O setor de transporte é um exemplo de atividade econômica que depende fundamentalmente das cadeias produtivas do petróleo, gás natural e biocombustíveis para sua operação, além de ser um dos principais consumidores da energia primária do país. Portanto, qualquer melhoria nos processos de produção e uso final dos combustíveis veiculares, repercute favoravelmente tanto na utilização dos recursos energéticos e o desempenho do setor, quanto no impacto ambiental e na economia nacional. Nesse sentido, faz-se necessário o desenvolvimento de uma metodologia que permita avaliar as diferentes rotas de produção e uso final, para determinar as principais fontes de degradação da energia e quantificar o impacto ambiental por meio de uma ferramenta apropriada. Uma valiosa ferramenta é a análise exergética ampliada, a qual provê uma oportunidade de quantificar os requerimentos exergéticos totais e não renováveis e as eficiências globais e, desse modo, perseguir e priorizar o uso daquelas fontes de energia mais favoráveis e amigáveis com o meio ambiente. A exergoeconomia, que visa à distribuição racional dos custos exergéticos entre os diversos produtos de uma mesma planta, usa a quantidade de exergia de cada produto como base para a distribuição da exergia despendida no respectivo processo. Desta forma, neste trabalho se apresenta uma análise comparativa sobre as rotas de produção e uso final dos combustíveis derivados do petróleo e o gás natural (inclusive o hidrogênio produzido da reforma a vapor), etanol, biodiesel, além da análise da geração e distribuição da eletricidade na matriz elétrica brasileira. Propõe-se o uso dos custos exergéticos unitários renováveis e não renováveis e as emissões de CO2 como indicadores para avaliar a intensidade exergética renovável e não renovável, o impacto ambiental e o desempenho termodinâmico no uso final. Este procedimento permite hierarquizar os diferentes processos de conversão de energia na produção e uso final de combustíveis veiculares, a fim de determinar as melhores opções para o setor de transporte. / Transportation sector is an example of economic activity that fundamentally depends on the supply chains of oil, natural gas and biofuels for its operation, as well as being a major consumer of primary energy in the country. Therefore, any improvement that could be achieved in the vehicle fuels production and end use processes, favorably affects both the use of energy resources and industry performance, as well as the environmental impact and the national economy. Accordingly, it is necessary to develop a methodology based on a suitable tool to evaluate the different routes of fuel production and end use, so that the main sources of energy degradation and the environmental impact can be determined and quantified. A valuable tool that serves that purpose is the extended exergy analysis, which provides an opportunity to quantify the total and non-renewable exergy requirements and overall efficiencies, and thereby pursue and prioritize the use of the most environmentally friendly sources of energy. Exergoeconomy, which attempts to rationally distribute the exergy cost among the several products of a single plant, uses the amount of exergy of each product as the basis for the distribution of exergy expended in the respective process. Thus, this work presents a comparative analysis of the production routes and end use of vehicles fuels derived from petroleum and natural gas (including hydrogen produced from methane steam reforming), ethanol, biodiesel, besides of the analysis of generation and distribution of electricity in the Brazilian electricity mix. Moreover, the renewable and non-renewable unit exergy costs and CO2 emissions are proposed as indicators, able to assess the renewable and non-renewable specific exergy consumption, the environmental impact and the thermodynamic performance of transportation sector. This procedure allows to hierarchize the exergy conversion processes in the production and end use of transportation fuels, in order to determine the best options for the transportation sector.

