Adaptive OCR coordination in distribution system with distributed energy resources contribution

More and more distributed energy resources (DERs) are being added to the medium-voltage (MV) or low-voltage (LV) radial distribution networks (RDNs). These distributed power sources will cause the redistribution of power flow and fault current, bringing new challenges to the coordination of power sy...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Tung-Sheng Zhan [verfasserIn] Chun-Lien Su [verfasserIn] Yih-Der Lee [verfasserIn] Jheng-Lun Jiang [verfasserIn] Jin-Ting Yu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	relay protection coordination time multiplier setting (tms) coordination time interval (cti) modified particle swarm optimization (mpso)

Übergeordnetes Werk:	In: AIMS Energy - AIMS Press, 2014, 11(2023), 6, Seite 1278-1305
Übergeordnetes Werk:	volume:11 ; year:2023 ; number:6 ; pages:1278-1305

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3934/energy.2023058

Katalog-ID:	DOAJ099126141

Internformat


LEADER	01000naa a22002652 4500
001	DOAJ099126141
003	DE-627
005	20240414013927.0
007	cr uuu---uuuuu
008	240414s2023 xx \|\|\|\|\|o 00\| \|\|eng c
024	7		\|a 10.3934/energy.2023058 \|2 doi
035			\|a (DE-627)DOAJ099126141
035			\|a (DE-599)DOAJb646447642b04ee8b9f202616c5c6154
040			\|a DE-627 \|b ger \|c DE-627 \|e rakwb
041			\|a eng
050		0	\|a TK1001-1841
050		0	\|a TJ807-830
100	0		\|a Tung-Sheng Zhan \|e verfasserin \|4 aut
245	1	0	\|a Adaptive OCR coordination in distribution system with distributed energy resources contribution
264		1	\|c 2023
336			\|a Text \|b txt \|2 rdacontent
337			\|a Computermedien \|b c \|2 rdamedia
338			\|a Online-Ressource \|b cr \|2 rdacarrier
520			\|a More and more distributed energy resources (DERs) are being added to the medium-voltage (MV) or low-voltage (LV) radial distribution networks (RDNs). These distributed power sources will cause the redistribution of power flow and fault current, bringing new challenges to the coordination of power system protection. An adaptive protection coordination strategy is proposed in this paper. It will trace the connectivity of the system structure to determine the set of relay numbers as a tracking path. According to the topology of the system structure, the tracking path can be divided into two categories: the main feeder path and the branch path. The time multiplier setting (TMS) of each relay can be used to evaluate the operation time of the over-current relay (OCR), and the operation time of the relay can be used to evaluate the fitness of the TMS setting combination. Furthermore, the relay protection coordination problem can be modeled to minimize the accumulated summation of all primary and backup relay operation time (OT) subject to the coordination time interval (CTI) limitation. A modified particle swarm optimization (MPSO) algorithm with adaptive self-cognition and society operation scheme (ASSOS) was proposed and utilized to determine TMS for each relay on the tracking path. A 16-bus test MV system with distributed generators (DGs) will be applied to test the adaptive protection coordination approach proposed in this paper. The results show that the proposed MPSO algorithm reduces the overall OT and relieves the impact on protection coordination settings after DG joins the system. The paper also tests and compares the proposed MPSO with other metaheuristic intelligence-based random search algorithms to prove that MPSO possesses with increased efficiency and performance.
650		4	\|a relay protection coordination
650		4	\|a time multiplier setting (tms)
650		4	\|a coordination time interval (cti)
650		4	\|a modified particle swarm optimization (mpso)
653		0	\|a Production of electric energy or power. Powerplants. Central stations
653		0	\|a Renewable energy sources
700	0		\|a Chun-Lien Su \|e verfasserin \|4 aut
700	0		\|a Yih-Der Lee \|e verfasserin \|4 aut
700	0		\|a Jheng-Lun Jiang \|e verfasserin \|4 aut
700	0		\|a Jin-Ting Yu \|e verfasserin \|4 aut
773	0	8	\|i In \|t AIMS Energy \|d AIMS Press, 2014 \|g 11(2023), 6, Seite 1278-1305 \|w (DE-627)790616165 \|w (DE-600)2777109-X \|x 23338334 \|7 nnns
773	1	8	\|g volume:11 \|g year:2023 \|g number:6 \|g pages:1278-1305
856	4	0	\|u https://doi.org/10.3934/energy.2023058 \|z kostenfrei
856	4	0	\|u https://doaj.org/article/b646447642b04ee8b9f202616c5c6154 \|z kostenfrei
856	4	0	\|u https://www.aimspress.com/article/doi/10.3934/energy.2023058?viewType=HTML \|z kostenfrei
856	4	2	\|u https://doaj.org/toc/2333-8334 \|y Journal toc \|z kostenfrei
912			\|a GBV_USEFLAG_A
912			\|a SYSFLAG_A
912			\|a GBV_DOAJ
912			\|a GBV_ILN_11
912			\|a GBV_ILN_20
912			\|a GBV_ILN_22
912			\|a GBV_ILN_23
912			\|a GBV_ILN_24
912			\|a GBV_ILN_31
912			\|a GBV_ILN_39
912			\|a GBV_ILN_40
912			\|a GBV_ILN_60
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_95
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_151
912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_213
912			\|a GBV_ILN_230
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2009
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4249
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4367
912			\|a GBV_ILN_4700
951			\|a AR
952			\|d 11 \|j 2023 \|e 6 \|h 1278-1305

