
Identification of Voltage Disturbances in a 134-Bus System
Validated by an Artificial Immunological Algorithm
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In view of the complexity of Electric Power Systems (PES), caused by the sharp increase in electricity demand, it is necessary to use efficient tools so that utilities can deliver quality energy to their consumers. This book presents a means of classifying and detecting three voltage disturbances: sag, harmonics and swell. The tool used is based on the Artificial Immunological System (AIS), specifically the Negative Selection Algorithm (NSA). The simulations were carried out in ATPDraw software and the test system is real, with 134 load bars, 1 substation and 133 circuits, and a base voltage o...
In view of the complexity of Electric Power Systems (PES), caused by the sharp increase in electricity demand, it is necessary to use efficient tools so that utilities can deliver quality energy to their consumers. This book presents a means of classifying and detecting three voltage disturbances: sag, harmonics and swell. The tool used is based on the Artificial Immunological System (AIS), specifically the Negative Selection Algorithm (NSA). The simulations were carried out in ATPDraw software and the test system is real, with 134 load bars, 1 substation and 133 circuits, and a base voltage of 13.8 kV.