This dissertation explores the potential of renewable energy and efficiency strategies to solve the energy challenges faced by the people living in the biosphere reserve of El Vizcaíno, which is located in the North Pacific region of the Mexican state of Baja California Sur. This research setting provides a practical analytical milieu to understand better the multiple problems faced by practitioners and agencies trying to implement sustainable energy solutions in Mexico. The thesis starts with a literature review (chapter two) that examines accumulated international experience regarding the development of renewable energy projects as a prelude to identifying the most salient implementation barriers impeding this type of initiatives. Two particularly salient findings from the literature review include the importance of considering gender issues in energy analysis and the value of using participatory research methods. These findings informed fieldwork design and the analytical framework of the dissertation. Chapter three surveys electricity generation as well as residential and commercial electricity use in nine coastal communities located in El Vizcaíno. Chapter three summarizes the fieldwork methodology used, which relies on a mix of qualitative and quantitative research methods that aim at enabling a gender-disaggregated analysis to describe more accurately local energy uses, needs, and barriers. Chapter four describes the current plans of the state government, which are focused in expanding one of the state’s diesel-powered electricity grids to El Vizcaíno. The Chapter also examines the potential for replacing diesel generators with a combination of renewable energy systems and efficiency measures in the coastal communities sampled. Chapter five analyzes strategies to enable the implementation of sustainable energy approaches in El Vizcaíno. Chapter five highlights several international examples that could be useful to inform organizational changes at the federal and state level aimed at fostering renewable energy and efficiency initiatives that enhance energy security, protect the environment, and also increase economic opportunities in El Vizcaíno and elsewhere in Mexico. Chapter six concludes the thesis by providing: a summary of all key findings, a broad analysis of the implications of the research, and an overview of future lines of inquiry.

This dissertation explores the potential of renewable energy and efficiency strategies to solve the energy challenges faced by the people living in the biosphere reserve of El Vizcaíno, which is located in the North Pacific region of the Mexican state of Baja California Sur. This research setting provides a practical analytical milieu to understand better the multiple problems faced by practitioners and agencies trying to implement sustainable energy solutions in Mexico. The thesis starts with a literature review (chapter two) that examines accumulated international experience regarding the development of renewable energy projects as a prelude to identifying the most salient implementation barriers impeding this type of initiatives. Two particularly salient findings from the literature review include the importance of considering gender issues in energy analysis and the value of using participatory research methods. These findings informed fieldwork design and the analytical framework of the dissertation. Chapter three surveys electricity generation as well as residential and commercial electricity use in nine coastal communities located in El Vizcaíno. Chapter three summarizes the fieldwork methodology used, which relies on a mix of qualitative and quantitative research methods that aim at enabling a gender-disaggregated analysis to describe more accurately local energy uses, needs, and barriers. Chapter four describes the current plans of the state government, which are focused in expanding one of the state’s diesel-powered electricity grids to El Vizcaíno. The Chapter also examines the potential for replacing diesel generators with a combination of renewable energy systems and efficiency measures in the coastal communities sampled. Chapter five analyzes strategies to enable the implementation of sustainable energy approaches in El Vizcaíno. Chapter five highlights several international examples that could be useful to inform organizational changes at the federal and state level aimed at fostering renewable energy and efficiency initiatives that enhance energy security, protect the environment, and also increase economic opportunities in El Vizcaíno and elsewhere in Mexico. Chapter six concludes the thesis by providing: a summary of all key findings, a broad analysis of the implications of the research, and an overview of future lines of inquiry.

During the past years, the usage of wood as construction material in multistory applications has increased. In Germany and Sweden, various activities have been, and are about to be performed, to accentuate and improve the position of wooden multistory houses. In line with that, this thesis tries to contribute to the understanding of how consumers perceive durable products; in the contextual frame of how German and Swedish consumers perceive wooden multistory houses. It was hypothesized that consumers’ perceptions on durable products differ, depending on their age, income, national and within-country habitation. Based on the Means-End Chain Theory, the Association Pattern Technique has been further developed to collect and analyze data for two samples. In Germany and Sweden, 31 respectively 34 laddering interviews have been carried out which formed the base for a survey-study in each country. Here, 229 surveys were received from German, and 503 from Swedish respondents. The results show that age, income, national and within-country habitation have significant impact on consumers’ perceptions of wooden multistory houses. Moreover, the extension of the Association Pattern Technique was validated. It allowed for additional data to be gathered, which can be regarded as rather important, since it appeared in the most dominant Means-End Chains of the respondents in both Germany and Sweden. This helps to understand consumers’ underlying reasons why one product is favoured over another.