Indexfelder

author_variant	t s z tsz c l s cls y d l ydl j l j jlj j t y jty
matchkey_str	article:23338334:2023----::dpieccodntoidsrbtossewtdsrbtdnr
hierarchy_sort_str	2023
callnumber-subject-code	TK
publishDate	2023
allfields	10.3934/energy.2023058 doi (DE-627)DOAJ099126141 (DE-599)DOAJb646447642b04ee8b9f202616c5c6154 DE-627 ger DE-627 rakwb eng TK1001-1841 TJ807-830 Tung-Sheng Zhan verfasserin aut Adaptive OCR coordination in distribution system with distributed energy resources contribution 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier More and more distributed energy resources (DERs) are being added to the medium-voltage (MV) or low-voltage (LV) radial distribution networks (RDNs). These distributed power sources will cause the redistribution of power flow and fault current, bringing new challenges to the coordination of power system protection. An adaptive protection coordination strategy is proposed in this paper. It will trace the connectivity of the system structure to determine the set of relay numbers as a tracking path. According to the topology of the system structure, the tracking path can be divided into two categories: the main feeder path and the branch path. The time multiplier setting (TMS) of each relay can be used to evaluate the operation time of the over-current relay (OCR), and the operation time of the relay can be used to evaluate the fitness of the TMS setting combination. Furthermore, the relay protection coordination problem can be modeled to minimize the accumulated summation of all primary and backup relay operation time (OT) subject to the coordination time interval (CTI) limitation. A modified particle swarm optimization (MPSO) algorithm with adaptive self-cognition and society operation scheme (ASSOS) was proposed and utilized to determine TMS for each relay on the tracking path. A 16-bus test MV system with distributed generators (DGs) will be applied to test the adaptive protection coordination approach proposed in this paper. The results show that the proposed MPSO algorithm reduces the overall OT and relieves the impact on protection coordination settings after DG joins the system. The paper also tests and compares the proposed MPSO with other metaheuristic intelligence-based random search algorithms to prove that MPSO possesses with increased efficiency and performance. relay protection coordination time multiplier setting (tms) coordination time interval (cti) modified particle swarm optimization (mpso) Production of electric energy or power. Powerplants. Central stations Renewable energy sources Chun-Lien Su verfasserin aut Yih-Der Lee verfasserin aut Jheng-Lun Jiang verfasserin aut Jin-Ting Yu verfasserin aut In AIMS Energy AIMS Press, 2014 11(2023), 6, Seite 1278-1305 (DE-627)790616165 (DE-600)2777109-X 23338334 nnns volume:11 year:2023 number:6 pages:1278-1305 https://doi.org/10.3934/energy.2023058 kostenfrei https://doaj.org/article/b646447642b04ee8b9f202616c5c6154 kostenfrei https://www.aimspress.com/article/doi/10.3934/energy.2023058?viewType=HTML kostenfrei https://doaj.org/toc/2333-8334 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 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 2023 6 1278-1305
spelling	10.3934/energy.2023058 doi (DE-627)DOAJ099126141 (DE-599)DOAJb646447642b04ee8b9f202616c5c6154 DE-627 ger DE-627 rakwb eng TK1001-1841 TJ807-830 Tung-Sheng Zhan verfasserin aut Adaptive OCR coordination in distribution system with distributed energy resources contribution 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier More and more distributed energy resources (DERs) are being added to the medium-voltage (MV) or low-voltage (LV) radial distribution networks (RDNs). These distributed power sources will cause the redistribution of power flow and fault current, bringing new challenges to the coordination of power system protection. An adaptive protection coordination strategy is proposed in this paper. It will trace the connectivity of the system structure to determine the set of relay numbers as a tracking path. According to the topology of the system structure, the tracking path can be divided into two categories: the main feeder path and the branch path. The time multiplier setting (TMS) of each relay can be used to evaluate the operation time of the over-current relay (OCR), and the operation time of the relay can be used to evaluate the fitness of the TMS setting combination. Furthermore, the relay protection coordination problem can be modeled to minimize the accumulated summation of all primary and backup relay operation time (OT) subject to the coordination time interval (CTI) limitation. A modified particle swarm optimization (MPSO) algorithm with adaptive self-cognition and society operation scheme (ASSOS) was proposed and utilized to determine TMS for each relay on the tracking path. A 16-bus test MV system with distributed generators (DGs) will be applied to test the adaptive protection coordination approach proposed in