Optimal Micro-PMU Placement Using Mutual Information Theory in Distribution Networks

Micro-phasor measurement unit (μPMU) is under fast development and becoming more and more important for application in future distribution networks. It is unrealistic and unaffordable to place all buses with μPMUs because of the high costs, leading to the necessity of determining optim...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Zhi Wu [verfasserIn] Xiao Du [verfasserIn] Wei Gu [verfasserIn] Ping Ling [verfasserIn] Jinsong Liu [verfasserIn] Chen Fang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	micro-phasor measurement unit mutual information theory stochastic state estimation two-point estimation method

Übergeordnetes Werk:	In: Energies - MDPI AG, 2008, 11(2018), 7, p 1917
Übergeordnetes Werk:	volume:11 ; year:2018 ; number:7, p 1917

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/en11071917

Katalog-ID:	DOAJ025463616

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allfields	10.3390/en11071917 doi (DE-627)DOAJ025463616 (DE-599)DOAJ0468a5ec4de042ca96dfdd672be53db5 DE-627 ger DE-627 rakwb eng Zhi Wu verfasserin aut Optimal Micro-PMU Placement Using Mutual Information Theory in Distribution Networks 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Micro-phasor measurement unit (μPMU) is under fast development and becoming more and more important for application in future distribution networks. It is unrealistic and unaffordable to place all buses with μPMUs because of the high costs, leading to the necessity of determining optimal placement with minimal numbers of μPMUs in the distribution system. An optimal μPMU placement (OPP) based on the information entropy evaluation and node selection strategy (IENS) using greedy algorithm is presented in this paper. The uncertainties of distributed generations (DGs) and pseudo measurements are taken into consideration, and the two-point estimation method (2PEM) is utilized for solving stochastic state estimation problems. The set of buses selected by improved IENS, which can minimize the uncertainties of network and obtain system observability is considered as the optimal deployment of μPMUs. The proposed method utilizes the measurements of smart meters and pseudo measurements of load powers in the distribution systems to reduce the number of μPMUs and enhance the observability of the network. The results of the simulations prove the effectiveness of the proposed algorithm with the comparison of traditional topological methods for the OPP problem. The improved IENS method can obtain the optimal complete and incomplete μPMU placement in the distribution systems. micro-phasor measurement unit mutual information theory stochastic state estimation two-point estimation method Technology T Xiao Du verfasserin aut Wei Gu verfasserin aut Ping Ling verfasserin aut Jinsong Liu verfasserin aut Chen Fang verfasserin aut In Energies MDPI AG, 2008 11(2018), 7, p 1917 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:11 year:2018 number:7, p 1917 https://doi.org/10.3390/en11071917 kostenfrei https://doaj.org/article/0468a5ec4de042ca96dfdd672be53db5 kostenfrei http://www.mdpi.com/1996-1073/11/7/1917 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2018 7, p 1917
spelling	10.3390/en11071917 doi (DE-627)DOAJ025463616 (DE-599)DOAJ0468a5ec4de042ca96dfdd672be53db5 DE-627 ger DE-627 rakwb eng Zhi Wu verfasserin aut Optimal Micro-PMU Placement Using Mutual Information Theory in Distribution Networks 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Micro-phasor measurement unit (μPMU) is under fast development and becoming more and more important for application in future distribution networks. It is unrealistic and unaffordable to place all buses with μPMUs because of the high costs, leading to the necessity of determining optimal placement with minimal numbers of μPMUs in the distribution system. An optimal μPMU placement (OPP) based on the information entropy evaluation and node selection strategy (IENS) using greedy algorithm is presented in this paper. The uncertainties of distributed generations (DGs) and pseudo measurements are taken into consideration, and the two-point estimation method (2PEM) is utilized for solving stochastic state estimation problems. The set of buses selected by improved IENS, which can minimize the uncertainties of network and obtain system observability is considered as the optimal deployment of μPMUs. The proposed method utilizes the measurements of smart meters and pseudo measurements of load powers in the distribution systems to reduce the number of μPMUs and enhance the observability of the network. The results of the simulations prove