Title :
A new optimal adaptive under frequency load shedding Using Artificial Neural Networks
Author :
Moazzami, M. ; Khodabakhshian, A.
Author_Institution :
Dept. of Electr. Eng., Univ. of Isfahan, Isfahan, Iran
Abstract :
Different short circuits, load growth, generation shortage, and other faults which disturb the voltage and frequency stability are serious threats to the system security. The frequency and voltage instability causes dispersal of a power system into sub-systems, and leads to blackout as well as heavy damages of the system equipment. This paper presents a fast and optimal adaptive load shedding method, for isolated power system using Artificial Neural Networks (ANN). The proposed method is able to determine the necessary load shedding in all steps simultaneously and is much faster than conventional methods. This method has been tested on the New-England power system. The simulation results show that the proposed algorithm is fast, robust and optimal values of load shedding in different loading scenarios are obtained in comparison with conventional method.
Keywords :
Artificial neural networks; Circuit faults; Circuit stability; Frequency; Power system faults; Power system security; Power system simulation; Power system stability; System testing; Voltage; Artificial Neural Networks; Blackout; Load-Shedding; Power System Stability;
Conference_Titel :
Electrical Engineering (ICEE), 2010 18th Iranian Conference on
Conference_Location :
Isfahan, Iran
Print_ISBN :
978-1-4244-6760-0
DOI :
10.1109/IRANIANCEE.2010.5506963