A Região Metropolitana de São Paulo (RMSP) sofre de sérios problemas de congestionamento, assim como muitas outras cidades de grande porte. Uma possível solução, proposta por pesquisadores de transportes, economia e ciências ambientais, é a implantação de um sistema de congestion charging, chamada no Brasil de pedágio urbano. Um dos objetivos do presente trabalho foi estabelecer os conceitos relacionados a este assunto e ilustrar as principais questões relacionadas à sua implantação. Espera-se que este trabalho possa auxiliar o desenvolvimento de estudos de avaliação da viabilidade e de impactos de sistemas propostos de congestion charging. Para atingir este objetivo, toca-se em diversos assuntos, como a definição de congestionamento e as formas de medi-lo, a base conceitual e teórica dos sistemas de congestion charging e seus diversos esquemas de diferenciação. São expostas também as medidas de mitigação de congestionamento que já foram implantadas na RMSP, quais foram os estudos já desenvolvidos considerando este tipo de política para a RMSP, e casos em que sistemas de congestion charging já foi implantado. Neste trabalho, desenvolveu-se também um modelo de escolha discreta a partir dos dados da Pesquisa Origem e Destino 2007 do METRÔ, onde pessoas deveriam escolher entre \"Transporte Coletivo\" e \"Transporte Público\". Este modelo foi utilizado para avaliar o potencial de impacto na divisão modal e de arrecadação de um congestion charge aplicado ao centro expandido de São Paulo. Adverte-se, porém, que os resultados obtidos são meramente ilustrativos. Mostra-se, também, que é possível avaliar a capacidade ociosa do sistema de transporte coletivo a partir dos dados disponíveis de bilhetagem e de GPS dos ônibus. Este processo é exemplificado através do cálculo de capacidade de uma única viagem de um único ônibus, dada a dificuldade de automatização deste processo para abranger toda a frota. / The São Paulo Metropolitan Region (SPMR) suffers from severe traffic congestion, as do many other large-scale urban areas around the world. A possible solution to this issue, which has been suggested by transportation, economics and environmental researchers, is the implementation of a congestion charging system. One of the objectives of this project is to establish clear concepts and shed light on the main issues regarding these systems by means of a comprehensive literary review. It is expected that this project may help the development of in-depth studies carried in order to evaluate the viability and impacts of congestion charging proposals. In order to achieve this goal, many subjects are addressed, such as the definition of congestion, how its measured, the theoretical backgrounds that support congestion charging schemes, their different degrees of differentiation, which policies were enacted in order to reduce traffic congestion in São Paulo, what considerations and studies have already been developed for Brazil and São Paulo regarding these systems and where have these systems been successfully installed. Later chapters deal with another goal of this project: estimating how a congestion charging system would affect SPMR. This was achieved through a multinomial logit model, where decision-makers choose between \"Public Transportation\" and \"Private Automobile\". The results presented at this phase are merely indicative of certain tendencies and should not be considered final. This project also attempts to show that given the available Automated Fare Collection (AFC) data and Automated Vehicle Location (AVL) data, it is possible to estimate the current public transportation system\'s unused capacity. The author shows this by calculating the capacity of one bus trip using these data, but also explains the difficulties of expanding this analysis to the whole of SPMR\'s public transportation system.

<p>In the US, seven regional transmission organizations (RTOs) operate wholesale electricity markets within three largely independent transmission systems, the largest of which includes five RTO regions and many vertically integrated utilities.</p> <p>RTOs operate a day-ahead and a real-time market. In the day-ahead market, generation and demand-side resources are optimally scheduled based on bids and offers for the next day. Those schedules are adjusted according to actual operating conditions in the real-time market. Both markets involve a unit commitment calculation, a mixed integer program that determines which generators will be online, and an economic dispatch calculation, an optimization determines the output of each online generator for every interval and calculates locational marginal prices (LMPs).</p> <p>The use of LMPs for the management of congestion in RTO transmission systems has brought efficiency and transparency to the operation of electric power systems and provides price signals that highlight the need for investment in transmission and generation. Through this work, we aim to extend these efficiency and transparency gains to the coordination across RTOs. Existing market-based inter-regional coordination schemes are limited to incremental changes in real-time markets. </p> <p>We propose a multi-regional unit-commitment that enables coordination in the day-ahead timeframe by applying a distributed approach to approximate a system-wide optimal commitment and dispatch while allowing each region to largely maintain their own rules, model only internal transmission up to the boundary, and keep sensitive financial information confidential. A heuristic algorithm based on an extension of the alternating directions method of multipliers (ADMM) for the mixed integer program is applied to the unit commitment. </p> The proposed coordinated solution was simulated and compared to the ideal single-market scenario and to a representation of the current uncoordinated solution, achieving at least 58% of the maximum potential savings, which, in terms of the annual cost of electric generation in the US, could add up to nearly $7 billion per year. In addition to the coordinated day-ahead solution, we develop a distributed solution for financial transmission rights (FTR) auctions with minimal information sharing across RTOs that constitutes the first known work to provide a viable option for market participants to seamlessly hedge price variability exposure on cross-border transactions.

As urban population across the globe increases, the demand for adequate transportation grows. Several strategies have been suggested as a solution to the congestion which results from this high demand outpacing the existing supply of transportation facilities. High –Occupancy Toll (HOT) lanes have become increasingly more popular as a feature on today’s highway system. The I-95 Express HOT lane in Miami Florida, which is currently being expanded from a single Phase (Phase I) into two Phases, is one such HOT facility. With the growing abundance of such facilities comes the need for indepth study of demand patterns and development of an appropriate pricing scheme which reduces congestion. This research develops a method for dynamic pricing on the I-95 HOT facility such as to minimize total travel time and reduce congestion. We apply non-linear programming (NLP) techniques and the finite difference stochastic approximation (FDSA), genetic algorithm (GA) and simulated annealing (SA) stochastic algorithms to formulate and solve the problem within a cell transmission framework. The solution produced is the optimal flow and optimal toll required to minimize total travel time and thus is the system-optimal solution. We perform a comparative evaluation of FDSA, GA and SA non-linear programming algorithms used to solve the NLP and the ANOVA results show that there are differences in the performance of the NLP algorithms in solving this problem and reducing travel time. We then conclude by demonstrating that econometric iv forecasting methods utilizing vector autoregressive (VAR) techniques can be applied to successfully forecast demand for Phase 2 of the 95 Express which is planned for 2014