the effectiveness of the proposed algorithm with the comparison of traditional topological methods for the OPP problem. The improved IENS method can obtain the optimal complete and incomplete μPMU placement in the distribution systems. micro-phasor measurement unit mutual information theory stochastic state estimation two-point estimation method Technology T Xiao Du verfasserin aut Wei Gu verfasserin aut Ping Ling verfasserin aut Jinsong Liu verfasserin aut Chen Fang verfasserin aut In Energies MDPI AG, 2008 11(2018), 7, p 1917 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:11 year:2018 number:7, p 1917 https://doi.org/10.3390/en11071917 kostenfrei https://doaj.org/article/0468a5ec4de042ca96dfdd672be53db5 kostenfrei http://www.mdpi.com/1996-1073/11/7/1917 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2018 7, p 1917
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allfieldsSound	10.3390/en11071917 doi (DE-627)DOAJ025463616 (DE-599)DOAJ0468a5ec4de042ca96dfdd672be53db5 DE-627 ger DE-627 rakwb eng Zhi Wu verfasserin aut Optimal Micro-PMU Placement Using Mutual Information Theory in Distribution Networks 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Micro-phasor measurement unit (μPMU) is under fast development and becoming more and more important for application in future distribution networks. It is unrealistic and unaffordable to place all buses with μPMUs because of the high costs, leading to the necessity of determining optimal placement with minimal numbers of μPMUs in the distribution system. An optimal μPMU placement (OPP) based on the information entropy evaluation and node selection strategy (IENS) using greedy algorithm is presented in this paper. The uncertainties of distributed generations (DGs) and pseudo measurements are taken into consideration, and the two-point estimation method (2PEM) is utilized for solving stochastic state estimation problems. The set of buses selected by improved IENS, which can minimize the uncertainties of network and obtain system observability is considered as the optimal deployment of μPMUs. The proposed method utilizes the measurements of smart meters and pseudo measurements of load powers in the distribution systems to reduce the number of μPMUs and enhance the observability of the network. The results of the simulations prove the effectiveness of the proposed algorithm with the comparison of traditional topological methods for the OPP problem. The improved IENS method can obtain the optimal complete and incomplete μPMU placement in the distribution systems. micro-phasor measurement unit mutual information theory stochastic state estimation two-point estimation method Technology T Xiao Du verfasserin aut Wei Gu verfasserin aut Ping Ling verfasserin aut Jinsong Liu verfasserin aut Chen Fang verfasserin aut In Energies MDPI AG, 2008 11(2018), 7, p 1917 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:11 year:2018 number:7, p 1917 https://doi.org/10.3390/en11071917 kostenfrei https://doaj.org/article/0468a5ec4de042ca96dfdd672be53db5 kostenfrei http://www.mdpi.com/1996-1073/11/7/1917 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2018 7, p 1917
language	English
source	In Energies 11(2018), 7, p 1917 volume:11 year:2018 number:7, p 1917
sourceStr	In Energies 11(2018), 7, p 1917 volume:11 year:2018 number:7, p 1917
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topic_facet	micro-phasor measurement unit mutual information theory stochastic state estimation two-point estimation method Technology T
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authorswithroles_txt_mv	Zhi Wu @@aut@@ Xiao Du @@aut@@ Wei Gu @@aut@@ Ping Ling @@aut@@ Jinsong Liu @@aut@@ Chen Fang @@aut@@
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author	Zhi Wu
spellingShingle	Zhi Wu misc micro-phasor measurement unit misc mutual information theory misc stochastic state estimation misc two-point estimation method misc Technology misc T Optimal Micro-PMU Placement Using Mutual Information Theory in Distribution Networks
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topic_title	Optimal Micro-PMU Placement Using Mutual Information Theory in Distribution Networks micro-phasor measurement unit mutual information theory stochastic state estimation two-point estimation method
topic	misc micro-phasor measurement unit misc mutual information theory misc stochastic state estimation misc two-point estimation method misc Technology misc T
topic_unstemmed	misc micro-phasor measurement unit misc mutual information theory misc stochastic state estimation misc two-point estimation method misc Technology misc T
