Optimal measurement placement using PSO for state estimation

This paper presents an effective method based on Particle Swarm Optimization (PSO) to identify the optimal measurement placement of power system state estimation. The main objective is to simplify the complexity in finding the best measurement placement and provide a high accuracy level of estimated...

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Main Authors: Rosli, H.M., Mokhlis, Hazlie, Bakar, A.H.A.
Format: Conference or Workshop Item
Language:English
Published: 2012
Subjects:
Online Access:http://eprints.um.edu.my/7814/1/Optimal_measurement_placement_using_PSO_for_state_estimation.pdf
http://eprints.um.edu.my/7814/
https://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6450333
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spelling my.um.eprints.78142019-10-09T08:56:07Z http://eprints.um.edu.my/7814/ Optimal measurement placement using PSO for state estimation Rosli, H.M. Mokhlis, Hazlie Bakar, A.H.A. TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering This paper presents an effective method based on Particle Swarm Optimization (PSO) to identify the optimal measurement placement of power system state estimation. The main objective is to simplify the complexity in finding the best measurement placement and provide a high accuracy level of estimated state. The effectiveness of the proposed method is tested using the IEEE 30 bus system. Pseudo measurements of load injection are included as measurement data in assisting the state estimation computation. © 2012 IEEE. 2012 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.um.edu.my/7814/1/Optimal_measurement_placement_using_PSO_for_state_estimation.pdf Rosli, H.M. and Mokhlis, Hazlie and Bakar, A.H.A. (2012) Optimal measurement placement using PSO for state estimation. In: 2012 IEEE International Conference on Power and Energy, PECon 2012, 2012, Kota Kinabalu. https://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6450333
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
language English
topic TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Rosli, H.M.
Mokhlis, Hazlie
Bakar, A.H.A.
Optimal measurement placement using PSO for state estimation
description This paper presents an effective method based on Particle Swarm Optimization (PSO) to identify the optimal measurement placement of power system state estimation. The main objective is to simplify the complexity in finding the best measurement placement and provide a high accuracy level of estimated state. The effectiveness of the proposed method is tested using the IEEE 30 bus system. Pseudo measurements of load injection are included as measurement data in assisting the state estimation computation. © 2012 IEEE.
format Conference or Workshop Item
author Rosli, H.M.
Mokhlis, Hazlie
Bakar, A.H.A.
author_facet Rosli, H.M.
Mokhlis, Hazlie
Bakar, A.H.A.
author_sort Rosli, H.M.
title Optimal measurement placement using PSO for state estimation
title_short Optimal measurement placement using PSO for state estimation
title_full Optimal measurement placement using PSO for state estimation
title_fullStr Optimal measurement placement using PSO for state estimation
title_full_unstemmed Optimal measurement placement using PSO for state estimation
title_sort optimal measurement placement using pso for state estimation
publishDate 2012
url http://eprints.um.edu.my/7814/1/Optimal_measurement_placement_using_PSO_for_state_estimation.pdf
http://eprints.um.edu.my/7814/
https://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6450333
_version_ 1648736077921386496
score 13.18916