Case study of power system state estimation by using artificial neural network

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 w...

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Main Author:	Liang, Kai Feng
Format:	Undergraduates Project Papers
Language:	English
Published:	2010
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/2073/ http://umpir.ump.edu.my/id/eprint/2073/ http://umpir.ump.edu.my/id/eprint/2073/1/Liang%2C_Kai_Feng_%28_CD_5316_%29.pdf

id	ump-2073
recordtype	eprints
spelling	ump-20732015-03-03T07:54:34Z http://umpir.ump.edu.my/id/eprint/2073/ Case study of power system state estimation by using artificial neural network Liang, Kai Feng TK Electrical engineering. Electronics Nuclear engineering 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 2010-12 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/2073/1/Liang%2C_Kai_Feng_%28_CD_5316_%29.pdf Liang, Kai Feng (2010) Case study of power system state estimation by using artificial neural network. Faculty of Electrical & Electronic Engineering, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:55039&theme=UMP2
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Liang, Kai Feng Case study of power system state estimation by using artificial neural network
description	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
format	Undergraduates Project Papers
author	Liang, Kai Feng
author_facet	Liang, Kai Feng
author_sort	Liang, Kai Feng
title	Case study of power system state estimation by using artificial neural network
title_short	Case study of power system state estimation by using artificial neural network
title_full	Case study of power system state estimation by using artificial neural network
title_fullStr	Case study of power system state estimation by using artificial neural network
title_full_unstemmed	Case study of power system state estimation by using artificial neural network
title_sort	case study of power system state estimation by using artificial neural network
publishDate	2010
url	http://umpir.ump.edu.my/id/eprint/2073/ http://umpir.ump.edu.my/id/eprint/2073/ http://umpir.ump.edu.my/id/eprint/2073/1/Liang%2C_Kai_Feng_%28_CD_5316_%29.pdf
first_indexed	2023-09-18T21:55:35Z
last_indexed	2023-09-18T21:55:35Z
_version_	1777414057137012736

Case study of power system state estimation by using artificial neural network

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