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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2012
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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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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 |
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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 |
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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 |
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2012 |
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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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1648736077921386496 |
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13.18916 |