Adaptive underfrequency load shedding using particle swarm optimization algorithm

Abstract Underfrequency load shedding plays an important role in prevention of the power system blackout. The common load shedding methods are based on measuring the frequency first derivative; therefore, an error in measurement process can highly affect their performance. Also, for proper performance of these load shedding schemes, the exact value of some parameters of power system is needed. Any error in estimation of these parameters reduces the reliability of these load shedding schemes. In this paper, an underfrequency load shedding method based on the forecast minimum frequency of system is proposed. In this method, the samples of the power system frequency are taken after disturbance; then, particle swarm optimization algorithm is used to forecast the minimum frequency based on these samples. To verify the effectiveness of the proposed load shedding scheme, its performance has been compared with a newly suggested method.

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Bibliographic Details
Main Authors: Ketabi,Abbas, Hajiakbari Fini,Masoud
Format: Digital revista
Language:English
Published: Universidad Nacional Autónoma de México, Instituto de Ciencias Aplicadas y Tecnología 2017
Online Access:http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1665-64232017000100054
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