Optimal dispatching strategy for residential demand response considering load participation

To facilitate the coordinated and large-scale participation of residential flexible loads in demand response (DR), a load aggregator (LA) can integrate these loads for scheduling. In this study, a residential DR optimization scheduling strategy was formulated considering the participation of flexibl...
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Autor*in:	Xiaoyu Zhou [verfasserIn] Xiaofeng Liu [verfasserIn] Huai Liu [verfasserIn] Zhenya Ji [verfasserIn] Feng Li [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Schlagwörter:	Residential demand response Flexible loads Load participation Load aggregator

Übergeordnetes Werk:	In: Global Energy Interconnection - KeAi Communications Co., Ltd., 2019, 7(2024), 1, Seite 38-47
Übergeordnetes Werk:	volume:7 ; year:2024 ; number:1 ; pages:38-47

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1016/j.gloei.2024.01.004

Katalog-ID:	DOAJ099730022

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520			\|a To facilitate the coordinated and large-scale participation of residential flexible loads in demand response (DR), a load aggregator (LA) can integrate these loads for scheduling. In this study, a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in DR. First, based on the operational characteristics of flexible loads such as electric vehicles, air conditioners, and dishwashers, their DR participation, the base to calculate the compensation price to users, was determined by considering these loads as virtual energy storage. It was quantified based on the state of virtual energy storage during each time slot. Second, flexible loads were clustered using the K-means algorithm, considering the typical operational and behavioral characteristics as the cluster centroid. Finally, the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix load. The simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys, thereby improving the load management performance.
650		4	\|a Residential demand response
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653		0	\|a Energy conservation
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spelling	10.1016/j.gloei.2024.01.004 doi (DE-627)DOAJ099730022 (DE-599)DOAJ3aa33660453b46fa9ea8cdb5cc1d25e6 DE-627 ger DE-627 rakwb eng TJ163.26-163.5 HD9502-9502.5 Xiaoyu Zhou verfasserin aut Optimal dispatching strategy for residential demand response considering load participation 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier To facilitate the coordinated and large-scale participation of residential flexible loads in demand response (DR), a load aggregator (LA) can integrate these loads for scheduling. In this study, a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in DR. First, based on the operational characteristics of flexible loads such as electric vehicles, air conditioners, and dishwashers, their DR participation, the base to calculate the compensation price to users, was determined by considering these loads as virtual energy storage. It was quantified based on the state of virtual energy storage during each time slot. Second, flexible loads were clustered using the K-means algorithm, considering the typical operational and behavioral characteristics as the cluster centroid. Finally, the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix load. The simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys, thereby improving the load management performance. Residential demand response Flexible loads Load participation Load aggregator Energy conservation Energy industries. Energy policy. Fuel trade Xiaofeng Liu verfasserin aut Huai Liu verfasserin aut Zhenya Ji verfasserin aut Feng Li verfasserin aut In Global Energy Interconnection KeAi Communications Co., Ltd., 2019 7(2024), 1, Seite 38-47 (DE-627)1663409803 (DE-600)2969898-4 25900358 nnns volume:7 year:2024 number:1 pages:38-47 https://doi.org/10.1016/j.gloei.2024.01.004 kostenfrei https://doaj.org/article/3aa33660453b46fa9ea8cdb5cc1d25e6 kostenfrei http://www.sciencedirect.com/science/article/pii/S2096511724000045 kostenfrei https://doaj.org/toc/2096-5117 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_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_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 7 2024 1 38-47
