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This dissertation presents novel application of spintronic sensors in power system monitoring. Spintronic sensors including giant magnetoresistance (GMR) sensors and tunnel magnetoresistance (TMR) sensors are advanced in magnetic field sensing. In power industry, power-frequency magnetic fields are produced by electric power sources, equipment and power lines. Thus it is impossible for monitoring the power system by sensing the emanated magnetic field. In Chapter 2, a novel concept based on magnetoresistive (MR) sensors is proposed for transmission line monitoring. A proof-of-concept laboratory setup was constructed and a series of experiments were carried out for demonstration. The result shows the feasibility of using this power system monitoring method in reality. In order to handle complicated transmission line configuration with the proposed method, an improved current monitoring technology is proposed in Chapter 3. It is realized by developing a current source reconstruction method based on stochastic optimization strategy. This concept of current monitoring by magnetic field sensing and current source reconstruction was experimentally implemented and verified in our laboratory setup. A typical model of 500 kV three-phase transmission lines was simulated to further corroborate this technology. The reconstruction results for the 500 kV transmission lines verify the feasibility and practicality of this novel current monitoring technology based on magnetic field sensing at the top of a transmission tower for monitoring overhead transmission lines. Chapter 4 offers further improvement of the transmission-line monitoring technology. Improved technology can measure simultaneously both electrical and spatial parameters of multiple lines in real-time in a non-contact way. Two typical models of high-voltage three-phase transmission lines were simulated and the resulting magnetic fields were calculated. A source reconstruction method was developed to reconstruct the spatial and electrical parameters from the magnetic field emanated by the overhead transmission lines. The reconstruction results for the 500 kV and 220 kV transmission lines verify the feasibility and practicality of this non-contact transmission-line monitoring technology based on magnetic field sensing. As well as the high-voltage transmission-line, the technology is applied in underground power cable operation-state monitoring and energization-status identification in Chapter 5. The magnetic field distribution of the cable was studied by using finite element method (FEM) for the power cable operating in different states, i.e. current-energized state (the cable is energized and carries load current) and voltage-energized state (the cable is energized but carries no load current). Application of this method was demonstrated on an 11 kV cable with metallic outer sheath. The results highly matched with the actual source parameters of the cable. An experimental setup was constructed and the test results were used for demonstration this method. In order to enhance the applicability of the proposed power system monitoring technology in practice, magnetic flux concentrators (MFC) and magnetic shielding are studied and designed for MR sensors in Chapter 6. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

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Thesis (M.S. in Operations Research)--Naval Postgraduate School, March 2004. / Thesis advisor(s): Susan M. Sanchez. Includes bibliographical references (p. 61-65). Also available online.

In recent years, considerable attention has been focused on the application of orthogonal expansions to system analysis, parameter identification, model reduction and control system design. However, little research has been done in applying their useful properties to Power System analysis and control. This research attempts to make some inroads in applying the so called " orthogonal expansion approach " to analysis and control of Power systems, especially the latter. A set of orthogonal functions commonly called Walsh functions in system science after it's discoverer J.L. Walsh [1923] have been successfully used for parameter identification in the presence of severe nonlinearities. The classical optimal control problem is applied to a synchronous machine infinite bus system via the orthogonal expansion approach and a convenient method outlined for designing PID controllers which can achieve prespecified closed loop response characteristics. The latter is then applied for designing a dynamic series capacitor controller for a single machine infinite bus system. / Graduation date: 1993

Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2010. / Committee Chair: Dr. Ronald G. Harley; Committee Member: Dr. Bonnie Heck; Committee Member: Dr. Deepak Divan; Committee Member: Dr. Ganesh K. Venayagamoorthy; Committee Member: Dr. Miroslav Begovic. Part of the SMARTech Electronic Thesis and Dissertation Collection.

A research project submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, in fulfillment of the requirements for the degree of Master of Science in Engineering, 2018. / The power system inertia immediately following small and large system disturbances was investigated. By understanding factors affecting the system inertia and primary frequency response behaviour, an online inertia model was developed. Historical data was extracted from the Eskom Energy Management System (EMS) and Wide Area Monitoring System (WAMS). The developed model using Multivariate Analysis (MVA) includes measured and estimated data from Eskom generators, Renewable Energy Sources (RESs) and the interconnected Southern African Power Pool (SAPP). Inertia plus Fast Primary (Frequency) Response (FPR) (as determined by the load behaviour) and system inertia models were developed from June 2015-December 2016 and validated with past frequency disturbance events (June 2014-March 2017). From the comparison between the measured and model results for 355 actual disturbances, 225 disturbances resulted in errors within ±5% and 51 events resulted in errors between ±5% and ±10%. Eight disturbances caused errors greater than ±10%, which were largely from trips at particular large power stations and HVDC. During a large disturbance, the multivariate coefficients for Renewable Energy Sources, HVDC and interconnectors were very small for the pure inertia model (excluding the load frequency behaviour and the generator damping). In contrast, the spinning reserve provides significant contribution and is location based. The location of a disturbance affects the FPR behaviour and the system inertia but not the Rate of Change of Frequency (RoCoF) with reference to the central power station. The strong and weak areas with respect of the stiffness of the system (extent of frequency nadir for particular disturbances) were identified. This can contribute to future grid planning and real-time operations in managing the system inertia and primary frequency response. The model is expected to improve with time, as the accuracy of a statistical approach requires large amounts of data. The model can be used to determine and monitor the maximum level of RES in real time. / XL2019