Chemicals and other potentially toxic substances have been released into nature at an increasing rate. Research on how they affect people and what damage they cause have developed rapidly in recent years, creating opportunities to better describe the consequences of emissions to nature. This thesis uses the latest advances in the field to update the EcoValue weighting tool. EcoValue can be used to convert quantitative amounts of emissions into monetary units. How this is done, the main uses and the background to weighting are addressed. Toxicity to humans is evaluated in previous EcoValue methods using a reference value: kg 1,4-Dicholorobenzene. The cost of society per kg of 1,4-Dichlorobenzene released is used as a "weighting factor". The weighting factor is then used as a multiplication factor, where the total kg of 1,4-Dichlorobenzene equivalents is multiplied by the cost per kg of emissions. In this thesis, a new value of cost per kg of 1,4-Dichlorobenzene equivalents has been determined through damage cost estimates. This was done by transferring the results of studies already carried out to costs per kg of 1,4-Dichlorobenzene. The updated version of EcoValue was then tested thorugh application to a previously published LCA study. The results were compared with EcoValue results without the updated damage cost for 1,4-Dichlorobenzene and results when using the EcoTax weighting tool. The suggested weight values are 2.1 €2017 per kg 1.4 DB equivalents, with a possible range between 0.09-6.996 €2017 per kg. / Ämnen giftiga för människor har under de senaste decennierna släpps ut i naturen i en allt högre grad. Forskningen kring hur de påverkar oss människor och vilka skador de orsakar har utvecklats snabbt de senaste åren, vilket skapat möjligheter för att bättre kunna beskriva följderna av giftiga utsläpp till naturen. I den här mastersuppsatsen används den senaste tidens framsteg för att uppdatera viktningsverktyget EcoValue. EcoValue kan användas för att omvandla kvantitativa mängder av utsläpp till monetära enheter. Hur detta görs, huvudsakliga användningsområden och bakgrunden till omvandlingen behandlas i arbetet. Giftighet för människor värderas i EcoValue genom användandet av ett referensvärde: kg 1,4-Dichlorobenzene. Kostnaden för samhället per kg av utsläppt 1,4-Dichlorobenzene används som en ”viktningsfaktor”. Viktningsfaktorn används sedan som en multiplikationsfaktor, där den totala mängden 1,4-Dichlorobenzeneekvivalenter multipliceras med kostnaden per kg utsläpp. I denna mastersuppsats har genom skadekostnadsuppskattningar ett nytt värde på kostnad för samhället per kg 1,4-Dichlorobenzeneekvivalenter tagits fram. Detta gjordes genom att resultat från utförda studier överfördes till skadekostnader för 1,4-Dichlorobenzene. Föreslagna viktningsvärden är 2.1 €2017 per kg 1,4 DB-ekvivalenter, med ett möjligt intervall på 0,09-6,996 €2017 per kg. Den uppdaterade versionen av EcoValue testades sedan genom att den användes på en tidigare publicerad LCAstudie. Resultaten jämfördes med resultat från EcoValue utan uppdaterat värde för 1,4-Dichlorobenzene och resultat där viktningsverktyget EcoTax användes. Genomgående förväntas de viktade kostnaderna för skador på människors hälsa orsakade av giftiga ämnen öka när den uppdaterade viktningsfaktorn används.

O requisito de continuidade de fornecimento de energia elétrica tem sido crescente na medida em que a sociedade de modo geral e os processos industriais em particular apresentam forte dependência desse insumo que assegura a todos satisfação e conforto. O consumidor é um agente econômico e ele faz parte do sistema elétrico (carga). No âmbito da análise de sistemas de potência são abordados temas, desde modelos de representação da rede e da carga até conceitos de custo da continuidade e técnicas de otimização da aplicação de investimentos para priorizar aqueles que trazem maior benefício tanto para o consumidor como para o controlador da concessão. No entanto, as técnicas usuais e convencionais de Planejamento podem conduzir a soluções pouco econômicas, porquanto consideram apenas a otimização dos investimentos em obras, ou seja, reforços da rede para atender a condição normal e em emergência (critério n-1), respeitando, naturalmente, critérios técnicos (limites de tensão, sobrecargas etc). Não raro estas instalações recomendadas pela técnica convencional serem utilizadas apenas em algumas contingências, algumas com baixa probabilidade de ocorrência. Esta pesquisa desenvolve como alternativa às soluções convencionais, um modelo que considera a otimização dos investimentos, lançando mão de recursos operativos como: corte de carga, despacho ou modificações topológicas por meio de chaveamentos, quando operando em contingência. O modelo proposto prevê que a representação da geração inclua funções que relacionam a intensidade de despacho com seus custos, bem como funções que associam custo à intensidade e duração do corte de carga a cada barra do sistema. O modelo também permite a reconfiguração da rede quando operando em contingências, por meio de alterações do estado das chaves, mudando a topologia. As funções de custo do corte de carga também são modeladas neste trabalho, considerando métodos analíticos e agregados para o cálculo do prejuízo sócio-econômico resultante da interrupção. A busca da solução ótima, que pode envolver corte de carga, despachos de geração e reconfiguração da rede, substituindo reforços realizados por obra, é obtida por um algoritmo genético evolutivo. Os procedimentos do modelo proposto representam um avanço do processo de planejamento convencional, porquanto introduz a componente continuidade de serviço de forma quantitativa, caracterizando o atendimento