this paper. The results show that the proposed MPSO algorithm reduces the overall OT and relieves the impact on protection coordination settings after DG joins the system. The paper also tests and compares the proposed MPSO with other metaheuristic intelligence-based random search algorithms to prove that MPSO possesses with increased efficiency and performance. relay protection coordination time multiplier setting (tms) coordination time interval (cti) modified particle swarm optimization (mpso) Production of electric energy or power. Powerplants. Central stations Renewable energy sources Chun-Lien Su verfasserin aut Yih-Der Lee verfasserin aut Jheng-Lun Jiang verfasserin aut Jin-Ting Yu verfasserin aut In AIMS Energy AIMS Press, 2014 11(2023), 6, Seite 1278-1305 (DE-627)790616165 (DE-600)2777109-X 23338334 nnns volume:11 year:2023 number:6 pages:1278-1305 https://doi.org/10.3934/energy.2023058 kostenfrei https://doaj.org/article/b646447642b04ee8b9f202616c5c6154 kostenfrei https://www.aimspress.com/article/doi/10.3934/energy.2023058?viewType=HTML kostenfrei https://doaj.org/toc/2333-8334 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 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 2023 6 1278-1305
allfields_unstemmed	10.3934/energy.2023058 doi (DE-627)DOAJ099126141 (DE-599)DOAJb646447642b04ee8b9f202616c5c6154 DE-627 ger DE-627 rakwb eng TK1001-1841 TJ807-830 Tung-Sheng Zhan verfasserin aut Adaptive OCR coordination in distribution system with distributed energy resources contribution 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier More and more distributed energy resources (DERs) are being added to the medium-voltage (MV) or low-voltage (LV) radial distribution networks (RDNs). These distributed power sources will cause the redistribution of power flow and fault current, bringing new challenges to the coordination of power system protection. An adaptive protection coordination strategy is proposed in this paper. It will trace the connectivity of the system structure to determine the set of relay numbers as a tracking path. According to the topology of the system structure, the tracking path can be divided into two categories: the main feeder path and the branch path. The time multiplier setting (TMS) of each relay can be used to evaluate the operation time of the over-current relay (OCR), and the operation time of the relay can be used to evaluate the fitness of the TMS setting combination. Furthermore, the relay protection coordination problem can be modeled to minimize the accumulated summation of all primary and backup relay operation time (OT) subject to the coordination time interval (CTI) limitation. A modified particle swarm optimization (MPSO) algorithm with adaptive self-cognition and society operation scheme (ASSOS) was proposed and utilized to determine TMS for each relay on the tracking path. A 16-bus test MV system with distributed generators (DGs) will be applied to test the adaptive protection coordination approach proposed in this paper. The results show that the proposed MPSO algorithm reduces the overall OT and relieves the impact on protection coordination settings after DG joins the system. The paper also tests and compares the proposed MPSO with other metaheuristic intelligence-based random search algorithms to prove that MPSO possesses with increased efficiency and performance. relay protection coordination time multiplier setting (tms) coordination time interval (cti) modified particle swarm optimization (mpso) Production of electric energy or power. Powerplants. Central stations Renewable energy sources Chun-Lien Su verfasserin aut Yih-Der Lee verfasserin aut Jheng-Lun Jiang verfasserin aut Jin-Ting Yu verfasserin aut In AIMS Energy AIMS Press, 2014 11(2023), 6, Seite 1278-1305 (DE-627)790616165 (DE-600)2777109-X 23338334 nnns volume:11 year:2023 number:6 pages:1278-1305 https://doi.org/10.3934/energy.2023058 kostenfrei https://doaj.org/article/b646447642b04ee8b9f202616c5c6154 kostenfrei https://www.aimspress.com/article/doi/10.3934/energy.2023058?viewType=HTML kostenfrei https://doaj.org/toc/2333-8334 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 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 2023 6 1278-1305
allfieldsGer	10.3934/energy.2023058 doi (DE-627)DOAJ099126141 (DE-599)DOAJb646447642b04ee8b9f202616c5c6154 DE-627 ger DE-627 rakwb eng TK1001-1841 TJ807-830 Tung-Sheng Zhan verfasserin aut Adaptive OCR coordination in distribution system with distributed energy resources contribution 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier More and more distributed energy resources (DERs) are being added to the medium-voltage (MV) or low-voltage (LV) radial distribution networks (RDNs). These distributed power sources will cause the redistribution of power flow and fault current, bringing new challenges to the coordination of power system protection. An adaptive protection coordination strategy is proposed in this paper. It will trace the