O setor de transporte é um exemplo de atividade econômica que depende fundamentalmente das cadeias produtivas do petróleo, gás natural e biocombustíveis para sua operação, além de ser um dos principais consumidores da energia primária do país. Portanto, qualquer melhoria nos processos de produção e uso final dos combustíveis veiculares, repercute favoravelmente tanto na utilização dos recursos energéticos e o desempenho do setor, quanto no impacto ambiental e na economia nacional. Nesse sentido, faz-se necessário o desenvolvimento de uma metodologia que permita avaliar as diferentes rotas de produção e uso final, para determinar as principais fontes de degradação da energia e quantificar o impacto ambiental por meio de uma ferramenta apropriada. Uma valiosa ferramenta é a análise exergética ampliada, a qual provê uma oportunidade de quantificar os requerimentos exergéticos totais e não renováveis e as eficiências globais e, desse modo, perseguir e priorizar o uso daquelas fontes de energia mais favoráveis e amigáveis com o meio ambiente. A exergoeconomia, que visa à distribuição racional dos custos exergéticos entre os diversos produtos de uma mesma planta, usa a quantidade de exergia de cada produto como base para a distribuição da exergia despendida no respectivo processo. Desta forma, neste trabalho se apresenta uma análise comparativa sobre as rotas de produção e uso final dos combustíveis derivados do petróleo e o gás natural (inclusive o hidrogênio produzido da reforma a vapor), etanol, biodiesel, além da análise da geração e distribuição da eletricidade na matriz elétrica brasileira. Propõe-se o uso dos custos exergéticos unitários renováveis e não renováveis e as emissões de CO2 como indicadores para avaliar a intensidade exergética renovável e não renovável, o impacto ambiental e o desempenho termodinâmico no uso final. Este procedimento permite hierarquizar os diferentes processos de conversão de energia na produção e uso final de combustíveis veiculares, a fim de determinar as melhores opções para o setor de transporte. / Transportation sector is an example of economic activity that fundamentally depends on the supply chains of oil, natural gas and biofuels for its operation, as well as being a major consumer of primary energy in the country. Therefore, any improvement that could be achieved in the vehicle fuels production and end use processes, favorably affects both the use of energy resources and industry performance, as well as the environmental impact and the national economy. Accordingly, it is necessary to develop a methodology based on a suitable tool to evaluate the different routes of fuel production and end use, so that the main sources of energy degradation and the environmental impact can be determined and quantified. A valuable tool that serves that purpose is the extended exergy analysis, which provides an opportunity to quantify the total and non-renewable exergy requirements and overall efficiencies, and thereby pursue and prioritize the use of the most environmentally friendly sources of energy. Exergoeconomy, which attempts to rationally distribute the exergy cost among the several products of a single plant, uses the amount of exergy of each product as the basis for the distribution of exergy expended in the respective process. Thus, this work presents a comparative analysis of the production routes and end use of vehicles fuels derived from petroleum and natural gas (including hydrogen produced from methane steam reforming), ethanol, biodiesel, besides of the analysis of generation and distribution of electricity in the Brazilian electricity mix. Moreover, the renewable and non-renewable unit exergy costs and CO2 emissions are proposed as indicators, able to assess the renewable and non-renewable specific exergy consumption, the environmental impact and the thermodynamic performance of transportation sector. This procedure allows to hierarchize the exergy conversion processes in the production and end use of transportation fuels, in order to determine the best options for the transportation sector.

