpose, the wave power potential along the Atlantic coast of the southeastern USA, and the tidal stream power along the coast of Georgia are investigated in this study. Wave power potential is studied in an area bounded by latitudes 27 N and 38 N and longitudes 82 W and 72 W (i.e. North Carolina, South Carolina, Georgia, and northern Florida). The available data from National Data Buoy Center wave stations in the given area are examined. Power calculated from hourly significant wave heights and average wave periods is compared to power calculated using spectral wave energy density. The mean power within 50 km of the shore is determined to be low, whereas higher power is available further offshore beyond the 3500 m contour line. The tidal stream power potential along the coast of the state of Georgia is evaluated based on the NOAA tidal predictions for maximum tidal currents and three dimensional numerical modeling of the currents with Regional Ocean Modeling System (ROMS). The modeling results are validated against the available measurements. This region has low to moderate average tidal currents along most of the coast, but with the possibility of very strong local currents within its complex network of tidal rivers and inlets between barrier islands. Tidal stream power extraction is simulated with a momentum sink in the numerical models at the estuary scale to investigate effect of power extraction on the estuarine hydrodynamics. It is found that different power extraction schemes might have counterintuitive effects on the estuarial hydrodynamics and the extraction efficiency. A multi-criteria method that accounts for the physical, environmental and socioeconomic constraints for tidal power conversion schemes is proposed to select favorable locations and to rank them according to their suitability. For this purpose, the model results are incorporated into a Geographical Information System (GIS) database together with other geospatial datasets relevant to the site selection methodology. The methodology is applied to the Georgia coast and the candidate areas with potential are marked.

<p>Today, a majority of the world’s energy need is supplied through sources that are finite and, at the current usage rates, will be consumed shortly. The high energy demand and pollution problems caused by the widespread use of fossil fuels make it increasingly necessary to develop renewable energy sources of limitless duration with smaller environmental impact than the traditional energy sources.</p><p>Three fuels – rapeseed methyl ester (RME), Fischer-Tropsch (FT) diesel and FT jet fuel – derived from biomass, coal or gas were evaluated in this project. The fuel properties evaluated are in most cases listed in standards, often with recommendations, developed for biodiesel, petroleum diesel and jet fuel.</p><p>Biodiesel is monoalkyl esters, e.g. RME, produced by transesterification of triglycerides in vegetable oil and an alcohol to esters and glycerin. This produce a fuel that is suitable as a direct substitution for petroleum diesel. Biodiesel may be used in pure form or in a blend with petrodiesel. Oxidative degradation and weak low temperature performance of biodiesel are properties of concern when substituting petrodiesel with biodiesel, as was shown in this project. The experiments show that oxidative stability can be improved with a synthetic antioxidant, e.g. butylated hydroxytoluene (BHT).</p><p>The FT process converts syngas (a mixture of hydrogen and carbon monoxide) to a range of hydrocarbons. Syngas can be generated from a variety of carbon sources, e.g. coal, natural gas and biomass. The high-temperature (300-350 °C) FT process with iron-based catalysts is used for the production of gasoline and linear low molecular mass olefins (alkenes). The lowtemperature (200-240 °C) FT process with either iron or cobalt catalysts is used for the production of high molecular mass linear waxes. By applying various downstream processes, fuels suitable for substitution of petrodiesel and conventional jet fuel can be obtained. The FT fuels have lower densities than the conventional fuels. However, conclusions from this project are that most of the properties of FT fuels are better, or equal, than conventional petroleum fuels.</p>

Thesis (M.Sc.)--Victoria University of Wellington, [2008] / Includes bibliographical references.

Thesis (Ph. D.)--Rutgers University, 2009. / "Graduate Program in Materials Science and Engineering." Includes bibliographical references (p. 164-172).

Thesis (Ph. D.)--Missouri University of Science and Technology, 2009. / Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed December 15, 2009) Includes bibliographical references (p. 72-80).

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

To combat global climate change, the reduction of carbon emissions in different industries, particularly the power industry, has been gradually moving towards a low-carbon profile to alleviate any irreversible damage to the planet and our future generations. Traditional fossil-fuel-based generation is slowly replaced by more renewable energy generation while it can be harnessed. However, renewables such as solar and wind are stochastic in nature and difficult to predict accurately. With the increasing content of renewables, there is also an increasing challenge to the planning and operation of the grid. With the rapid deployment of smart meters and advanced metering infrastructure (AMI), an emerging approach is to schedule controllable end-use devices to improve energy efficiency. Real-time pricing signals combined with this approach can potentially deliver more economic and environmental advantages compared with the existing common flat tariffs. Motivated by this, the thesis presents an automatic and optimal load scheduling framework to help balance intermittent renewables via the demand side. A bi-level consumer-utility optimization model is proposed to take marginal price signals and wind power into account. The impact of wind uncertainty is formulated in three different ways, namely deterministic value, scenario analysis, and cumulative distributions function, to provide a comprehensive modeling of unpredictable wind energy. To solve the problem in off-the-shelf optimization software, the proposed non-linear bi-level model is converted into an equivalent single-level mixed integer linear programming problem using the Karush-Kuhn-Tucker optimality conditions and linearization techniques. Numerical examples show that the proposed model is able to achieve the dual goals of minimizing the consumer payment as well as improving system conditions. The ultimate goal of this work is to provide a tool for utilities to consider the demand response model into their market-clearing procedure. As high penetration of distributed renewable energy resources are most likely applied to remote or stand-alone systems, planning such systems with uncertainties in both generation and demand sides is needed. As such, a three-level probabilistic sizing methodology is developed to obtain a practical sizing result for a stand-alone photovoltaic (PV) system. The first-level consists of three modules: 1) load demand, 2) renewable resources, and 3) system components, which comprise the fundamental elements of sizing the system. The second-level consists of various models, such as a Markov chain solar radiation model and a stochastic load simulator. The third-level combines reliability indices with an annualized cost of system to form a new objective function, which can simultaneously consider both system cost and reliability based on a chronological Monte Carlo simulation and particle swamp optimization approach. The simulation results are then tested and verified in a smart grid laboratory at the University of Hong Kong to demonstrate the feasibility of the proposed model. In summary, this thesis has developed a comprehensive framework of demand response on variable end-use consumptions with stochastic generation from renewables while optimizing both reliability and cost. Smart grid technologies, such as renewables, microgrid, storage, load signature, and demand response, have been extensively studied and interactively modeled to provide more intelligent planning and management for the smart grid. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

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