connectivity of the system structure to determine the set of relay numbers as a tracking path. According to the topology of the system structure, the tracking path can be divided into two categories: the main feeder path and the branch path. The time multiplier setting (TMS) of each relay can be used to evaluate the operation time of the over-current relay (OCR), and the operation time of the relay can be used to evaluate the fitness of the TMS setting combination. Furthermore, the relay protection coordination problem can be modeled to minimize the accumulated summation of all primary and backup relay operation time (OT) subject to the coordination time interval (CTI) limitation. A modified particle swarm optimization (MPSO) algorithm with adaptive self-cognition and society operation scheme (ASSOS) was proposed and utilized to determine TMS for each relay on the tracking path. A 16-bus test MV system with distributed generators (DGs) will be applied to test the adaptive protection coordination approach proposed in this paper. The results show that the proposed MPSO algorithm reduces the overall OT and relieves the impact on protection coordination settings after DG joins the system. The paper also tests and compares the proposed MPSO with other metaheuristic intelligence-based random search algorithms to prove that MPSO possesses with increased efficiency and performance. relay protection coordination time multiplier setting (tms) coordination time interval (cti) modified particle swarm optimization (mpso) Production of electric energy or power. Powerplants. Central stations Renewable energy sources Chun-Lien Su verfasserin aut Yih-Der Lee verfasserin aut Jheng-Lun Jiang verfasserin aut Jin-Ting Yu verfasserin aut In AIMS Energy AIMS Press, 2014 11(2023), 6, Seite 1278-1305 (DE-627)790616165 (DE-600)2777109-X 23338334 nnns volume:11 year:2023 number:6 pages:1278-1305 https://doi.org/10.3934/energy.2023058 kostenfrei https://doaj.org/article/b646447642b04ee8b9f202616c5c6154 kostenfrei https://www.aimspress.com/article/doi/10.3934/energy.2023058?viewType=HTML kostenfrei https://doaj.org/toc/2333-8334 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 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 2023 6 1278-1305
allfieldsSound	10.3934/energy.2023058 doi (DE-627)DOAJ099126141 (DE-599)DOAJb646447642b04ee8b9f202616c5c6154 DE-627 ger DE-627 rakwb eng TK1001-1841 TJ807-830 Tung-Sheng Zhan verfasserin aut Adaptive OCR coordination in distribution system with distributed energy resources contribution 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier More and more distributed energy resources (DERs) are being added to the medium-voltage (MV) or low-voltage (LV) radial distribution networks (RDNs). These distributed power sources will cause the redistribution of power flow and fault current, bringing new challenges to the coordination of power system protection. An adaptive protection coordination strategy is proposed in this paper. It will trace the connectivity of the system structure to determine the set of relay numbers as a tracking path. According to the topology of the system structure, the tracking path can be divided into two categories: the main feeder path and the branch path. The time multiplier setting (TMS) of each relay can be used to evaluate the operation time of the over-current relay (OCR), and the operation time of the relay can be used to evaluate the fitness of the TMS setting combination. Furthermore, the relay protection coordination problem can be modeled to minimize the accumulated summation of all primary and backup relay operation time (OT) subject to the coordination time interval (CTI) limitation. A modified particle swarm optimization (MPSO) algorithm with adaptive self-cognition and society operation scheme (ASSOS) was proposed and utilized to determine TMS for each relay on the tracking path. A 16-bus test MV system with distributed generators (DGs) will be applied to test the adaptive protection coordination approach proposed in this paper. The results show that the proposed MPSO algorithm reduces the overall OT and relieves the impact on protection coordination settings after DG joins the system. The paper also tests and compares the proposed MPSO with other metaheuristic intelligence-based random search algorithms to prove that MPSO possesses with increased efficiency and performance. relay protection coordination time multiplier setting (tms) coordination time interval (cti) modified particle swarm optimization (mpso) Production of electric energy or power. Powerplants. Central stations Renewable energy sources Chun-Lien Su verfasserin aut Yih-Der Lee verfasserin aut Jheng-Lun Jiang verfasserin aut Jin-Ting Yu verfasserin aut In AIMS Energy AIMS Press, 2014 11(2023), 6, Seite 1278-1305 (DE-627)790616165 (DE-600)2777109-X 23338334 nnns volume:11 year:2023 number:6 pages:1278-1305 https://doi.org/10.3934/energy.2023058 kostenfrei https://doaj.org/article/b646447642b04ee8b9f202616c5c6154 kostenfrei https://www.aimspress.com/article/doi/10.3934/energy.2023058?viewType=HTML kostenfrei https://doaj.org/toc/2333-8334 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 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 2023 6 1278-1305
