This is Part A. / <p> The equipment necessary to measure the loss in an optical fibre has been constructed. The details of the design and the results of testing the equipment are given. This equipment was designed to measure the loss induced in fibres by ionizing radiation, but can also be used to measure undamaged samples. A "dual-beam" system is used to increase the accuracy of the equipment.</p> <p> The equipment will measure the spectral attenuation of an optical fibre to an accuracy of ±1 dB/km between .9 and 1.65 μm if the fibre is at least 175m long and has an attenuation of less than 115 dB/km. Simple modifications to the equipment would reduce the sample length required for ±1 dB/km accuracy to 60 m.</p> <p> The minimum sample length is determined by the accuracy with which samples can be connected into the system. The maximum sample attenuation is determined by the signal to noise ratio. Methods of increasing the signal to noise ratio and the sample connection accuracy are discussed. Calculations based on the suggested improvements show that the sample length can be reduced to 45 m and the maximum attenuation increased to 750 dB/km for ±1 dB/km accuracy. The use of a testing method which does not require removal of the sample could give ±1 dB/km accuracy for 10 m samples.</p> <p> The operating and adjustment procedures for the equipment are given in the appendices to this report.</p> / Thesis / Master of Engineering (MEngr)

Various sensors distributed across different parts of the electric power grid provide measurements to the control center operator for situational awareness of the system. Voltage transformer, current transformer, relay and phasor measurement units (PMU) are types of sensors for power system monitoring. The utilities monitor the operating condition of their system by processing the measurements received from these various sensors using a state estimator. A state estimator refines these measurements, compensates for any lost data and provides a snapshot of the power system. The operator at the control center does further analysis using energy management system tools based on the most recent data and required state of the system. The electric power grid is vulnerable to blackouts caused by physical disturbances, human errors and external disasters. These disturbances can also cause loss of data, sensor failure or communication link failure. This research work focuses on comparing state estimation algorithms with loss of measurement data. The measurements are assumed to be lost as clustered and scattered data sets. Weighted Least Square (WLS), Least Absolute Value (LAV) and Iteratively Reweighted Least Squares (IRLS) implementation of Weighted Least Absolute Value (WLAV) algorithms are compared for state estimation with clustered and scattered loss of data. These algorithms are tested on a six bus, I 30 bus and 137 bus utility test cases. The test results indicate the best possible algorithm in several considered scenarios based on an error index. Additionally, phasor measurements data are included in two of the state estimation algorithms to study their ability to mitigate the loss of measurement data.