Artificial immuned based real and reactive power rescheduling for voltage stability improvement in power system / Sazwan Ishak

Voltage stability improvement in power system is an important consideration in power system operation when involving heavily stressed system with large amount of real and reactive power demand and low voltage condition. In addition, generation and load rescheduling changes power flows system netw...

Full description

Saved in:
Bibliographic Details
Main Author: Ishak, Sazwan
Format: Thesis
Language:English
Published: 2008
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/597/1/TM_SAZWAN%20ISHAK%20EE%2008_5%201.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Voltage stability improvement in power system is an important consideration in power system operation when involving heavily stressed system with large amount of real and reactive power demand and low voltage condition. In addition, generation and load rescheduling changes power flows system networks and voltage profiles which will also affect voltage stability in power system. One of the methods known to be able to improve voltage stability is by means of real and reactive power rescheduling. This research proposed a new technique for rescheduling the real and reactive power generated by the generating units and also identifying suitable location and sizing for compensating capacitors based on Artificial Immune System (AIS) optimization technique. In this study two objective functions were consider for optimization which is L index technique and total loss minimization. The voltage stability L index also was utilized as an indicator for voltage stability evaluation. The study also considers contingency cases such as single line and double line outages. The performance of this technique was tested using the 57 bus IEEE Reliability Test Systems. A comparative study was made between the AIS optimization technique and the other biological computing technique namely the Evolutionary Programming (EP) optimization technique in performing similar task in order to identify the merits of former technique.