Human activities pressure the socio-ecological system that maintains our quality of life by causing global repercussions such as climate change. The energy system, a major contributor to climate change due to its reliance on fossil fuels makes the transition to sustainable energy an imperative. The purpose of this thesis is to identify focus areas that support businesses in changing their energy habits. This leads to the research question: How can local businesses on small islands become drivers in the transition towards sustainable energy? The Framework for Strategic Sustainable Development (FSSD) enabled us to employ a systems perspective, place sustainable energy into a comprehensive and scientific definition of sustainability, and align our findings’ relevance to a strategic approach. The Motivation-capability-implementation- results (MCIR) framework was a suitable tool for our needs. For data collection purposes, literature analysis and a case study on the French island Île d’Oléron were conducted. The main findings of the thesis are that in order for businesses to become drivers in the transition to sustainability energy, Awareness, Consistent and Proactive Political System, Engaged Community, Supporting Infrastructure, Financial Capability and Agile Approach need to be addressed. The six focus areas cover the many barriers and enablers for achieving sustainable energy.

The wind energy industry in the U.S. has seen robust growth within the last two decades. The amount of renewable resources available throughout the U.S. is substantial, and as renewable energy penetration approaches a significant proportion of total electricity generation, grid operators and utilities will be presented with a myriad of challenges. Such is the case in wind’ rich Texas, where the rate of wind installations surpasses every other state and rivals that of China. By the end of 2009, the ERCOT region of Texas had approximately 9000 MW installed, serving 6.5% of the annual electricity load . The intermittent nature of wind energy can place a burden on existing generators as they are increasingly relied on to provide regulation of power, frequency control and back-up energy services when wind production is low. Exacerbating the difficulty of integrating wind energy is the mismatch of wind generation and electricity demand. Although Texas is blessed with plentiful wind resources, the majority of energy produced typically occurs at night when electricity demands are low. The result is transmission congestion that prevents cost effective generators from serving load. Despite these integration difficulties, ERCOT is paving the way forward with transformative infrastructure plans and proactive rulemaking. This report provides a background on the state of the wind energy industry in the U.S., with a review of power system operation strategies and wind integration best practices. With that context, this study concludes that ERCOT’s electricity market operations, transmission plans, and Texas’ renewable energy policies will act to reasonably and reliably accommodate wind generation capacity that serves over 15% of annual load by 2030. / text

The World Energy Outlook (WEO), an annual publication from the International Energy Agency (IEA), is often considered to be the most authoritative source of future energy scenarios for policy decision makers. The demand and supply scenarios for oil, one of the most irreplaceable resources in the global energy system, are central in each report. For the last decade, the outlook for oil supply in 2030 in the main IEA scenario has been reduced by almost 20 million barrels per day. The aim of this study is to examine the revisions to the oil supply scenarios, both at global and individual country level, and note if and how the IEA has motivated these revisions. The accuracy of past WEO scenarios is quantified by track record analysis and the latest WEO scenario is assessed in detail in relation to current scientific literature. Finally, implications of the latest WEO scenario for the long term oil supply are assessed. It is noted that the IEA generally motivate upward revisions to their scenarios, while downward revisions are often left unmentioned. Some recent revisions are attributed to the financial crises of 2008 and the largest revision in absolute terms is the gradual downward revision of OPEC production motivated by an underestimation of key producing countries’ will and ability to expand capacity. The track record analysis indicates that the accuracy of the IEA scenarios has increased on a five year prediction basis following the extended methodology applied in the WEO 2008. The analysis also shows that the accuracy of scenarios decrease with time. On a ten year horizon, the mean absolute error for the IEA aggregate ‘World oil supply” was estimated to 8.2%. The WEO2013 ‘New Policies Scenario’, with a time frame of 2012-2035, was assessed using decline and depletion rate analysis, and compared to empirically proven rates. The scenario was found to provide a realistic but optimistic view of the future of oil supply. An alternative scenario, with depletion rates in line with the fastest observed regional rates, resulted in somewhat lower production rates throughout the scenario time frame. A long term extrapolation to year 2100 of the WEO 2013 scenario, based strictly on resource and production data from the WEO reports, indicated that oil supply will reach a peak in 2035 and then enter decline for the remainder of the century. A sensitivity analysis showed that changes to the assumed resource base only moves the peak by a few years, but has a significant effect on the rate of the following decline.

