Optimal day-ahead operation of user-level integrated energy system considering dynamic behaviour of heat loads and customers' heat satisfaction

This study proposes a novel optimal day-ahead operation method for the user-level integrated energy system (IES), which can take into account the dynamic behaviour of heat loads and customers' heat satisfaction. First, based on the energy hub, the dynamic model of heat loads is added into IES....
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Autor*in:	Jiawei Lv [verfasserIn] Shenxi Zhang [verfasserIn] Haozhong Cheng [verfasserIn] Sidun Fang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	power generation scheduling quadratic programming power distribution economics power generation economics nonlinear programming optimisation power markets user-level integrated energy system dynamic behaviour heat loads customers novel optimal day-ahead operation method energy hub dynamic model optimal day-ahead operation model total cost energy purchase energy converters standard modelling method

Übergeordnetes Werk:	In: IET Smart Grid - Wiley, 2019, (2019)
Übergeordnetes Werk:	year:2019

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1049/iet-stg.2019.0065

Katalog-ID:	DOAJ014520915

Internformat


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245	1	0	\|a Optimal day-ahead operation of user-level integrated energy system considering dynamic behaviour of heat loads and customers' heat satisfaction
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520			\|a This study proposes a novel optimal day-ahead operation method for the user-level integrated energy system (IES), which can take into account the dynamic behaviour of heat loads and customers' heat satisfaction. First, based on the energy hub, the dynamic model of heat loads is added into IES. Additionally, the customers' heat satisfaction model is constructed by the variance of water temperature and punishment coefficient. Then, the optimal day-ahead operation model aimed at minimising the total cost is proposed. Constraints of energy purchase, operation of energy converters, loads, temperature and the variation of temperature are all contained. Piecewise linearisation and a standard modelling method are utilised to simplify the initial non-convex and non-linear problem to a quadratic programming problem. Finally, case studies are carried out on a practical calculation example. Results indicate that the total cost can be reduced by 5.6% when considering the dynamic behaviour of heat loads. Also, customers' heat satisfaction exerts a remarkable influence on the total cost.
650		4	\|a power generation scheduling
650		4	\|a quadratic programming
650		4	\|a power distribution economics
650		4	\|a power generation economics
650		4	\|a nonlinear programming
650		4	\|a optimisation
650		4	\|a power markets
650		4	\|a user-level integrated energy system
650		4	\|a dynamic behaviour
650		4	\|a heat loads
650		4	\|a customers
650		4	\|a novel optimal day-ahead operation method
650		4	\|a energy hub
650		4	\|a dynamic model
650		4	\|a optimal day-ahead operation model
650		4	\|a total cost
650		4	\|a energy purchase
650		4	\|a energy converters
650		4	\|a standard modelling method
653		0	\|a Electrical engineering. Electronics. Nuclear engineering
700	0		\|a Shenxi Zhang \|e verfasserin \|4 aut
700	0		\|a Haozhong Cheng \|e verfasserin \|4 aut
700	0		\|a Sidun Fang \|e verfasserin \|4 aut
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publishDate	2019
allfields	10.1049/iet-stg.2019.0065 doi (DE-627)DOAJ014520915 (DE-599)DOAJ21cd77ab796d4e13a529ce2d9a675c90 DE-627 ger DE-627 rakwb eng TK1-9971 Jiawei Lv verfasserin aut Optimal day-ahead operation of user-level integrated energy system considering dynamic behaviour of heat loads and customers' heat satisfaction 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This study proposes a novel optimal day-ahead operation method for the user-level integrated energy system (IES), which can take into account the dynamic behaviour of heat loads and customers' heat satisfaction. First, based on the energy hub, the dynamic model of heat loads is added into IES. Additionally, the customers' heat satisfaction model is constructed by the variance of water temperature and punishment coefficient. Then, the optimal day-ahead operation model aimed at minimising the total cost is proposed. Constraints of energy purchase, operation of energy converters, loads, temperature and the variation of temperature are all