A new algorithmic approach on distribution system power quality monitoring and controlled islanding with distributed generation

Abstract

A decade ago, electrical Power Quality (PQ) issue had reported a significant consideration due to the availability of coordination of Renewable Energy (RE) sources into the grid, microprocessor based controlled loads and large penetration of power electronics based loads. Particularly, in a deregulated environment, PQ has turned into a vital theme of discussion and research. There is failure or mal-operation of electric equipment due to voltage, current or frequency deviation causing this issue. At rated magnitude and frequency that need to keep up the close sinusoidal waveform of power system bus voltages and currents referred to as electric Power Quality. Hence proven voltage qualities, current quality, reliability of service, quality of power supply, the electric PQ are frequently utilized. Effectiveness of power system equipments defined by generators and control equipment has diminished PQ disturbances. In this manner, the issue present in the PQ is vital for consumers. There is a need to investigate PQ effects on the disturbance on the customer equipment of the power system. Faults in the power system are the essential source of PQ disturbances. During faulty conditions in the power network, PQ disturbances with high magnitude and short durations have proliferated. This thesis manages to detect and categorize single and combined PQ disturbances in the distribution system by utilizing Fuzzy Logic Classifier (FLC) oriented Gravitational Search Algorithm (GSA). GSA-FLC systems have utilized to detect and categorize the single and multiple PQ disturbances from the different kinds of events present in the input power signal newline