dos requisitos de sensibilidade das cargas de cada barra do sistema, lançando mão de recursos operativos, através de possíveis despachos e alterações topológicas. Um estudo de caso ilustra a aplicação do modelo proposto. / The need for reliable electrical energy supply continuity, the industrial demand and its dependence has been growing worldwide. Besides, it also concerns society and assures satisfaction and comfort of consumers. The consumer is the economic agent since he takes part in the system. On analyzing an electrical system, models are needed to represent the network and the load and optimization frameworks in order to make better investments and prioritize those which can benefit the consumer and the concession holder. The usual Planning Models commonly provide us with uneconomical solutions since the optimization is carried out through active investments or network reinforcements to attend the normal and the emergency condition (n-1 criteria), based on technical criteria, like voltage and overload . Frequently, these techniques recommended by the conventional analysis can be applied only in some contingencies, some of them with a small probability of occurrence.. This research develops an alternative to the conventional solutions, considering the investment optimization and using operative resources, such as: load shedding, generation rescheduling or network change operation (circuit breaker, e.g.) when operating in contingency. In this model, the generation is represented by a function that relates the intensity rescheduling and its costs and functions that relates load shedding cost, the intensity and duration of curtailment on each system bus. The model sets a network contingency reconfiguration, changing the circuit break situation (open or closed) and altering the topology. The calculation of cost of load discontinuity or social cost functions (damage cost) is shown in this thesis, considering analytical and aggregating methods. The search for an optimized solution can involve load shedding, generation rescheduling and topology changes as substitutes for network reinforcements, and may be obtained by genetic- evolutive algorithm. The procedures of the proposed model represent an advancement over the conventional Planning Process as it introduces, quantitatively, the consumer service continuity, meeting the sensibility criteria of the load characterization of each consumer class connected to the system bus, through operative resources, rescheduling, load shedding and topology changes. A case study illustrates the application of the proposed model.

O requisito de continuidade de fornecimento de energia elétrica tem sido crescente na medida em que a sociedade de modo geral e os processos industriais em particular apresentam forte dependência desse insumo que assegura a todos satisfação e conforto. O consumidor é um agente econômico e ele faz parte do sistema elétrico (carga). No âmbito da análise de sistemas de potência são abordados temas, desde modelos de representação da rede e da carga até conceitos de custo da continuidade e técnicas de otimização da aplicação de investimentos para priorizar aqueles que trazem maior benefício tanto para o consumidor como para o controlador da concessão. No entanto, as técnicas usuais e convencionais de Planejamento podem conduzir a soluções pouco econômicas, porquanto consideram apenas a otimização dos investimentos em obras, ou seja, reforços da rede para atender a condição normal e em emergência (critério n-1), respeitando, naturalmente, critérios técnicos (limites de tensão, sobrecargas etc). Não raro estas instalações recomendadas pela técnica convencional serem utilizadas apenas em algumas contingências, algumas com baixa probabilidade de ocorrência. Esta pesquisa desenvolve como alternativa às soluções convencionais, um modelo que considera a otimização dos investimentos, lançando mão de recursos operativos como: corte de carga, despacho ou modificações topológicas por meio de chaveamentos, quando operando em contingência. O modelo proposto prevê que a representação da geração inclua funções que relacionam a intensidade de despacho com seus custos, bem como funções que associam custo à intensidade e duração do corte de carga a cada barra do sistema. O modelo também permite a reconfiguração da rede quando operando em contingências, por meio de alterações do estado das chaves, mudando a topologia. As funções de custo do corte de carga também são modeladas neste trabalho, considerando métodos analíticos e agregados para o cálculo do prejuízo sócio-econômico resultante da interrupção. A busca da solução ótima, que pode envolver corte de carga, despachos de geração e reconfiguração da rede, substituindo reforços realizados por obra, é obtida por um algoritmo genético evolutivo. Os procedimentos do modelo proposto representam um avanço do processo de planejamento convencional, porquanto introduz a componente continuidade de serviço de forma quantitativa, caracterizando o atendimento dos requisitos de sensibilidade das cargas de cada barra do sistema, lançando mão de recursos operativos, através de possíveis despachos e alterações topológicas. Um estudo de caso ilustra a aplicação do modelo proposto. / The need for reliable electrical energy supply continuity, the industrial demand and its dependence has been growing worldwide. Besides, it also concerns society and assures satisfaction and comfort of consumers. The consumer is the economic agent since he takes part in the system. On analyzing an electrical system, models are needed to represent the network and the load and optimization frameworks in order to make better investments and prioritize those which can benefit the consumer