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As the future of the world’s oil reserves becomes progressively more uncertain, it is becoming increasingly important that steps are taken to ensure that there are viable, attractive alternatives to travel by private motor vehicle. As with many of New Zealand’s major urban centres, Christchurch is still exceptionally reliant on private motor vehicles; although a significant proportion of the population indicate that they would like to cycle more, cycling is still an underutilised mode of transport. Following a series of fatal earthquakes that struck the city in 2010 and 2011, there has been the need to significantly redevelop much of the city’s horizontal infrastructure – subsequently providing the perfect platform for significant changes to be made to the road network. Many of the key planning frameworks governing the rebuild process have identified the need to improve Christchurch’s cycling facilities in order to boost cycling numbers and cyclist safety. The importance of considering future growth and travel patterns when planning for transport infrastructure has been highlighted extensively throughout literature. Accordingly, this study sought to identify areas where future cycle infrastructure development would be advantageous based on a number of population and employment projections, and likely future travel patterns throughout the city. Through the use of extensive GIS analysis, future population growth, employment and travel patterns for Christchurch city were examined in order to attain an understanding of where the current proposed major cycleways network could be improved, or extended. A range of data and network analysis were used to derive likely travel patterns throughout Christchurch in 2041. Trips were derived twice, once with a focus on simply finding the shortest route between each origin and destination, and then again with a focus on cyclist safety and areas where cyclists were unlikely to travel. It was found that although the proposed major cycleways network represents a significant step towards improving the cycling environment in Christchurch, there are areas of the city that will not be well serviced by the current proposed network in 2041. These include a number of key residential growth areas such as Halswell, Belfast and Prestons, along with a number of noteworthy key travel zones, particularly in areas close to the central city and key employment areas. Using network analysis, areas where improvements or extensions to the proposed network would be most beneficial were identified, and a number of potential extensions in a variety of areas throughout the city were added to the network of cycle ways. Although it has been found that filling small gaps in the network can have considerable positive outcomes, results from the prioritisation analysis suggested that initially in Christchurch demand is likely to be for more substantial extensions to the proposed major cycleways network.

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This thesis describes the implementation of the Flexible AC Transmission Systems (FACTS) devices to develop a market-based approach to the problem of transmission congestion management in a Balancing Market. The causes, remedies and pricing methods of transmission congestion are briefly reviewed. Balancing Market exists in markets in which most of the trading is done via decentralized bilateral contracts. In these markets only final adjustments necessary to ensure secure system operation is carried out at a centralized Balancing Market. Each market player can participate in the Balancing Market by submitting offers and bids to increase and decrease its initially submitted active generation output. In this research a method is proposed to reduce costs associated with congestion re-dispatch in a Balancing Market by optimal placement of FACTS devices, and in particular Thyristor Controlled Phase Shifter Transformers (TCPST). The proposed technique is applicable to both Mixed Integer Linear Programming (MILP) and Mixed Integer Non-Linear Programming (MINLP). In the MILP a power system network is represented by a simplified DC power flow under a MILP structure and the Market participants' offers and bids are also represented by linear models. Results show that applications of FACTS devices can significantly reduce costs of congestion re-dispatch. The application of the method based on the MINLP creates a nonlinear and non-convex AC OPF problem that might be trapped in local sub-optima solutions. The reliability of the solution that determines the optimal placement of FACTS devices is an important issue and is carried out by investigation of alternative solvers. The behavior of the MINLP solvers is presented and finally the best solvers for this particular optimization problem are introduced. The application of DC OPF is very common in industry. The accuracy of the DC OPF results is investigated and a comparison between the DC and AC OPF is presented.

An Origin-Destination (OD) traffic matrix provides a major input to the design, planning and management of a telecommunications network. Since the Internet is being proposed as the principal delivery mechanism for telecommunications traffic at the present time, and this network is not owned or managed by a single entity, there are significant challenges for network planners and managers needing to determine equipment and topology configurations for the various sections of the Internet that are currently the responsibility of ISPs and traditional telcos. Planning of these sub-networks typically requires a traffic matrix of demands that is then used to infer the flows on the administrator's network. Unfortunately, computation of the traffic matrix from measurements of individual flows is extremely difficult due to the fact that the problem formulation generally leads to the need to solve an under-determined system of equations. Thus, there has been a major effort f rom among researchers to obtain the traffic matrix using various inference techniques. The major contribution of this thesis is the development of inference techniques for traffic matrix estimation problem according to three different approaches, viz: (1) deterministic, (2) statistical, and (3) dynamic approaches. Firstly, for the deterministic approach, the traffic matrix estimation problem is formulated as a nonlinear optimization problem based on the generalized Kruithof approach which uses the Kullback distance to measure the probabilistic distance between two traffic matrices. In addition, an algorithm using the Affine scaling method is developed to solve the constrained optimization problem. Secondly, for the statistical approach, a series of traffic matrices are obtained by applying a standard deterministic approach. The components of these matrices represent estimates of the volumes of flows being exchanged between all pairs of nodes at the respective measurement points and they form a stochastic counting process. Then, a Markovian Arrival Process of order two (MAP-2) is applied to model the counting processes formed from this series of estimated traffic matrices. Thirdly, for the dynamic approach, the dual problem of the multi-commodity flow problem is formulated to obtain a set of link weights. The new weight set enables flows to be rerouted along new paths, which create new constraints to overcome the under-determined nature of traffic matrix estimation. Since a weight change disturbs a network, the impact of weight changes on the network is investigated by using simulation based on the well-known ns2 simulator package. Finally, we introduce two network applications that make use of the deterministic and the statistical approaches to obtain a traffic matrix respectively and also describe a scenario for the use of the dynamic approach.

