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Thrikkakara, India

Vishnu T.P.,Government Model Engg College
Proceedings of 2015 IEEE International Conference on Power, Instrumentation, Control and Computing, PICC 2015 | Year: 2015

Recently semiconductor industry witnessed a revolutionary change with the development of wide band gap devices namely silicon carbide and gallium nitride. These devices are found to be superior to silicon because of their ability to be operated at high frequency, high temperature and high voltage with reduced switching losses. In this paper a comparison between Silicon and Silicon carbide semiconductor materials are done with the help of LTSpice software by considering DC-DC Buck Boost converter topology. It can be seen that the efficiency of the converter significantly increases when SiC switches are used for switching. With the use of SiC it is possible to increase the switching frequency which will considerably reduce the size of the filters making converter compact. At present, the only challenge faced by wide band gap device industry is its cost since the technology is not yet mature enough to make it easily available. © 2015 IEEE. Source


Vishnu T.P.,Government Model Engg College
Proceedings of 2015 IEEE International Conference on Power, Instrumentation, Control and Computing, PICC 2015 | Year: 2015

The static state of an electric power system is defined by the voltage magnitudes and angles at all network buses. The static-state estimator is a data processing algorithm for converting redundant meter readings and other available information into an estimate of the static-state of the system. This paper explains the concept of Weighted Least Square static state estimation. Static state estimation is performed on the data made available through the SCADA system. In this paper this data is obtained through Newton Raphson Load flow analysis. Power flow, power injections and voltage magnitudes are the various measurements taken from load flow analysis as the measurements for state estimation. Weighted least square method estimates the state of the power system based on the weight given to each measurement. A state estimator should have the ability to detect and identify the presence of a bad data. If a bad data is present among the measurements, then the estimated state variables will vary from the actual state variables. In this paper bad data detection is performed using Chi Squared test and bad data identification is performed using largest normalized residual method. Weighted least square algorithm is applied on an IEEE 14 bus. © 2015 IEEE. Source

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