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allfieldsGer	10.1016/j.gloei.2024.01.004 doi (DE-627)DOAJ099730022 (DE-599)DOAJ3aa33660453b46fa9ea8cdb5cc1d25e6 DE-627 ger DE-627 rakwb eng TJ163.26-163.5 HD9502-9502.5 Xiaoyu Zhou verfasserin aut Optimal dispatching strategy for residential demand response considering load participation 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier To facilitate the coordinated and large-scale participation of residential flexible loads in demand response (DR), a load aggregator (LA) can integrate these loads for scheduling. In this study, a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in DR. First, based on the operational characteristics of flexible loads such as electric vehicles, air conditioners, and dishwashers, their DR participation, the base to calculate the compensation price to users, was determined by considering these loads as virtual energy storage. It was quantified based on the state of virtual energy storage during each time slot. Second, flexible loads were clustered using the K-means algorithm, considering the typical operational and behavioral characteristics as the cluster centroid. Finally, the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix load. The simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys, thereby improving the load management performance. Residential demand response Flexible loads Load participation Load aggregator Energy conservation Energy industries. Energy policy. Fuel trade Xiaofeng Liu verfasserin aut Huai Liu verfasserin aut Zhenya Ji verfasserin aut Feng Li verfasserin aut In Global Energy Interconnection KeAi Communications Co., Ltd., 2019 7(2024), 1, Seite 38-47 (DE-627)1663409803 (DE-600)2969898-4 25900358 nnns volume:7 year:2024 number:1 pages:38-47 https://doi.org/10.1016/j.gloei.2024.01.004 kostenfrei https://doaj.org/article/3aa33660453b46fa9ea8cdb5cc1d25e6 kostenfrei http://www.sciencedirect.com/science/article/pii/S2096511724000045 kostenfrei https://doaj.org/toc/2096-5117 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_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_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 7 2024 1 38-47
allfieldsSound	10.1016/j.gloei.2024.01.004 doi (DE-627)DOAJ099730022 (DE-599)DOAJ3aa33660453b46fa9ea8cdb5cc1d25e6 DE-627 ger DE-627 rakwb eng TJ163.26-163.5 HD9502-9502.5 Xiaoyu Zhou verfasserin aut Optimal dispatching strategy for residential demand response considering load participation 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier To facilitate the coordinated and large-scale participation of residential flexible loads in demand response (DR), a load aggregator (LA) can integrate these loads for scheduling. In this study, a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in DR. First, based on the operational characteristics of flexible loads such as electric vehicles, air conditioners, and dishwashers, their DR participation, the base to calculate the compensation price to users, was determined by considering these loads as virtual energy storage. It was quantified based on the state of virtual energy storage during each time slot. Second, flexible loads were clustered using the K-means algorithm, considering the typical operational and behavioral characteristics as the cluster centroid. Finally, the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix load. The simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys, thereby improving the load management performance. Residential demand response Flexible loads Load participation Load aggregator Energy conservation Energy industries. Energy policy. Fuel trade Xiaofeng Liu verfasserin aut Huai Liu verfasserin aut Zhenya Ji verfasserin aut Feng Li verfasserin aut In Global Energy Interconnection KeAi Communications Co., Ltd., 2019 7(2024), 1, Seite 38-47 (DE-627)1663409803 (DE-600)2969898-4 25900358 nnns volume:7 year:2024 number:1 pages:38-47 https://doi.org/10.1016/j.gloei.2024.01.004 kostenfrei https://doaj.org/article/3aa33660453b46fa9ea8cdb5cc1d25e6 kostenfrei http://www.sciencedirect.com/science/article/pii/S2096511724000045 kostenfrei https://doaj.org/toc/2096-5117 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_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_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 7 2024 1 38-47
language	English
source	In Global Energy Interconnection 7(2024), 1, Seite 38-47 volume:7 year:2024 number:1 pages:38-47
sourceStr	In Global Energy Interconnection 7(2024), 1, Seite 38-47 volume:7 year:2024 number:1 pages:38-47
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Residential demand response Flexible loads Load participation Load aggregator Energy conservation Energy industries. Energy policy. Fuel trade
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container_title	Global Energy Interconnection
authorswithroles_txt_mv	Xiaoyu Zhou @@aut@@ Xiaofeng Liu @@aut@@ Huai Liu @@aut@@ Zhenya Ji @@aut@@ Feng Li @@aut@@
publishDateDaySort_date	2024-01-01T00:00:00Z
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callnumber-first	T - Technology
author	Xiaoyu Zhou
spellingShingle	Xiaoyu Zhou misc TJ163.26-163.5 misc HD9502-9502.5 misc Residential demand response misc Flexible loads misc Load participation misc Load aggregator misc Energy conservation misc Energy industries. Energy policy. Fuel trade Optimal dispatching strategy for residential demand response considering load participation