The amount of distributed generation (DG) is increasing worldwide, and it is located in distribution networks close to consumers or even in the consumers¡¦ side of the meter. Therefore, the net demand to be supplied through transmission and distribution networks may decrease, allowing to postpone reinforcement of existing networks. This thesis presents a methodology for assessing the potential benefits of using non--constructional reinforcement strategies to relieve distribution network congestion and increase the utilization of the network assets. Due to the randomness of involved variables (load demand patterns, DG hourly production, DG availability, etc.), a simulation approach is used to model the uncertainties. The benefits of DG, energy storage (ES), and demand response (DR) on congestion relief and investment deferment are evaluated. The analyzed items include: the distribution network investment avoided cost, levelized annual cost, hourly overload probability, and hourly overload risk. Simulation results indicate the potential benefits of non--traditional strategies in increasing the distribution network utilization and relieving network congestion.

Over the last two decades, wireless technology has become ubiquitous in the United States and other developed countries. Consumer devices such as AM/FM radios, cordless and cellular telephones, pagers, satellite televisions, garage door openers, and television channel changers are just some of the applications of wireless technology. More recently, wireless computer networking has seen increasing employment. A few reasons for this move toward wireless networking are improved electronics transmitters and receivers, reduced costs, simplified installation, and enhanced network expandability. The objective of the study is to generate understanding of the planning inherent in a broadband, fixed wireless telecommunication network and to implement that knowledge into an SDSS. Intermediate steps toward this goal include solutions to both fixed wireless point-to-multipoint (PMP) and fixed wireless mesh networks, which are developed and incorporated into the SDSS. This study explores the use of a Spatial Decision Support System (SDSS) for broadband fixed wireless connectivity to solve the wireless network planning problem. The spatial component of the DSS is a Geographic Information System (GIS), which displays visibility for specific tower locations. The SDSS proposed here incorporates cost, revenue, and performance capabilities of a wireless technology applied to a given area. It encompasses cost and range capabilities of wireless equipment, the customers' propensity to pay, the market penetration of a given service offering, the topology of the area in which the wireless service is proffered, and signal obstructions due to local geography. This research is both quantitative and qualitative in nature. Quantitatively, the wireless network planning problem may be formulated as integer programming problems (IP). The line-of-sight restriction imposed by several extant wireless technologies necessitates the incorporation of a GIS and the development of an SDSS to facilitate the symbiosis of the mathematics and geography. The qualitative aspect of this research involves the consideration of planning guidelines for the general wireless planning problem. Methodologically, this requires a synthesis of the literature and insights gathered from using the SDSS above in a what-if mode. / Ph. D.

Le résumé en français n'a pas été communiqué par l'auteur. / Le résumé en anglais n'a pas été communiqué par l'auteur.

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Due to the steady increased in public transportation demand, there is a need to provide more desirable and user-friendly transit systems. Typically, the public transportation timetables are modeled as an assignment problem, which often has objectives such as reducing the cost of operation, minimizing waiting time between transfer points or improving the quality of performance. This research considers the problem of developing synchronized timetables for bus transit systems with fixed routes when a waiting time limit exist at each transfer stops, for the passengers making connections. The objective of this research is to have maximum number of simultaneous arrivals. Different to previous studies, a simultaneous arrival' has been defined as an arrival of buses of different routes at a transfer point such that the time between these arrivals do not exceed the passenger waiting time range associated with the transfer stop. In other words, at each node, an upper bound and a lower bound are set for the arrivals of two buses and these buses are run within this allowable window. The heuristic developed has been modeled as a mixed integer linear programming problem and applied to some real life problems to evaluate the outcomes. The total number of synchronizations obtained by the model was compared to the maximum possible simultaneous arrivals at each node. Results show that a larger number of simultaneous arrivals are obtained when the waiting time ranges are relaxed. Finally some important applications of the proposed model compared to the existing models are presented.