This thesis focuses on determining the potential of bio-energy crops to contribute to Europe’s future energy needs and to reduce future greenhouse gas emissions. This requires an end-to-end (seed to exhaust gas) analysis of the crop production and enabling technology in terms of energy use and greenhouse gas emissions. The starting point of this research was to consider which energy crops had the potential to grow in future European climate scenarios and to determine those for which models did not exist to make this prediction. <i>Miscanthus</i> was identified as a relatively new crop with 15 years of European growing experience but with limited previous model development.  MISCANMOD, a simple model of <i>Miscanthus</i> crop growth, was improved and rewritten in FORTRAN so that it could be interfaced to use climate scenario, soil property and land use data bases to predict energy yields for current and future climate scenarios. A greenhouse gas emissions and energy balance model was added to investigate the sustainability of <i>Miscanthus</i> as a bio-energy crop. This model was combined with data from other energy crop predictions to determine the energy yields and GHG mitigation of different crops for the various scenarios of future climate, each considering the soil conditions, land available and climatic conditions. We conclude that <i>Miscanthus</i> is the crop with the highest energy yield and largest carbon mitigation potential of all the available energy crops, and that the maximum amount of primary energy that could be produced by bio-energy crops in Europe would represent only 12% of EU 25’s primary energy needs. The carbon intensity of such energy is estimated to be 24% of that for gas. To achieve this level of energy production we show that it is necessary to develop drought and frost resistant hybrids to increase the range of the <i>Miscanthus</i> crop for current and future climate scenarios. This demonstrates that bio-energy is not a panacea but must be considered as part of the strategy to achieve sustainable energy whilst mitigating greenhouse gas emissions.

Energy conservation can mitigate significant issues such as climate change and fuel poverty, yet the determinants of this behaviour are poorly understood. It is important to understand the antecedents of energy conservation in order to effectively stimulate this behaviour in society. Traditional models have focused on normative and intentional processes to explain environmental behaviour, but have proven largely unsuccessful for predicting energy use. Considering that day-to-day energy behaviour is likely to be habitual and context dependent, models such as the Comprehensive Action Determination Model (CADM, Klöckner & Blöbaum, 2010), which have integrated these factors with more traditional antecedents of behaviour, may better account for people’s actions. The early research in this thesis tests the application of this model to energy saving behaviour using a mixed-methods approach. Findings show that such a model is suitable to account for the drivers of energy behaviour, particularly because of the important role of habits and situational influences on this behaviour. Although this model can successfully predict daily energy behaviours that involve the routine curtailment of household energy use, one-off energy efficiency investment behaviours are unlikely to be determined by the variables considered by the CADM. That is, these behaviours may be more dependent on people’s understanding of the energy consumption in their household, or their energy literacy. Therefore, the second part of this thesis investigates the cognitive processes that inform conscious energy judgements to explore the antecedents of this energy literacy. The studies in this thesis uncover an unprecedented variety of energy judgement heuristics in this decision-making process, and these heuristics are further investigated, again using various methods. This thesis concludes that, to maximally facilitate energy conservation, the habitual and situational antecedents of energy saving behaviour, as captured in such frameworks as the CADM, need to be considered alongside the cognitive processes that shape people’s energy literacy when designing effective energy conservation interventions that target both routine and non-routine actions.

No description available.