language	English
source	In AIMS Energy 11(2023), 6, Seite 1278-1305 volume:11 year:2023 number:6 pages:1278-1305
sourceStr	In AIMS Energy 11(2023), 6, Seite 1278-1305 volume:11 year:2023 number:6 pages:1278-1305
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	relay protection coordination time multiplier setting (tms) coordination time interval (cti) modified particle swarm optimization (mpso) Production of electric energy or power. Powerplants. Central stations Renewable energy sources
isfreeaccess_bool	true
container_title	AIMS Energy
authorswithroles_txt_mv	Tung-Sheng Zhan @@aut@@ Chun-Lien Su @@aut@@ Yih-Der Lee @@aut@@ Jheng-Lun Jiang @@aut@@ Jin-Ting Yu @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	790616165
id	DOAJ099126141
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">DOAJ099126141</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240414013927.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240414s2023 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3934/energy.2023058</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ099126141</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJb646447642b04ee8b9f202616c5c6154</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">TK1001-1841</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">TJ807-830</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Tung-Sheng Zhan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Adaptive OCR coordination in distribution system with distributed energy resources contribution</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">More and more distributed energy resources (DERs) are being added to the medium-voltage (MV) or low-voltage (LV) radial distribution networks (RDNs). These distributed power sources will cause the redistribution of power flow and fault current, bringing new challenges to the coordination of power system protection. An adaptive protection coordination strategy is proposed in this paper. It will trace the connectivity of the system structure to determine the set of relay numbers as a tracking path. According to the topology of the system structure, the tracking path can be divided into two categories: the main feeder path and the branch path. The time multiplier setting (TMS) of each relay can be used to evaluate the operation time of the over-current relay (OCR), and the operation time of the relay can be used to evaluate the fitness of the TMS setting combination. Furthermore, the relay protection coordination problem can be modeled to minimize the accumulated summation of all primary and backup relay operation time (OT) subject to the coordination time interval (CTI) limitation. A modified particle swarm optimization (MPSO) algorithm with adaptive self-cognition and society operation scheme (ASSOS) was proposed and utilized to determine TMS for each relay on the tracking path. A 16-bus test MV system with distributed generators (DGs) will be applied to test the adaptive protection coordination approach proposed in this paper. The results show that the proposed MPSO algorithm reduces the overall OT and relieves the impact on protection coordination settings after DG joins the system. The paper also tests and compares the proposed MPSO with other metaheuristic intelligence-based random search algorithms to prove that MPSO possesses with increased efficiency and performance.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">relay protection coordination</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">time multiplier setting (tms)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">coordination time interval (cti)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">modified particle swarm optimization (mpso)</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Production of electric energy or power. Powerplants. Central stations</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Renewable energy sources</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Chun-Lien Su</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yih-Der Lee</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Jheng-Lun Jiang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Jin-Ting Yu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">AIMS Energy</subfield><subfield code="d">AIMS Press, 2014</subfield><subfield code="g">11(2023), 6, Seite 1278-1305</subfield><subfield code="w">(DE-627)790616165</subfield><subfield code="w">(DE-600)2777109-X</subfield><subfield code="x">23338334</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:11</subfield><subfield code="g">year:2023</subfield><subfield code="g">number:6</subfield><subfield code="g">pages:1278-1305</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3934/energy.2023058</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/b646447642b04ee8b9f202616c5c6154</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.aimspress.com/article/doi/10.3934/energy.2023058?viewType=HTML</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2333-8334</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2055</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2111</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">11</subfield><subfield code="j">2023</subfield><subfield code="e">6</subfield><subfield code="h">1278-1305</subfield></datafield></record></collection>