contained. Piecewise linearisation and a standard modelling method are utilised to simplify the initial non-convex and non-linear problem to a quadratic programming problem. Finally, case studies are carried out on a practical calculation example. Results indicate that the total cost can be reduced by 5.6% when considering the dynamic behaviour of heat loads. Also, customers' heat satisfaction exerts a remarkable influence on the total cost. power generation scheduling quadratic programming power distribution economics power generation economics nonlinear programming optimisation power markets user-level integrated energy system dynamic behaviour heat loads customers novel optimal day-ahead operation method energy hub dynamic model optimal day-ahead operation model total cost energy purchase energy converters standard modelling method Electrical engineering. Electronics. Nuclear engineering Shenxi Zhang verfasserin aut Haozhong Cheng verfasserin aut Sidun Fang verfasserin aut In IET Smart Grid Wiley, 2019 (2019) (DE-627)1023132958 (DE-600)2930480-5 25152947 nnns year:2019 https://doi.org/10.1049/iet-stg.2019.0065 kostenfrei https://doaj.org/article/21cd77ab796d4e13a529ce2d9a675c90 kostenfrei https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0065 kostenfrei https://doaj.org/toc/2515-2947 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_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2019
spelling	10.1049/iet-stg.2019.0065 doi (DE-627)DOAJ014520915 (DE-599)DOAJ21cd77ab796d4e13a529ce2d9a675c90 DE-627 ger DE-627 rakwb eng TK1-9971 Jiawei Lv verfasserin aut Optimal day-ahead operation of user-level integrated energy system considering dynamic behaviour of heat loads and customers' heat satisfaction 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This study proposes a novel optimal day-ahead operation method for the user-level integrated energy system (IES), which can take into account the dynamic behaviour of heat loads and customers' heat satisfaction. First, based on the energy hub, the dynamic model of heat loads is added into IES. Additionally, the customers' heat satisfaction model is constructed by the variance of water temperature and punishment coefficient. Then, the optimal day-ahead operation model aimed at minimising the total cost is proposed. Constraints of energy purchase, operation of energy converters, loads, temperature and the variation of temperature are all contained. Piecewise linearisation and a standard modelling method are utilised to simplify the initial non-convex and non-linear problem to a quadratic programming problem. Finally, case studies are carried out on a practical calculation example. Results indicate that the total cost can be reduced by 5.6% when considering the dynamic behaviour of heat loads. Also, customers' heat satisfaction exerts a remarkable influence on the total cost. power generation scheduling quadratic programming power distribution economics power generation economics nonlinear programming optimisation power markets user-level integrated energy system dynamic behaviour heat loads customers novel optimal day-ahead operation method energy hub dynamic model optimal day-ahead operation model total cost energy purchase energy converters standard modelling method Electrical engineering. Electronics. Nuclear engineering Shenxi Zhang verfasserin aut Haozhong Cheng verfasserin aut Sidun Fang verfasserin aut In IET Smart Grid Wiley, 2019 (2019) (DE-627)1023132958 (DE-600)2930480-5 25152947 nnns year:2019 https://doi.org/10.1049/iet-stg.2019.0065 kostenfrei https://doaj.org/article/21cd77ab796d4e13a529ce2d9a675c90 kostenfrei https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0065 kostenfrei https://doaj.org/toc/2515-2947 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_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2019
allfields_unstemmed	10.1049/iet-stg.2019.0065 doi (DE-627)DOAJ014520915 (DE-599)DOAJ21cd77ab796d4e13a529ce2d9a675c90 DE-627 ger DE-627 rakwb eng TK1-9971 Jiawei Lv verfasserin aut Optimal day-ahead operation of user-level integrated energy system considering dynamic behaviour of heat loads and customers' heat satisfaction 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This study proposes a novel optimal day-ahead operation method for the user-level integrated energy system (IES), which can take into account the dynamic behaviour of heat loads and customers' heat satisfaction. First, based on the energy hub, the dynamic model of heat loads is added into IES. