Congestion charging is a now accepted means of influencing traffic to behave in a more socio-economic optimal way, like e.g. in the Stockholm project. Already early work, in the 1920’s, showed that road use can be inefficient due externalities, i.e. that users don’t experience their own (negative) effect on other users: an extra car on a traffic link causes delays for other cars, but the driver himself does not experience this cost.In the 1950’s it was further shown - for a congested road network with homogeneous users – that if each user is charged a toll equal to the total value of time loss incurred on other users of the network, then -if we have fixed travel demand - this will induce an equilibrium that is system optimal in the sense that the total cost of network usage is minimal (assuming that all users have fixed and identical time values).  But toll charges need to be levied in monetary units, and different travelers have different values of time. Therefore, to account for the effects of tolls, and to be able to compute equilibria, one needs to introduce different user classes, differing in their time values. In this thesis, consisting of four papers, we study congestion pricing of road networks with users differing only in their time values. In particular, we analyze marginal social cost (MSC) pricing, a tolling scheme that charges each user a penalty corresponding to the value of the delays inflicted on other users, as well as its implementation through fixed tolls. Paper III contains the main theoretical work of the thesis. In that paper we show that the variational inequalities characterizing the equilibria in question can be stated in symmetric or non-symmetric forms. The symmetric forms correspond to optimization problems, convex in the fixed-toll case and non-convex in the MSC case, which hence may have multiple equilibria. The objective of the latter problem is the total value of travel time, which thus is minimized at the global optima of that problem. Implementing close-to-optimal MSC tolls as fixed tolls leads to equilibria with possibly non-unique class specific flows, but with identical close-to-optimal values of the total value of travel time. Finally we give an adaptation, to the MSC setting, of the Frank-Wolfe algorithm, which is further applied to some test cases, including Stockholm. Paper I is an early application using Frank-Wolfe, after having realized the possibility to symmetrize the problem. Paper II gives a convexification of non-convex equilibrium problem for MSC tolls. We have used these convexifications to compute lower bounds when computing equilibria. Paper IV is a short note commenting some flaws in two papers by Dial on MSC tolls. / <p>QC 20100610</p>

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We analyze the policy implications of aversion to Knightian uncertainty (ambiguity) about the possibility of tipping points. We demonstrate two channels through which uncertainty aversion affects optimal policy in the general setting. The first channel relates to the policy's effect on the probability of tipping, and the second channel to its differential impact in the pre- and post-tipping regimes. We then extend a recursive dynamic model of climate policy and tipping points to include uncertainty aversion. Numerically, aversion to Knightian uncertainty in the face of an ambiguous tipping point increases the optimal tax on carbon dioxide emissions, but only by a small amount.

A continuidade no fornecimento de energia elétrica a clientes é um objetivo constante das distribuidoras de energia, as quais estão constantemente buscando desenvolver soluções tecnológicas a fim de melhorar o desempenho das redes de distribuição. Com o crescimento das cargas eletrônicas e o expressivo aumento dos dispositivos automáticos nas redes, surge uma nova forma de analisar a rede de distribuição sob o aspecto da filosofia da proteção, considerando interrupções sustentadas e momentâneas, sob dois aspectos distintos, o primeiro considera o custo da energia não fornecida sob o período de contingência, enquanto que o segundo refere-se ao impacto do custo social para diferentes classes de clientes, durante o período das interrupções. Desta forma este trabalho propõe o desenvolvimento de uma estratégia de minimização de custos dessas interrupções considerando as características das cargas, bem como o tempo necessário para reinicialização da carga. Para este fim, é aplicado um modelo de programação não-linear, que emprega variáveis binárias para definir a habilitação ou não de curvas rápidas nos religadores e uma abordagem de otimização clássica. Os algoritmos foram desenvolvidos no software Matlab e posteriormente convertido para linguagem GAMS (Generic Algebraic Modeling System). A metodologia foi testada e validada em um alimentador de distribuição real urbano, localizado na região metropolitana de Porto Alegre (RS, Brasil). / Uninterrupted power delivery is a permanent goal of power utilities. One way of attaining this objective is constantly investing in technological solutions to improve the performance of distribution networks. With increasing loads, mainly electronic ones, as well as growing insertion of automatic reclosers, the protection philosophy of distribution systems has to be rethought taking into account temporary and permanent interruptions. In this work, we propose a strategy to minimize the cost of interruptions taking into account the load characteristics and the time required to restart the load. This is achieved by deriving a mixed integer nonlinear programming model. The proposed model uses binary variables to define if the instantaneous characteristic of the recloser should be enabled and a classical explicit mathematical optimization approach. The algorithms were developed with Matlab software and the conversion was made to a General Algebraic Modeling System (GAMS). The applicability of the proposed methodology is tested in an actual feeder from Porto Alegre.

The issues of global warming and climate change are a worldwide concern and the UK government has committed itself to major reductions in CO2 emissions, the most significant of the six greenhouse gases. Road transport currently accounts for about 22% of total UK emissions of CO2, and has been steadily rising. Therefore, initiatives are required to try and reduce the gas emissions in this sector. The aim of this research has been to develop a computer based vehicle routing model that calculates the overall amount of CO2 emitted from road journeys, as well as time and distance. The model has been used to examine a number of delivery strategies to assess how CO2 emissions vary. The aim has not been to produce new mathematical theories, but to produce an innovative basis for routing which will provide new information and knowledge about how CO2 emissions vary for different minimisation and congestion criteria. The approach used in this research brings together elements from transportation planning and environmental modelling combined with logistics based vehicle routing techniques. The model uses a digitised road network containing predicted traffic volumes, to which speed flow formulae are applied so that a good representation of speed can be generated on each of the roads. This means that the model is uniquely able to address the issue of congestion in the context of freight vehicle routing. It uses driving cycle data to apply variability to the generated speeds to reflect acceleration and deceleration so that fuel consumption, and therefore CO2, can be estimated. Integrated within the model are vehicle routing heuristics to enable routes to be produced which minimise the specified criterion of time, distance or CO2. The results produced by the model show that there is a potential to reduce CO2 emissions by about 5%. However, when other transport externalities are considered overall benefits are dependent on road traffic volumes.

Kyoto University (京都大学) / 0048 / 新制・課程博士 / 博士(地球環境学) / 甲第19156号 / 地環博第131号 / 新制||地環||27 / 32107 / 京都大学大学院地球環境学舎地球環境学専攻 / (主査)准教授 森 晶寿, 教授 劉 徳強, 准教授 吉野 章 / 学位規則第4条第1項該当

A continuidade no fornecimento de energia elétrica a clientes é um objetivo constante das distribuidoras de energia, as quais estão constantemente buscando desenvolver soluções tecnológicas a fim de melhorar o desempenho das redes de distribuição. Com o crescimento das cargas eletrônicas e o expressivo aumento dos dispositivos automáticos nas redes, surge uma nova forma de analisar a rede de distribuição sob o aspecto da filosofia da proteção, considerando interrupções sustentadas e momentâneas, sob dois aspectos distintos, o primeiro considera o custo da energia não fornecida sob o período de contingência, enquanto que o segundo refere-se ao impacto do custo social para diferentes classes de clientes, durante o período das interrupções. Desta forma este trabalho propõe o desenvolvimento de uma estratégia de minimização de custos dessas interrupções considerando as características das cargas, bem como o tempo necessário para reinicialização da carga. Para este fim, é aplicado um modelo de programação não-linear, que emprega variáveis binárias para definir a habilitação ou não de curvas rápidas nos religadores e uma abordagem de otimização clássica. Os algoritmos foram desenvolvidos no software Matlab e posteriormente convertido para linguagem GAMS (Generic Algebraic Modeling System). A metodologia foi testada e validada em um alimentador de distribuição real urbano, localizado na região metropolitana de Porto Alegre (RS, Brasil). / Uninterrupted power delivery is a permanent goal of power utilities. One way of attaining this objective is constantly investing in technological solutions to improve the performance of distribution networks. With increasing loads, mainly electronic ones, as well as growing insertion of automatic reclosers, the protection philosophy of distribution systems has to be rethought taking into account temporary and permanent interruptions. In this work, we propose a strategy to minimize the cost of interruptions taking into account the load characteristics and the time required to restart the load. This is achieved by deriving a mixed integer nonlinear programming model. The proposed model uses binary variables to define if the instantaneous characteristic of the recloser should be enabled and a classical explicit mathematical optimization approach. The algorithms were developed with Matlab software and the conversion was made to a General Algebraic Modeling System (GAMS). The applicability of the proposed methodology is tested in an actual feeder from Porto Alegre.

