SOFT-COMPUTING BASED DATA MINING | APPLIED FOR FAULT DIAGNOSIS AND RELIABILITY PROBLEMS EVALUATION IN POWER SYSTEM

A. S. Zadgaonkar (u. a.)

ISBN 10: 6202676264 / ISBN 13: 9786202676267

Published by LAP LAMBERT Academic Publishing, 2020

About this Item

SOFT-COMPUTING BASED DATA MINING | APPLIED FOR FAULT DIAGNOSIS AND RELIABILITY PROBLEMS EVALUATION IN POWER SYSTEM | A. S. Zadgaonkar (u. a.) | Taschenbuch | 192 S. | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202676267 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 118812566

Bibliographic Details

• Title: SOFT-COMPUTING BASED DATA MINING | APPLIED FOR FAULT DIAGNOSIS AND RELIABILITY PROBLEMS EVALUATION IN POWER SYSTEM
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2020
• Language: English
• ISBN 10: 6202676264
• ISBN 13: 9786202676267
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 13D millimeters 220 millimeters width by 150 millimeters height by 13 millimeters depth
• Weight: 304 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

In this thesis a noble method of fault locating in a radial power distribution system is discussed. Interval type-2 fuzzy system will ease the calculation involved. The history associated with fault occurred in power system can be effectively used as a strong database. This database will act as the trainer to the interval type-2 fuzzy expert system. A rich history of faulty area will enhance the performance of the interval type-2 Fuzzy Fault Identification System (IT2FFIS). Fault section location aims to identify the faulty area in the power system using the post fault status of protective relays and circuit breakers and diagnose the cause of a fault that has occurred. Restoration cost can be significantly reduced by accurately identifying a fault location and its cause, which also reduces the restoration time of the faulty section. In this thesis methodology based on interval type-2 fuzzy expert system is discussed for assistance to the operators for easy fault detection.The interval type-2 fuzzy sets are used here for data mining for fault location in the distribution system.