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title	Optimal Micro-PMU Placement Using Mutual Information Theory in Distribution Networks
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title_full	Optimal Micro-PMU Placement Using Mutual Information Theory in Distribution Networks
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title_sort	optimal micro-pmu placement using mutual information theory in distribution networks
title_auth	Optimal Micro-PMU Placement Using Mutual Information Theory in Distribution Networks
abstract	Micro-phasor measurement unit (μPMU) is under fast development and becoming more and more important for application in future distribution networks. It is unrealistic and unaffordable to place all buses with μPMUs because of the high costs, leading to the necessity of determining optimal placement with minimal numbers of μPMUs in the distribution system. An optimal μPMU placement (OPP) based on the information entropy evaluation and node selection strategy (IENS) using greedy algorithm is presented in this paper. The uncertainties of distributed generations (DGs) and pseudo measurements are taken into consideration, and the two-point estimation method (2PEM) is utilized for solving stochastic state estimation problems. The set of buses selected by improved IENS, which can minimize the uncertainties of network and obtain system observability is considered as the optimal deployment of μPMUs. The proposed method utilizes the measurements of smart meters and pseudo measurements of load powers in the distribution systems to reduce the number of μPMUs and enhance the observability of the network. The results of the simulations prove the effectiveness of the proposed algorithm with the comparison of traditional topological methods for the OPP problem. The improved IENS method can obtain the optimal complete and incomplete μPMU placement in the distribution systems.
abstractGer	Micro-phasor measurement unit (μPMU) is under fast development and becoming more and more important for application in future distribution networks. It is unrealistic and unaffordable to place all buses with μPMUs because of the high costs, leading to the necessity of determining optimal placement with minimal numbers of μPMUs in the distribution system. An optimal μPMU placement (OPP) based on the information entropy evaluation and node selection strategy (IENS) using greedy algorithm is presented in this paper. The uncertainties of distributed generations (DGs) and pseudo measurements are taken into consideration, and the two-point estimation method (2PEM) is utilized for solving stochastic state estimation problems. The set of buses selected by improved IENS, which can minimize the uncertainties of network and obtain system observability is considered as the optimal deployment of μPMUs. The proposed method utilizes the measurements of smart meters and pseudo measurements of load powers in the distribution systems to reduce the number of μPMUs and enhance the observability of the network. The results of the simulations prove the effectiveness of the proposed algorithm with the comparison of traditional topological methods for the OPP problem. The improved IENS method can obtain the optimal complete and incomplete μPMU placement in the distribution systems.
abstract_unstemmed	Micro-phasor measurement unit (μPMU) is under fast development and becoming more and more important for application in future distribution networks. It is unrealistic and unaffordable to place all buses with μPMUs because of the high costs, leading to the necessity of determining optimal placement with minimal numbers of μPMUs in the distribution system. An optimal μPMU placement (OPP) based on the information entropy evaluation and node selection strategy (IENS) using greedy algorithm is presented in this paper. The uncertainties of distributed generations (DGs) and pseudo measurements are taken into consideration, and the two-point estimation method (2PEM) is utilized for solving stochastic state estimation problems. The set of buses selected by improved IENS, which can minimize the uncertainties of network and obtain system observability is considered as the optimal deployment of μPMUs. The proposed method utilizes the measurements of smart meters and pseudo measurements of load powers in the distribution systems to reduce the number of μPMUs and enhance the observability of the network. The results of the simulations prove the effectiveness of the proposed algorithm with the comparison of traditional topological methods for the OPP problem. The improved IENS method can obtain the optimal complete and incomplete μPMU placement in the distribution systems.
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