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topic_title	TJ163.26-163.5 HD9502-9502.5 Optimal dispatching strategy for residential demand response considering load participation Residential demand response Flexible loads Load participation Load aggregator
topic	misc TJ163.26-163.5 misc HD9502-9502.5 misc Residential demand response misc Flexible loads misc Load participation misc Load aggregator misc Energy conservation misc Energy industries. Energy policy. Fuel trade
topic_unstemmed	misc TJ163.26-163.5 misc HD9502-9502.5 misc Residential demand response misc Flexible loads misc Load participation misc Load aggregator misc Energy conservation misc Energy industries. Energy policy. Fuel trade
topic_browse	misc TJ163.26-163.5 misc HD9502-9502.5 misc Residential demand response misc Flexible loads misc Load participation misc Load aggregator misc Energy conservation misc Energy industries. Energy policy. Fuel trade
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title	Optimal dispatching strategy for residential demand response considering load participation
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title_full	Optimal dispatching strategy for residential demand response considering load participation
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journal	Global Energy Interconnection
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title_sort	optimal dispatching strategy for residential demand response considering load participation
callnumber	TJ163.26-163.5
title_auth	Optimal dispatching strategy for residential demand response considering load participation
abstract	To facilitate the coordinated and large-scale participation of residential flexible loads in demand response (DR), a load aggregator (LA) can integrate these loads for scheduling. In this study, a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in DR. First, based on the operational characteristics of flexible loads such as electric vehicles, air conditioners, and dishwashers, their DR participation, the base to calculate the compensation price to users, was determined by considering these loads as virtual energy storage. It was quantified based on the state of virtual energy storage during each time slot. Second, flexible loads were clustered using the K-means algorithm, considering the typical operational and behavioral characteristics as the cluster centroid. Finally, the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix load. The simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys, thereby improving the load management performance.
abstractGer	To facilitate the coordinated and large-scale participation of residential flexible loads in demand response (DR), a load aggregator (LA) can integrate these loads for scheduling. In this study, a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in DR. First, based on the operational characteristics of flexible loads such as electric vehicles, air conditioners, and dishwashers, their DR participation, the base to calculate the compensation price to users, was determined by considering these loads as virtual energy storage. It was quantified based on the state of virtual energy storage during each time slot. Second, flexible loads were clustered using the K-means algorithm, considering the typical operational and behavioral characteristics as the cluster centroid. Finally, the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix load. The simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys, thereby improving the load management performance.
abstract_unstemmed	To facilitate the coordinated and large-scale participation of residential flexible loads in demand response (DR), a load aggregator (LA) can integrate these loads for scheduling. In this study, a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in DR. First, based on the operational characteristics of flexible loads such as electric vehicles, air conditioners, and dishwashers, their DR participation, the base to calculate the compensation price to users, was determined by considering these loads as virtual energy storage. It was quantified based on the state of virtual energy storage during each time slot. Second, flexible loads were clustered using the K-means algorithm, considering the typical operational and behavioral characteristics as the cluster centroid. Finally, the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix load. The simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys, thereby improving the load management performance.
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title_short	Optimal dispatching strategy for residential demand response considering load participation
url	https://doi.org/10.1016/j.gloei.2024.01.004 https://doaj.org/article/3aa33660453b46fa9ea8cdb5cc1d25e6 http://www.sciencedirect.com/science/article/pii/S2096511724000045 https://doaj.org/toc/2096-5117
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doi_str	10.1016/j.gloei.2024.01.004
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