A continuidade no fornecimento de energia elétrica a clientes é um objetivo constante das distribuidoras de energia, as quais estão constantemente buscando desenvolver soluções tecnológicas a fim de melhorar o desempenho das redes de distribuição. Com o crescimento das cargas eletrônicas e o expressivo aumento dos dispositivos automáticos nas redes, surge uma nova forma de analisar a rede de distribuição sob o aspecto da filosofia da proteção, considerando interrupções sustentadas e momentâneas, sob dois aspectos distintos, o primeiro considera o custo da energia não fornecida sob o período de contingência, enquanto que o segundo refere-se ao impacto do custo social para diferentes classes de clientes, durante o período das interrupções. Desta forma este trabalho propõe o desenvolvimento de uma estratégia de minimização de custos dessas interrupções considerando as características das cargas, bem como o tempo necessário para reinicialização da carga. Para este fim, é aplicado um modelo de programação não-linear, que emprega variáveis binárias para definir a habilitação ou não de curvas rápidas nos religadores e uma abordagem de otimização clássica. Os algoritmos foram desenvolvidos no software Matlab e posteriormente convertido para linguagem GAMS (Generic Algebraic Modeling System). A metodologia foi testada e validada em um alimentador de distribuição real urbano, localizado na região metropolitana de Porto Alegre (RS, Brasil). / Uninterrupted power delivery is a permanent goal of power utilities. One way of attaining this objective is constantly investing in technological solutions to improve the performance of distribution networks. With increasing loads, mainly electronic ones, as well as growing insertion of automatic reclosers, the protection philosophy of distribution systems has to be rethought taking into account temporary and permanent interruptions. In this work, we propose a strategy to minimize the cost of interruptions taking into account the load characteristics and the time required to restart the load. This is achieved by deriving a mixed integer nonlinear programming model. The proposed model uses binary variables to define if the instantaneous characteristic of the recloser should be enabled and a classical explicit mathematical optimization approach. The algorithms were developed with Matlab software and the conversion was made to a General Algebraic Modeling System (GAMS). The applicability of the proposed methodology is tested in an actual feeder from Porto Alegre.

The issues of global warming and climate change are a worldwide concern and the UK government has committed itself to major reductions in CO2 emissions, the most significant of the six greenhouse gases. Road transport currently accounts for about 22% of total UK emissions of CO2, and has been steadily rising. Therefore, initiatives are required to try and reduce the gas emissions in this sector. The aim of this research has been to develop a computer based vehicle routing model that calculates the overall amount of CO2 emitted from road journeys, as well as time and distance. The model has been used to examine a number of delivery strategies to assess how CO2 emissions vary. The aim has not been to produce new mathematical theories, but to produce an innovative basis for routing which will provide new information and knowledge about how CO2 emissions vary for different minimisation and congestion criteria. The approach used in this research brings together elements from transportation planning and environmental modelling combined with logistics based vehicle routing techniques. The model uses a digitised road network containing predicted traffic volumes, to which speed flow formulae are applied so that a good representation of speed can be generated on each of the roads. This means that the model is uniquely able to address the issue of congestion in the context of freight vehicle routing. It uses driving cycle data to apply variability to the generated speeds to reflect acceleration and deceleration so that fuel consumption, and therefore CO2, can be estimated. Integrated within the model are vehicle routing heuristics to enable routes to be produced which minimise the specified criterion of time, distance or CO2. The results produced by the model show that there is a potential to reduce CO2 emissions by about 5%. However, when other transport externalities are considered overall benefits are dependent on road traffic volumes.

This compilation dissertation consists of four essays with the common theme of welfare analysis of long-term public investments. The first two essays focus on analysis of climate change mitigation, i.e., the social cost of carbon dioxide. The third essay focuses on cost-benefit analysis (CBA) of transport investment projects, while the last essay takes a broader perspective on welfare analysis. Essay 1: The Temporal Aspects of the Social Cost of Greenhouse Gases. The purpose of Essay 1 is to investigate the temporal aspects of the social cost of greenhouse gases. I find that the calculation period should ultimately be modeled to be consistent with the discount rate and that the “global-warming potential” concept is unsuitable for calculation of the social cost of GHGs other than carbon dioxide. Essay 2: Avoiding path dependence of distributional weights: Lessons from climate change economic assessments. In Essay 2, I explore shortcomings in income weighting in evaluation of climate change policy. In short, in previous versions of two of the most important existing models, regional economic growth is double counted. The proposed alternative approaches yield about 20–40% higher values of SCCO2 than the old approach. Essay 3: Does uncertainty make cost-benefit analyses pointless? In Essay 3, the aim is to investigate to what extent CBA improves the selection decision of projects when uncertainties are taken into account, using a simulation-based approach on real data of infrastructure investments. The results indicate that, in line with previous literature, CBA is a rather robust tool and considerably increases the quality of decision making compared with a random selection mechanism, even when high levels of uncertainty are considered. Essay 4: Household Production and the Elasticity of Marginal Utility of Consumption. In Essay 4, I develop a new model to show that omission of household production in a previous model leads to bias when the elasticity of marginal utility of consumption, EMUC, is estimated. I further offer new, unbiased estimates based on current evidence of the included parameters, suggesting a lower bound of EMUC at about 0.9.