ADVANCED FAULT AREA IDENTIFICATION AND FAULT LOCATION FOR TRANSMISSION AND DISTRIBUTION SYSTEMS

Fault location reveals the exact information needed for utility crews to timely and promptly perform maintenance and system restoration. Therefore, accurate fault location is a key function in reducing outage time and enhancing power system reliability. Modern power systems are witnessing a trend of integrating more distributed generations (DG) into the grid. DG power outputs may be intermittent and can no longer be treated as constants in fault location method development. DG modeling is also difficult for fault location purpose. Moreover, most existing fault location methods are not applicable to simultaneous faults. To solve the challenges, this dissertation proposes three impedance-based fault location algorithms to pinpoint simultaneous faults for power transmission systems and distribution systems with high penetration of DGs. The proposed fault location algorithms utilize the voltage and/or current phasors that are captured by phasor measurement units. Bus impedance matrix technique is harnessed to establish the relationship between the measurements and unknown simultaneous fault locations. The distinct features of the proposed algorithms are that no fault types and fault resistances are needed to determine the fault locations. In particular, Type I and Type III algorithms do not need the information of source impedances and prefault measurements to locate the faults. Moreover, the effects of shunt capacitance are fully considered to improve fault location accuracy. The proposed algorithms for distribution systems are validated by evaluation studies using Matlab and Simulink SimPowerSystems on a 21 bus distribution system and the modified IEEE 34 node test system. Type II fault location algorithm for transmission systems is applicable to untransposed lines and is validated by simulation studies using EMTP on a 27 bus transmission system. Fault area identification method is proposed to reduce the number of line segments to be examined for fault location. In addition, an optimal fault location method that can identify possible bad measurement is proposed for enhanced fault location estimate. Evaluation studies show that the optimal fault location method is accurate and effective. The proposed algorithms can be integrated into the existing energy management system for enhanced fault management capability for power systems