The built environment is responsible for a large portion of total energy use and emissions. A large portion comes from the buildings themselves, but also the transportation system to move people around. As global populations grow, and more people migrate to cities, it is critically important that new city growth is done in the most sustainable manner possible. The typical North American pattern of urban growth is urban sprawl, characterized by single use type zoning, low density, transportation system dominated by personal vehicles, and poor public transit. Urban sprawl has numerous downsides, including poorer energy efficiency in buildings and infrastructure, more congestion and higher emission from vehicles, as well as many negative health effects. This thesis presents the concept of a Mothership, a large, high-density mixed-use building designed to combat urban sprawl and minimize energy use and emissions of the built environment. A mothership is designed to provide all the amenities and housing of a typical suburb for 10,000 people. The analysis in this thesis employ building simulation tools to model various mothership designs and analyse the operational and embodied energy and carbon emissions for each design, and compare it to base cases of more traditional building use types such as single detached homes, and different types of apartment buildings. The effect of high-performance building envelopes and other building materials on operational and embodied energy and emissions are analysed. A multi objective optimization analysis is performed to determine which technologies and combinations of technologies provide the lowest cost solution to meet the mothership’s energy demands while also minimizing emissions. The mothership’s effect on transportation emissions is also investigated. The building’s mixed-use nature allows trips to be satisfied within walking distance in the building. The high concentration of people makes for a good anchor load for public transportation, so the emissions reductions of implementing a bus rapid transit system from the mothership to the central business district is estimated. To reduce transportation emissions further, the effect of an electric car share fleet for mothership residents use is also quantified. The energy system of a mothership is optimized, along with base cases of single detached homes, under numerous scenarios. These scenarios are designed to explore how the energy system changes in an attempt to answer a series of research questions. Some of the measures explored are a high carbon tax, net metering, and emissions limits of net zero, and negative emissions with two different electrical grid carbon intensities. Results showed that a highly insulated, timber framed mothership can achieve very high reductions in energy use and emissions. Overall it showed reductions of 71%, 73%, and 74% in operational energy, embodied energy and embodied carbon respectively, over a baseline case of single detached homes. It was estimated that transportation emissions could be reduced by 58% through the mixed-use development reducing the number of trips and electrically powered transportation vehicles and bus rapid transit. This gives a combined total emissions reduction of 61%. Energy system optimization showed that the mothership design in achieved far lower costs and emissions (4 and 8.7 times lower respectively) than the base case of single detached homes. Of the mothership cases examined, the most expensive case was the one which had a carbon tax, with an annualized cost of $4.3 million. The case with the lowest annualized cost was one with, among other factors, a net zero carbon emissions restriction (annualized cost of $3.08 million. Many of the cases had negative operating costs due to the sale of renewable energy or carbon credits. This illustrates that the integration of renewable energy technologies is not only beneficial for reducing emissions but can also act as an income pathway for energy systems. / Graduate

Over the last decade, wind penetration in the Pacific Northwest has increased rapidly. The variable nature of this massive new resource has increased stress on the hydropower resource to the point where system limits are currently being reached. In order to cultivate continued growth of the wind energy industry both in the Pacific Northwest and the rest of the world, something must be added to help mitigate the effects of the variability of wind power. This research aims to show what can be done by adding energy storage to a wind farm. A novel model predictive control structure has been created with the focus of increasing the dispatchability and reliability of wind farm power output along with allowing participation in frequency regulation. First, the effectiveness of the addition of energy storage with simple control is explored. This is followed by a study on the performance of the system when predictive control is added. Finally, a cost analysis is performed to assess the level of savings and potential profitability of the simulated system. Conclusions support the use of an energy storage resource for more reliable wind farm performance. However, storage technologies are still approaching the price point needed to ensure profitability. / Graduation date: 2012

Thesis (M.A. (Human Movement Science))--North-West University, Potchefstroom Campus, 2009.

The thesis project explores the use of an optimization methodology for selecting the lowest monetary cost combinations of technologies to meet a set operational energy efficiency targets for buildings. The optimization approach, which is operated on a normative energy model, is compared with existing prescriptive methodologies for selecting technology combinations and a metric is developed for ranking their effectiveness; the E/C Ratio. The energy savings/ cost ratio is also the objective function that the optimization algorithm is set to maximize. The optimization routine is coded in to a custom MATLAB script and is used in two case studies to optimize a proto-typical Korean apartment and office building. The optimization methodology finds technology combinations that are much more cost effective than the prescriptive methodology at meeting an energy savings target and can generically be applied to other buildings given a palette of technology alternatives and the corresponding cost data.