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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Transmission System Restoration Strategies in Real Time

January 2010 (has links)
abstract: After a power system blackout, system restoration is the most important task for the operators. Most power systems rely on an off&ndashline; restoration plan and the experience of operators to select scenarios for the black start path. Using an off&ndashline; designed restoration plan based on past experience may not be the most reliable approach under changing network configurations and loading levels. Hence, an objective restoration path selection procedure, including the option to check constraints, may be more responsive in providing directed guidance to the operators to identify the optimal transmission path to deliver power to other power plants or to pick up load as needed. After the system is subjected to a blackout, parallel restoration is an efficient way to speed up the restoration process. For a large scale power system, this system sectionalizing problem is quite complicated when considering black&ndashstart; constraints, generation/load balance constraints and voltage constraints. This dissertation presents an ordered binary decision diagram (OBDD) &ndashbased; system sectionalizing method, by which the splitting points can be quickly found. The simulation results on the IEEE 39 and 118&ndashbus; system show that the method can successfully split the system into subsystems satisfying black&ndashstart; constraints, generation/load balance constraints and voltage constraints. A power transfer distribution factor (PTDF)&ndashbased; approach will be described in this dissertation to check constraints while restoring the system. Two types of restoration performance indices are utilized considering all possible restoration paths, which are then ranked according to their expected performance characteristics as reflected by the restoration performance index. PTDFs and weighting factors are used to determine the ordered list of restoration paths, which can enable the load to be picked up by lightly loaded lines or relieve stress on heavily loaded lines. A transmission path agent can then be formulated by performing the automatic path selection under different system operating conditions. The proposed restoration strategy is tested on the IEEE&ndash39; bus system and on the Western region of the Entergy system. The testing results reveal that the proposed strategy can be used in real time. / Dissertation/Thesis / Ph.D. Electrical Engineering 2010
2

Power System Network Reduction for Engineering and Economic Analysis

January 2012 (has links)
abstract: Electric power systems are facing great challenges from environmental regulations, changes in demand due to new technologies like electric vehicle, as well as the integration of various renewable energy sources. These factors taken together require the development of new tools to help make policy and investment decisions for the future power grid. The requirements of a network equivalent to be used in such planning tools are very different from those assumed in the development of traditional equivalencing procedures. This dissertation is focused on the development, implementation and verification of two network equivalencing approaches on large power systems, such as the Eastern Interconnection. Traditional Ward-type equivalences are a class of equivalencing approaches but this class has some significant drawbacks. It is well known that Ward-type equivalents "smear" the injections of external generators over a large number of boundary buses. For newer long-term investment applications that take into account such things as greenhouse gas (GHG) regulations and generator availability, it is computationally impractical to model fractions of generators located at many buses. A modified-Ward equivalent is proposed to address this limitation such that the external generators are moved wholesale to some internal buses based on electrical distance. This proposed equivalencing procedure is designed so that the retained-line power flows in the equivalent match those in the unreduced (full) model exactly. During the reduction process, accommodations for special system elements are addressed, including static VAr compensators (SVCs), high voltage dc (HVDC) transmission lines, and phase angle regulators. Another network equivalencing approach based on the dc power flow assumptions and the power transfer distribution factors (PTDFs) is proposed. This method, rather than eliminate buses via Gauss-reduction, aggregates buses on a zonal basis. The bus aggregation approach proposed here is superior to the existing bus aggregation methods in that a) under the base case, the equivalent-system inter-zonal power flows exactly match those calculated using the full-network-model b) as the operating conditions change, errors in line flows are reduced using the proposed bus clustering algorithm c) this method is computationally more efficient than other bus aggregation methods proposed heretofore. A critical step in achieving accuracy with a bus aggregation approach is selecting which buses to cluster together and how many clusters are needed. Clustering in this context refers to the process of partitioning a network into subsets of buses. An efficient network clustering method is proposed based on the PTDFs and the data mining techniques. This method is applied to the EI topology using the "Saguaro" supercomputer at ASU, a resource with sufficient memory and computational capability for handling this 60,000-bus and 80,000-branch system. The network equivalents generated by the proposed approaches are verified and tested for different operating conditions and promising results have been observed. / Dissertation/Thesis / Ph.D. Electrical Engineering 2012

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