Fault location and analysis in transmission and distribution networks
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Short-circuit faults are inevitable on transmission and distribution networks. In an effort to provide system operators with an accurate location estimate and reduce service restoration times, several impedance-based fault location algorithms have been developed for transmission and distribution networks. Each algorithm has specific input data requirements and make certain assumptions that may or may not hold true in a particular scenario. Identifying the best fault location approach, therefore, requires a thorough understanding of the working principle behind each algorithm. Moreover, impedance-based fault location algorithms require voltage and current phasors, captured by intelligent electronic devices (IEDs), to estimate the fault location. Unfortunately, voltage phasors are not always available due to operational constraints or equipment failure. Furthermore, impedance-based fault location algorithms assume a radial distribution feeder. With increased interconnection of distributed generators (DGs) to the feeder, this assumption is violated. DGs also contribute to the fault and severely compromise the accuracy of location estimates. In addition, the variability of certain DGs such as the fixed-speed wind turbine can alter fault current levels and result in relay misoperations. Finally, data recorded by IEDs during a fault contain a wealth of information and are prime for use in other applications that improve power system reliability. Based on the above background, the first objective of this dissertation is to present a comprehensive theory of impedance-based fault location algorithms. The contributions lie in clearly specifying the input data requirement of each algorithm and identifying their strengths and weaknesses. The following criteria are recommended for selecting the most suitable fault location algorithm: (a) data availability and (b) application scenario. The second objective is to develop fault location algorithms that use only the current to estimate the fault location. The simple but powerful algorithms allow system operators to locate faults even in the absence of voltage data. The third objective is to investigate the shortcomings of existing fault location algorithms when DGs are interconnected to the distribution feeder and develop an improved solution. A novel algorithm is proposed that require only the voltage and current phasors at the substation, is straightforward to implement, and is capable of locating all fault types. The fourth objective is to examine the effects of wind speed variation on the maximum and minimum fault current levels of a wind turbine and investigate the impact on relay settings. Contributions include developing an accurate time-domain model of a fixed-speed wind turbine with tower shadow and wind shear and verifying that the variation in wind speed does not violate relay settings calculated using the IEC 60909-0 Standard. The final objective is to exploit intelligent electronic device data for improving power system reliability. Contributions include validating the zero-sequence impedance of multi-terminal transmission lines with unsynchronized measurements, reconstructing the sequence of events, assessing relay performance, estimating the fault resistance, and verifying the accuracy of the system model. Overall, the research presented in this dissertation aims to describe the theory of impedance-based fault location, identify the sources of fault location error, propose solutions to overcome those error sources, and share lessons learned from analyzing intelligent electronic device data. The research is expected to reduce service downtime, prevent protection system misoperations, and improve power quality.