callnumber-first	T - Technology
author	Tung-Sheng Zhan
spellingShingle	Tung-Sheng Zhan misc TK1001-1841 misc TJ807-830 misc relay protection coordination misc time multiplier setting (tms) misc coordination time interval (cti) misc modified particle swarm optimization (mpso) misc Production of electric energy or power. Powerplants. Central stations misc Renewable energy sources Adaptive OCR coordination in distribution system with distributed energy resources contribution
authorStr	Tung-Sheng Zhan
ppnlink_with_tag_str_mv	@@773@@(DE-627)790616165
format	electronic Article
delete_txt_mv	keep
author_role	aut aut aut aut aut
collection	DOAJ
remote_str	true
callnumber-label	TK1001-1841
illustrated	Not Illustrated
issn	23338334
topic_title	TK1001-1841 TJ807-830 Adaptive OCR coordination in distribution system with distributed energy resources contribution relay protection coordination time multiplier setting (tms) coordination time interval (cti) modified particle swarm optimization (mpso)
topic	misc TK1001-1841 misc TJ807-830 misc relay protection coordination misc time multiplier setting (tms) misc coordination time interval (cti) misc modified particle swarm optimization (mpso) misc Production of electric energy or power. Powerplants. Central stations misc Renewable energy sources
topic_unstemmed	misc TK1001-1841 misc TJ807-830 misc relay protection coordination misc time multiplier setting (tms) misc coordination time interval (cti) misc modified particle swarm optimization (mpso) misc Production of electric energy or power. Powerplants. Central stations misc Renewable energy sources
topic_browse	misc TK1001-1841 misc TJ807-830 misc relay protection coordination misc time multiplier setting (tms) misc coordination time interval (cti) misc modified particle swarm optimization (mpso) misc Production of electric energy or power. Powerplants. Central stations misc Renewable energy sources
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
format_main_str_mv	Text Zeitschrift/Artikel
carriertype_str_mv	cr
hierarchy_parent_title	AIMS Energy
hierarchy_parent_id	790616165
hierarchy_top_title	AIMS Energy
isfreeaccess_txt	true
familylinks_str_mv	(DE-627)790616165 (DE-600)2777109-X
title	Adaptive OCR coordination in distribution system with distributed energy resources contribution
ctrlnum	(DE-627)DOAJ099126141 (DE-599)DOAJb646447642b04ee8b9f202616c5c6154
title_full	Adaptive OCR coordination in distribution system with distributed energy resources contribution
author_sort	Tung-Sheng Zhan
journal	AIMS Energy
journalStr	AIMS Energy
callnumber-first-code	T
lang_code	eng
isOA_bool	true
recordtype	marc
publishDateSort	2023
contenttype_str_mv	txt
container_start_page	1278
author_browse	Tung-Sheng Zhan Chun-Lien Su Yih-Der Lee Jheng-Lun Jiang Jin-Ting Yu
container_volume	11
class	TK1001-1841 TJ807-830
format_se	Elektronische Aufsätze
author-letter	Tung-Sheng Zhan
doi_str_mv	10.3934/energy.2023058
author2-role	verfasserin
title_sort	adaptive ocr coordination in distribution system with distributed energy resources contribution
callnumber	TK1001-1841
title_auth	Adaptive OCR coordination in distribution system with distributed energy resources contribution
abstract	More and more distributed energy resources (DERs) are being added to the medium-voltage (MV) or low-voltage (LV) radial distribution networks (RDNs). These distributed power sources will cause the redistribution of power flow and fault current, bringing new challenges to the coordination of power system protection. An adaptive protection coordination strategy is proposed in this paper. It will trace the connectivity of the system structure to determine the set of relay numbers as a tracking path. According to the topology of the system structure, the tracking path can be divided into two categories: the main feeder path and the branch path. The time multiplier setting (TMS) of each relay can be used to evaluate the operation time of the over-current relay (OCR), and the operation time of the relay can be used to evaluate the fitness of the TMS setting combination. Furthermore, the relay protection coordination problem can be modeled to minimize the accumulated summation of all primary and backup relay operation time (OT) subject to the coordination time interval (CTI) limitation. A modified particle swarm optimization (MPSO) algorithm with adaptive self-cognition and society operation scheme (ASSOS) was proposed and utilized to determine TMS for each relay on the tracking path. A 16-bus test MV system with distributed generators (DGs) will be applied to test the adaptive protection coordination approach proposed in this paper. The results show that the proposed MPSO algorithm reduces the overall OT and relieves the impact on protection coordination settings after DG joins the system. The paper also tests and compares the proposed MPSO with other metaheuristic intelligence-based random search algorithms to prove that MPSO possesses with increased efficiency and performance.
