Case study of power system state estimation by using artificial neural network / (Record no. 2808)

MARC details
000 -LEADER
fixed length control field 02611nam a2200265 a 4500
001 - CONTROL NUMBER
control field vtls000055039
003 - CONTROL NUMBER IDENTIFIER
control field KUKTEM
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251114204501.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 110722t2009 my a f m 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number THE0006680(Local)
039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE]
Level of rules in bibliographic description 201905171505
Level of effort used to assign nonsubject heading access points amirul
-- 201107221559
-- ida
040 ## - CATALOGING SOURCE
Original cataloging agency UMP
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) TK1005 .L53 2010 rs Bc.
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Liang, Kai Feng
245 10 - TITLE STATEMENT
Title Case study of power system state estimation by using artificial neural network /
Statement of responsibility, etc. Liang Kai Feng
246 3# - VARYING FORM OF TITLE
Title proper/short title Case study of power system state estimation by using artificial neural network
Medium [computer file]
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Kuantan, Pahang :
Name of publisher, distributor, etc. UMP,
Date of publication, distribution, etc. 2010
300 ## - PHYSICAL DESCRIPTION
Extent xiv, 68 p. :
Other physical details ill. (some col.) ;
Dimensions 30 cm. + 1 computer disc
502 ## - DISSERTATION NOTE
Dissertation note Project paper (Bachelor of Electrical Engineering (Power System)) -- Universiti Malaysia Pahang - 2010
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Bibliography : p. 67-68
520 3# - SUMMARY, ETC.
Summary, etc. This is a study that mains in Artificial Neural Network technique which introduces approach towards the problem of errors that arise due to the practical equipment and actual measurements in distribution systems. Real time data or the state variables measured in power system are often incorporated with error. This project outputs a software program that performs power system state estimation using artificial intelligence optimization. It was developed using Artificial Neural Network in MATLAB software. This method considers nonlinear characteristics of the practical equipment and actual measurements in distribution systems. It can estimate bus voltage and load angle values at each node by minimizing difference between measured and calculated state variables. This is accomplished by the utilization of load flow analysis program which acts as computerized conventional solution that calculates mathematically the exact target outputs in accordance to the inputs applied. The significant functions of the developed software program also include the accurate estimation of power system state with insufficient input data applied. This project has successfully built a power system state estimation software program that perform accurate state estimation achieving desired outputs even when provided with insufficient input data magnitudes. It helps identify the current operating state of the system on which, security assessment functions and hence contingencies can be analyzed leading to the required corrective actions
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Electric power system
General subdivision State estimation
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Neural networks
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Date acquired Total checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
  Not lost   Not for loan UMPLIB PEKAN UMPLIB PEKAN 04/09/2019   TK1005 .L53 2010 rs Bc. 0000058232 04/09/2019 1 04/09/2019 Final Year Report
  Not lost   Not for loan UMPLIB PEKAN UMPLIB PEKAN 04/09/2019   CD 5316 | TK1005 .L53 2010 rs Bc. 0000058233 04/09/2019 1 04/09/2019 Final Year Report

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