Soft computing techniques in power system analysis

2025 658 1340 12 27281 document 1340 ann_simulation_results.pdf application/pdf 637056 2011-09-09 10:22:57 https://vuir.vu.edu.au/2025/1/ann_simulation_results.pdf 27282 document 1340 Table_A3_1.pdf application/pdf 15558 2011-09-09 10:22:57 https://vuir.vu.edu.au/2025/1/Table_A3_1.pdf 27283 document 1340 Chapter_6_Tables.pdf application/pdf 3783527 2011-09-09 10:22:57 https://vuir.vu.edu.au/2025/1/Chapter_6_Tables.pdf 27284 document 1340 thesis.pdf application/pdf 5894899 2011-09-09 10:22:57 https://vuir.vu.edu.au/2025/1/thesis.pdf 2025 1 application/pdf text en public

thesis.pdf

http://eprints.org/relation/hasVolatileVersion https://vuir.vu.edu.au/id/document/10153 http://eprints.org/relation/hasVersion https://vuir.vu.edu.au/id/document/10153 http://eprints.org/relation/hasIndexCodesVersion https://vuir.vu.edu.au/id/document/10153 10153 3 1732834 document 10153 indexcodes.txt text/x-c 6476ba4d7ff141171a12f16cfa77b1b1 MD5 103408 2013-02-06 12:51:01 https://vuir.vu.edu.au/2025/2/indexcodes.txt 2025 2 2 text/x-c other Generate index codes conversion from application/pdf to indexcodes en public

indexcodes.txt

http://eprints.org/relation/isVersionOf https://vuir.vu.edu.au/id/document/1340 http://eprints.org/relation/isVolatileVersionOf https://vuir.vu.edu.au/id/document/1340 http://eprints.org/relation/isIndexCodesVersionOf https://vuir.vu.edu.au/id/document/1340 64419 2 2401277 document 64419 lightbox.jpg image/png c23439fb728ce519d1fb6d2979a9aeee MD5 38122 2020-09-22 04:20:04 https://vuir.vu.edu.au/2025/4/lightbox.jpg 2025 4 4 image/png other Thumbnails conversion from text to thumbnail_lightbox en staffonly

lightbox.jpg

preview.jpg

medium.jpg

small.jpg

http://eprints.org/relation/isVersionOf https://vuir.vu.edu.au/id/dark_document/64418 http://eprints.org/relation/isVolatileVersionOf https://vuir.vu.edu.au/id/dark_document/64418 http://eprints.org/relation/issmallThumbnailVersionOf https://vuir.vu.edu.au/id/dark_document/64418 archive 301 disk0/00/00/20/25 2009-04-05 17:00:55 2021-08-27 07:42:39 2009-04-05 17:00:55 thesis show Fernando Kurukulasuriya Joseph Tilak Nihal Fernando, Kurukulasuriya Joseph Tilak Nihal Soft computing techniques in power system analysis unpub 290000 tafeengineering Soft computing techniques, Power system analysis, Voltage stability Soft computing is a concept that has come into prominence in recent times and its application to power system analysis is still more recent. This thesis explores the application of soft computing techniques in the area of voltage stability of power systems. Soft computing, as opposed to conventional “hard” computing, is a technique that is tolerant of imprecision, uncertainty, partial truth and approximation. Its methods are based on the working of the human brain and it is commonly known as artificial intelligence. The human brain is capable of arriving at valid conclusions based on incomplete and partial data obtained from prior experience. It is an approximation of this process on a very small scale that is used in soft computing. Some of the important branches of soft computing (SC) are artificial neural networks (ANNs), fuzzy logic (FL), genetic computing (GC) and probabilistic reasoning (PR). The soft computing methods are robust and low cost. It is to be noted that soft computing methods are used in such diverse fields as missile guidance, robotics, industrial plants, pattern recognition, market prediction, patient diagnosis, logistics and of course power system analysis and prediction. However in all these fields its application is comparatively new and research is being carried out continuously in many universities and research institutions worldwide. The research presented in this thesis uses the soft computing method of Artificial Neural Networks (ANN’s) for the prediction of voltage instability in power systems. The research is very timely and current and would be a substantial contribution to the present body of knowledge in soft computing and voltage stability, which by itself is a new field. The methods developed in this research would be faster and more economical than presently available methods enabling their use online. 2008 submitted 64418 2 2401275 dark_document 64418 Fernando, Kurukulasuriya.pdf application/pdf a90b59dd790e7319b7a9cd59472e6269 MD5 44049 2020-09-22 04:19:34 2025 3 3 application/pdf text VURR permission form en staffonly

Fernando, Kurukulasuriya.pdf

other public 544 Victoria University Faculty of Health, Engineering and Science phd Includes bibliographical references: pp. 220-224 FALSE