Energy forms a vital input and critical infrastructure for the economic development of countries and for improving the quality of life of people. Energy is utilized in society through the operation of large socio-technical systems called energy systems. In a growing world, as the focus shifts to better access and use of modern energy sources, there is a rising demand for energy. However, certain externalities result in this demand not being met adequately, especially in developing countries. This constitutes the energy demand – supply matching problem. Load shedding is a response used by distribution utilities in developing countries, to deal with the energy demand – supply problem in the short term and to secure the grid. This response impacts the activities of consumers and entails economic losses. Given this scenario, demand – supply matching becomes a crucial decision making activity. Traditionally demand – supply matching has been carried out by increasing supply centrally in the long term or reducing demand centrally in the short term. Literature shows that these options have not been very effective in solving the demand-supply problem. Gaps in literature also show that the need of the hour is the design of alternate solutions which are tailored to a nation's specific energy service needs in a sustainable way. Microgrids using renewable and clean energy resources and demand side management can be suitable decentralized alternatives to augment the centralized grid based systems and enable demand – supply matching at a local community level. The central research question posed by this thesis is: “How can we reduce the demand – supply gap existing in a community, due to grid insufficiency, using locally available resources and the grid in an optimal way; and thereby facilitate microgrid implementation?” The overall aim of this dissertation is to solve the energy demand – supply matching problem at the community level. It is known that decisions for the creation of energy systems are influenced by several factors. This study focuses on those factors which policy-makers and stakeholders can influence. It proposes an integrated decision framework for the creation of community microgrids. The study looks at several different dimensions of the existing demand – supply problem in a holistic way. The research objectives of this study are: 1. To develop an integrated decision framework that solves the demand – supply matching problem at a community level. 2. To decompose the consumption patterns of the community into end-uses. solar thermal, solar lighting and solar pumps and a combination of these at different capacities. The options feasible for medium income consumers are solar thermal, solar pumps, municipal waste based systems and a combination of these. The options for high income consumers are municipal waste based CHP systems, solar thermal and solar pumps. Residential consumers living in multi-storied buildings also have the options of CHP, micro wind and solar. For cooking, LPG is the single most effective alternative. 3. To identify the ‗best fitting‘ distributed energy system (microgrid), based on the end-use consumption patterns of the community and locally available clean and renewable energy resources, for matching demand – supply at the community level. 4. To facilitate the implementation of microgrids by * Contextualizing the demand – supply matching problem to consider the local social and political environment or landscape, * Studying the economic impact of load shedding and incorporating it into the demand-supply matching problem, and * Presenting multiple decision scenarios, addressing the needs of different stakeholders, to enable dialogue and participative decision making. A multi-stage Integrated Decision Framework (IDF) is developed to solve the demand - supply matching problem in a sequential manner. The first stage in the IDF towards solving the problem is the identification and estimation of the energy needs / end-uses of consumers in a community. This process is called End-use Demand Decomposition (EUDD) and is accomplished by an empirical estimation of consumer electricity demand based on structural and socio-economic factors. An algorithm/ heuristic is also presented to decompose this demand into its constituent end-uses at the community level for the purpose of identifying suitable and optimal alternatives/ augments to grid based electricity. The second stage in the framework is Best Fit DES. This stage involves identifying the “best-fit‘ distributed energy system (microgrid) for the community that optimally matches the energy demand with available forms of supply and provides a schedule for the operation of these various supply options to maximize stakeholder utility. It provides the decision makers with a methodology for identifying the optimal distributed energy resource (DER) mix, capacity and annual operational schedule that “best fits” the given end-use demand profile of consumers in a community and under the constraints of that community such that it meets the needs of the stakeholders. The optimization technique developed is a Mixed Integer Linear Program and is a modification of the DER-CAM™ (Distributed Energy Resources Customer Adoption Model), which is developed by the Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory using the GAMS platform. The third stage is the Community Microgrid Implementation (CMI) stage. The CMI stage of IDF includes three steps. The first one is to contextualize the energy demand and supply for a specific region and the communities within it. This is done by the Energy Landscape Analysis (ELA). The energy landscape analysis attempts to understand the current scenario and develop a baseline for the study. It identifies the potential solutions for the demand - supply problem from a stakeholder perspective. The next step provides a rationale for the creation of community level decentralized energy systems and microgrids from a sustainability perspective. This is done by presenting a theoretical model for outage costs (or load shedding), empirically substantiating it and providing a simulation model to demonstrate the viability for distributed energy systems. Outage cost or the cost of non supply is a variable that can be used to determine the need for alternate systems in the absence/ unavailability of the grid. The final step in the CMI stage is to provide a scenario analysis for the implementation of community microgrids. The scenario analysis step in the framework enlightens decision makers about the baselines and thresholds for the solutions obtained in the “best fit‘ analysis. The first two stages of IDF, EUDD and Best Fit DES, address the problem from a bottom-up perspective. The solution obtained from these stages constitutes the optimal solution from a technical perspective. The third stage CMI is a top-down approach to the problem, which assesses the social and policy parameters. This stage provides a set of satisficing