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The need for optimal air vessel sizing tools, in protecting large pipe networks from undue transient pressures is well known. Graphical and other heuristic methods reported in literature are limited to sizing the air vessels for simple rising mains. Although attempts have been made to utilize optimization techniques, they have been largely unsuccessful due to their impractical computational requirements. This research work proposes a robust framework for developing surge protection design tools and demonstrates the usefulness of the framework through an example air vessel sizing tool. Efficiency and robustness of the proposed framework are demonstrated by developing a design aid for air vessel sizing for protecting large pipe network systems against excessive high pressures generated by rapid valve closures. The essence of the proposed framework is in identification of key transient response parameters influencing air vessel parameters from seemingly unmanageable transient response data. This parameterization helps in exploiting the similarity between transient responses of small pipe networks and sub-sections of large pipe networks. The framework employs an extensive knowledgebase of transient pressure and flow scenarios defined from several small network models and corresponding optimal air vessel sizes obtained from a genetic algorithm optimizer. A regression model based on an artificial neural network was used on this knowledgebase to identify key parameters influencing air vessel sizes. These key parameters were used as input variables and the corresponding air vessel parameters as output variables to train the neural network model. The trained neural network model was successfully applied for large complex pipe networks to obtain optimal air vessel sizes for transient protection. The neural network model predictions were compared with optimal air vessel parameters to assess the efficacy of the proposed framework. The validity and limitation of the design aid developed and areas in the framework that need further research are also presented. The proposed frame work requires generation of hundreds of optimization data for small and simple network systems which is a daunting task since genetic algorithm-based optimization is computationally expensive. Selection of a numerically efficient and sufficiently accurate transient analysis method for use inside a genetic algorithm based optimization scheme is crucial as any reduction in transient analysis time for a network system would tremendously reduce the computational costs of bi-level genetic algorithm optimization scheme. This research work also demonstrate that the Wave Plan Method is computationally more efficient than the Method of Characteristics for similar accuracies and the resulting savings in computational costs in the transient analysis of pipe networks and subsequently in the genetic algorithm based optimization schemes are significant.

Transient stability studies are primarily concerned with the generator response of ac power systems and use only steady state type equations to model HVdc converter terminals. These equations are adequate for small disturbances at the converter terminals but cannot accurately represent a converters behaviour during, and through its recovery of, a significant transient disturbance. A detailed three phase electromagnetic analysis is necessary to describe the converters correct behaviour. This thesis describes an accurate and effective hybrid method combining these two types of studies, for analyzing dynamically fast devices such as HVdc converters within ac power systems. Firstly, conventional techniques are reviewed for both a transient stability analysis of power systems and for an electromagnetic transient analysis of HVdc converters. This review deals in particular with the two programs that constitute the hybrid developed in this thesis. Various techniques are then examined to efficiently and accurately pass the dynamic effects of an HVdc link to an ac system stability study, and the dynamic effects of an ac system to a detailed HVdc link study. An optimal solution is derived to maximise the inherent advantages of a hybrid. Finally, the hybrid is applied to a test system and its effectiveness in performing its task is shown.

Surge modeling is a tool used by engineers and utility owners in determining the surge pressures or transients that may result from routine pump and valve operations. Recent surge modeling work has focused on low and/or negative pressures within water distribution systems and how those occurrences could lead to intrusions. Effective surge modeling is needed in order to determine if the intrusion potential exists and what mitigation is needed to prevent intrusions. This work focuses on the generally unexplored area of using surge models to predict the location and duration of transient induced low and/or negative pressures within large complex water distribution systems. The studied system serves 350,000 people in the southeast United States, has 65 MGD of pumping capacity at two treatment plants, over 1500 miles of main and 12 storage tanks. This work focuses on the correlation between field data and the surge model using the author's extensive operational knowledge of the system, access to real-time SCADA data, and different celerity or wave speed values. This work also traces the steps taken by the author to locate areas within the system that experienced transient induced low and / or negative pressure.

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Thesis (M.S.)--University of Missouri--Rolla, 2007. / Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed November 14, 2007) Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references and index.

Thesis (M.S.)--Ohio University, June, 1994. / Title from PDF t.p.

Thesis (M.A. (Health Social Scinece))--Mahidol University, 2006. / LICL has E-Thesis 0012 ; please contact computer services.

Thesis (M. Phil.)--University of Hong Kong, 1993.