and the concession holder. The usual Planning Models commonly provide us with uneconomical solutions since the optimization is carried out through active investments or network reinforcements to attend the normal and the emergency condition (n-1 criteria), based on technical criteria, like voltage and overload . Frequently, these techniques recommended by the conventional analysis can be applied only in some contingencies, some of them with a small probability of occurrence.. This research develops an alternative to the conventional solutions, considering the investment optimization and using operative resources, such as: load shedding, generation rescheduling or network change operation (circuit breaker, e.g.) when operating in contingency. In this model, the generation is represented by a function that relates the intensity rescheduling and its costs and functions that relates load shedding cost, the intensity and duration of curtailment on each system bus. The model sets a network contingency reconfiguration, changing the circuit break situation (open or closed) and altering the topology. The calculation of cost of load discontinuity or social cost functions (damage cost) is shown in this thesis, considering analytical and aggregating methods. The search for an optimized solution can involve load shedding, generation rescheduling and topology changes as substitutes for network reinforcements, and may be obtained by genetic- evolutive algorithm. The procedures of the proposed model represent an advancement over the conventional Planning Process as it introduces, quantitatively, the consumer service continuity, meeting the sensibility criteria of the load characterization of each consumer class connected to the system bus, through operative resources, rescheduling, load shedding and topology changes. A case study illustrates the application of the proposed model.

Since the transportation sector still relies mostly on fossil fuels, the emissions and overall environmental impacts of the transportation sector are particularly relevant to the mitigation of the adverse effects of climate change. Sustainable transportation therefore plays a vital role in the ongoing discussion on how to promote energy insecurity and address future energy requirements. One of the most promising ways to increase energy security and reduce emissions from the transportation sector is to support alternative fuel technologies, including electric vehicles (EVs). As vehicles become electrified, the transportation fleet will rely on the electric grid as well as traditional transportation fuels for energy. The life cycle cost and environmental impacts of EVs are still very uncertain, but are nonetheless extremely important for making policy decisions. Moreover, the use of EVs will help to diversify the fuel mix and thereby reduce dependence on petroleum. In this respect, the United States has set a goal of a 20% share of EVs on U.S. roadways by 2030. However, there is also a considerable amount of uncertainty in the market share of EVs that must be taken into account. This dissertation aims to address these inherent uncertainties by presenting two new models: the Electric Vehicles Regional Optimizer (EVRO), and Electric Vehicle Regional Market Penetration (EVReMP). Using these two models, decision makers can predict the optimal combination of drivetrains and the market penetration of the EVs in different regions of the United States for the year 2030. First, the life cycle cost and life cycle environmental emissions of internal combustion engine vehicles, gasoline hybrid electric vehicles, and three different EV types (gasoline plug-in hybrid EVs, gasoline extended-range EVs, and all-electric EVs) are evaluated with their inherent uncertainties duly considered. Then, the environmental damage costs and water footprints of the studied drivetrains are estimated. Additionally, using an Exploratory Modeling and Analysis method, the uncertainties related to the life cycle costs, environmental damage costs, and water footprints of the studied vehicle types are modeled for different U.S. electricity grid regions. Next, an optimization model is used in conjunction with this Exploratory Modeling and Analysis method to find the ideal combination of different vehicle types in each U.S. region for the year 2030. Finally, an agent-based model is developed to identify the optimal market shares of the studied vehicles in each of 22 electric regions in the United States. The findings of this research will help policy makers and transportation planners to prepare our nation*s transportation system for the future influx of EVs. The findings of this research indicate that the decision maker*s point of view plays a vital role in selecting the optimal fleet array. While internal combustion engine vehicles have the lowest life cycle cost, the highest environmental damage cost, and a relatively low water footprint, they will not be a good choice in the future. On the other hand, although all-electric vehicles have a relatively low life cycle cost and the lowest environmental damage cost of the evaluated vehicle options, they also have the highest water footprint, so relying solely on all-electric vehicles is not an ideal choice either. Rather, the best fleet mix in 2030 will be an electrified fleet that relies on both electricity and gasoline. From the agent-based model results, a deviation is evident between the ideal fleet mix and that resulting from consumer behavior, in which EV shares increase dramatically by the year 2030 but only dominate 30 percent of the market. Therefore, government subsidies and the word-of-mouth effect will play a vital role in the future adoption of EVs.