abstractGer	More and more distributed energy resources (DERs) are being added to the medium-voltage (MV) or low-voltage (LV) radial distribution networks (RDNs). These distributed power sources will cause the redistribution of power flow and fault current, bringing new challenges to the coordination of power system protection. An adaptive protection coordination strategy is proposed in this paper. It will trace the connectivity of the system structure to determine the set of relay numbers as a tracking path. According to the topology of the system structure, the tracking path can be divided into two categories: the main feeder path and the branch path. The time multiplier setting (TMS) of each relay can be used to evaluate the operation time of the over-current relay (OCR), and the operation time of the relay can be used to evaluate the fitness of the TMS setting combination. Furthermore, the relay protection coordination problem can be modeled to minimize the accumulated summation of all primary and backup relay operation time (OT) subject to the coordination time interval (CTI) limitation. A modified particle swarm optimization (MPSO) algorithm with adaptive self-cognition and society operation scheme (ASSOS) was proposed and utilized to determine TMS for each relay on the tracking path. A 16-bus test MV system with distributed generators (DGs) will be applied to test the adaptive protection coordination approach proposed in this paper. The results show that the proposed MPSO algorithm reduces the overall OT and relieves the impact on protection coordination settings after DG joins the system. The paper also tests and compares the proposed MPSO with other metaheuristic intelligence-based random search algorithms to prove that MPSO possesses with increased efficiency and performance.
abstract_unstemmed	More and more distributed energy resources (DERs) are being added to the medium-voltage (MV) or low-voltage (LV) radial distribution networks (RDNs). These distributed power sources will cause the redistribution of power flow and fault current, bringing new challenges to the coordination of power system protection. An adaptive protection coordination strategy is proposed in this paper. It will trace the connectivity of the system structure to determine the set of relay numbers as a tracking path. According to the topology of the system structure, the tracking path can be divided into two categories: the main feeder path and the branch path. The time multiplier setting (TMS) of each relay can be used to evaluate the operation time of the over-current relay (OCR), and the operation time of the relay can be used to evaluate the fitness of the TMS setting combination. Furthermore, the relay protection coordination problem can be modeled to minimize the accumulated summation of all primary and backup relay operation time (OT) subject to the coordination time interval (CTI) limitation. A modified particle swarm optimization (MPSO) algorithm with adaptive self-cognition and society operation scheme (ASSOS) was proposed and utilized to determine TMS for each relay on the tracking path. A 16-bus test MV system with distributed generators (DGs) will be applied to test the adaptive protection coordination approach proposed in this paper. The results show that the proposed MPSO algorithm reduces the overall OT and relieves the impact on protection coordination settings after DG joins the system. The paper also tests and compares the proposed MPSO with other metaheuristic intelligence-based random search algorithms to prove that MPSO possesses with increased efficiency and performance.
collection_details	GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 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
container_issue	6
title_short	Adaptive OCR coordination in distribution system with distributed energy resources contribution
url	https://doi.org/10.3934/energy.2023058 https://doaj.org/article/b646447642b04ee8b9f202616c5c6154 https://www.aimspress.com/article/doi/10.3934/energy.2023058?viewType=HTML https://doaj.org/toc/2333-8334
remote_bool	true
author2	Chun-Lien Su Yih-Der Lee Jheng-Lun Jiang Jin-Ting Yu
author2Str	Chun-Lien Su Yih-Der Lee Jheng-Lun Jiang Jin-Ting Yu
ppnlink	790616165
callnumber-subject	TK - Electrical and Nuclear Engineering
mediatype_str_mv	c
isOA_txt	true