solutions/ scenarios to enable a dialogue between stakeholders to facilitate implementation of microgrids. Thus, IDF follows a hybrid approach to problem solving. The proposed IDF is then used to demonstrate the choice of microgrids for residential communities. In particular, the framework is demonstrated for a typical residential community, Vijayanagar, situated in Bangalore and the findings presented. The End-use Demand Decomposition (EUDD) stage provides the decision makers with a methodology for estimating consumer demand given their socio-economic status, fuel choice and appliance profiles. This is done by the means of a statistical analysis. For this a primary survey of 375 residential households belonging to the LT2a category of BESCOM (Bangalore Electricity Supply Company) was conducted in the Bangalore metropolitan area. The results of the current study show that consumer demand is a function of the variables family income, refrigeration, entertainment, water heating, family size, space cooling, gas use, wood use, kerosene use and space heating. The final regression model (with these variables) can effectively predict up to 60% of the variation in the electricity consumption of a household ln(ElecConsumption) = 0.2880.396*ln(Income)+0.2 66*Refri geration+ 0.708*Entertainment+0.334*WaterHeating+0.047*FamSize+ 0243*SpaceCooling.+580*GasUse+0.421*WoodUse–0.159*KeroseneUse+ 0.568*SpaceHeating ln(ElecConsumption) = 0.406*ln(Income)0.168*Ref rigeration+0.139*Entertainment+ 0.213*WaterHeating+0.114*FamSize+0.121*SpacCooling+0.171*GasUse+ 0.115*WoodUse–0.094*KeroseneUse+0.075*SpaceHeating   The next step of EUDD is to break up the demand into its constituent end-uses. The third step involves aggregating the end-uses at the community level. These two steps are to be performed using a heuristic. The Best Fit DES stage of IDF is demonstrated with data from an urban community in Bangalore. This community is located in an area called Vijayanagar in Bangalore city. Vijayanagar is a mainly a residential area with some pockets of mixed use. Since grid availability is the constraining parameter that yields varying energy availability, this constraint is taken as the criteria for evaluation of the model. The Best Fit DES model is run for different values of the grid availability parameter to study the changes in outputs obtained in DER mix, schedules and overall cost of the system and the results are tabulated. Sensitivity analysis is also performed to study the effect of changing load, price options, fuel costs and technology parameters. The results obtained from the BEST Fit DES model for Vijayanagar illustrate that microgrids and DERs can be a suitable alternative for meeting the demand – supply gap locally. The cost of implementing DERs is the optimal solution. The savings obtained from this option however is less than 1% than the base case due to the subsidized price of grid based electricity. The corresponding costs for different hours of grid availability are higher than the base case, but this is offset by the increased efficiency of the overall system and improved reliability that is obtained in the community due to availability of power 24/7 regardless of the availability of grid based power. If the price of grid power is changed to reflect the true price of electricity, it is shown that DERs continue to be the optimal solution. Also the combination of DERs chosen change with the different levels of non-supply from the grid. For the study community, Vijayanagar, Bangalore, the DERs chosen on the basis of resource availability are mainly discrete DERs. The DERs chosen are the LPG based CHP systems which run as base and intermediate generating systems. The capacity of the discrete DERs selected, depend on the end-use load of the community. Biomass based CHP systems are not chosen by the model as this technology has not reached maturity in an urban setup. Wind and hydro based systems are not selected as these resources are not available in Vijayanagar. The CMI stage of IDF demonstrates the top-down approach to the demand-supply matching problem. For the Energy Landscape Analysis (ELA), Bangalore metropolis was chosen in the study for the purpose of demonstration of the IDF framework. Bangalore consumes 25% of the state electricity supply and its per capita consumption at 1560kWh is higher than the state average of 1230kWh and is 250% more than the Indian average of 612kWh. A stakeholder workshop was conducted to ascertain the business value for clean and renewable energy technologies. From the workshop it was established that significant peak power savings could be obtained with even low penetrations of distributed energy technologies in Bangalore. The feasible options chosen by stakeholders for low income consumers are The second step of CMI is finding an economic rationale for the implementation of community microgrids. It is hypothesized that the ‘The cost of non-supply follows an s-shaped curve similar to a growth curve.’ It is moderated by the consumer income, consumer utility, and time duration of the load shedding. A pre and post event primary survey was conducted to analyze the difference in the pattern of consumer behaviour before and after the implementation of a severe load shedding program by BESCOM during 2009-10. Data was collected from 113 households during February 2009 and July 2010. The analysis proves that there is indeed a significant difference in the number of uninterrupted power systems (inverters) possessed by households. This could be attributed mainly to the power situation in Karnataka during the same period. The data also confirms the nature of the cost of non-supply curve. The third step in CMI is scenario analysis. Four categories of scenarios are developed based on potential interventions. These are business-as-usual, demand side, supply side and demand-supply side. About 21 scenarios are identified and their results compared. Comparing the four categories of scenarios, it is shown that business-as-usual scenarios may result in exacerbation of the demand-supply gap. Demand side interventions result in savings in the total costs for the community, but cannot aid communities with load shedding. Supply side interventions increase the reliability of the energy system for a small additional cost and communities have the opportunity to even meet their energy needs independent of the grid. The combination of both demand and supply side interventions are the best solution alternative for communities, as they enable communities to meet their energy needs 24/7 in a reliable manner and also do it at a lower cost. With an interactive microgrid implementation, communities have the added opportunity to sell back power to the grid for a profit. The thesis concludes with a discussion of the potential use of IDF in policy making, the potential barriers to implementation and minimization strategies. It presents policy recommendations based on the framework developed and the results obtained.