hochschulschrift_bool	false
doi_str	10.3934/energy.2023058
callnumber-a	TK1001-1841
up_date	2024-07-03T21:08:19.302Z
_version_	1803593606029639680
fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">DOAJ099126141</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240414013927.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240414s2023 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3934/energy.2023058</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ099126141</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJb646447642b04ee8b9f202616c5c6154</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">TK1001-1841</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">TJ807-830</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Tung-Sheng Zhan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Adaptive OCR coordination in distribution system with distributed energy resources contribution</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">More and more distributed energy resources (DERs) are being added to the medium-voltage (MV) or low-voltage (LV) radial distribution networks (RDNs). These distributed power sources will cause the redistribution of power flow and fault current, bringing new challenges to the coordination of power system protection. An adaptive protection coordination strategy is proposed in this paper. It will trace the connectivity of the system structure to determine the set of relay numbers as a tracking path. According to the topology of the system structure, the tracking path can be divided into two categories: the main feeder path and the branch path. The time multiplier setting (TMS) of each relay can be used to evaluate the operation time of the over-current relay (OCR), and the operation time of the relay can be used to evaluate the fitness of the TMS setting combination. Furthermore, the relay protection coordination problem can be modeled to minimize the accumulated summation of all primary and backup relay operation time (OT) subject to the coordination time interval (CTI) limitation. A modified particle swarm optimization (MPSO) algorithm with adaptive self-cognition and society operation scheme (ASSOS) was proposed and utilized to determine TMS for each relay on the tracking path. A 16-bus test MV system with distributed generators (DGs) will be applied to test the adaptive protection coordination approach proposed in this paper. The results show that the proposed MPSO algorithm reduces the overall OT and relieves the impact on protection coordination settings after DG joins the system. The paper also tests and compares the proposed MPSO with other metaheuristic intelligence-based random search algorithms to prove that MPSO possesses with increased efficiency and performance.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">relay protection coordination</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">time multiplier setting (tms)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">coordination time interval (cti)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">modified particle swarm optimization (mpso)</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Production of electric energy or power. Powerplants. Central stations</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Renewable energy sources</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Chun-Lien Su</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yih-Der Lee</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Jheng-Lun Jiang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Jin-Ting Yu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">AIMS Energy</subfield><subfield code="d">AIMS Press, 2014</subfield><subfield code="g">11(2023), 6, Seite 1278-1305</subfield><subfield code="w">(DE-627)790616165</subfield><subfield code="w">(DE-600)2777109-X</subfield><subfield code="x">23338334</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:11</subfield><subfield code="g">year:2023</subfield><subfield code="g">number:6</subfield><subfield code="g">pages:1278-1305</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3934/energy.2023058</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/b646447642b04ee8b9f202616c5c6154</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.aimspress.com/article/doi/10.3934/energy.2023058?viewType=HTML</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2333-8334</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2055</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2111</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">11</subfield><subfield code="j">2023</subfield><subfield code="e">6</subfield><subfield code="h">1278-1305</subfield></datafield></record></collection>
score	7.40096

Nicht das Richtige dabei?

Schreiben Sie uns!

Adaptive OCR coordination in distribution system with distributed energy resources contribution

Nicht das Richtige dabei?

Zugang & Verfügbarkeit

Vorhandene Bände

Nicht das Richtige dabei?