Sustainable management of finite resources is vital for ensuring livable conditions for both current and future generations. Measuring the total water consumption of residential households at high temporal resolutions and automatically disaggregating the sole signal into classified end usages (e.g. shower, sink) allows for identification of behavioural patterns that could be improved to minimise wasteful water consumption. Such disaggregation is not trivial, as water consuming patterns vary greatly depending on consumer behaviour, and further since at any given time, an unknown amount of fixtures may be used simultaneously. In this work, we approach the disaggregation problem by evaluating the performance of a set of recurrent and convolutional neural network structures provided approximately one year of high resolution water consumption data from a single apartment in Sweden. Unlike previous approaches to the problem, we let the models process the full, uninterrupted flow traces (as opposed to extracted segments of water consuming activity) in order to allow for temporal dependencies within and between water consuming activities to be learned. Out of four networks applied to the task, we find that a deeper temporal convolutional network structure yields the best overall results on the test data, with prediction accuracy of 85% and F1-score above 0.8 averaged over all end-use categories - a performance exceeding that of commercial analysis tools, and comparable to components of current state-of-the-art approaches. However, significant decreases in performance are observed for all of the networks, particularly for toilet and washing machine activity, when evaluating the models on unseen and augmented data from the apartment, indicating the results can not be fully generalised for usage in other households. / Hållbar användning av ändliga resurser är avgörande för att försäkra god livskvalitet för både nutida och framtida generationer. I Sverige är vatten för många en självklarhet, vilket öppnar upp för slösaktigt användande. En metod för att utbilda användare och identifiera icke hållbara beteenden är att kvantifiera vattenförbrukningen i hushåll baserat på syfte (t.ex. tvätta händerna, diska) eller källa (t.ex. dusch, handfat) av slutanvändningen. För att göra en sådan sammanställning mäts den totala åtkomsten av vatten i hög upplösning från hushåll, och signalen delas sedan upp i respektive kategori av slutanvändning. En sådan disaggregering är inte trivial, och försvåras av skillnader i beteendemönster hos användare samt faktumet att vi inte vid någon tidpunkt vet hur många vattenarmaturer som används samtidigt. I syftet att förbättra nuvarande tekniker för disaggregeringsproblemet implementerar och utvärderar vi alternativa lösningar baserade på rekurrenta och konvolutionerande neurala nätverk, på flödesdata insamlad med hög upplösning från en lägenhet i Sverige under en period av cirka ett år. Till skillnad från tidigare förhållningssätt till problemet låter vi våra modeller bearbeta den fullständiga, oavbrutna, flödesdatan (i motsats till extraherade segment av vattenförbrukande aktiviteter) för att möjliggöra lärandet av tidsmässiga beroenden inom och mellan vattenförbrukande aktiviteter. Utav fyra testade nätverk finner vi att ett djupt konvolutionerande nätverk ger den bästa klassificeringen överlag, givet testdata, med genomsnittlig igenkänningsnogrannhet på 85%. Signifikant försämrade resultat observerades för samtliga modeller i kategorierna toalett och tvättmaskin när nätverken testades på augmenterad data från hushållet, vilket indikerar att resultaten inte kan generaliseras för användning i andra lägenheter.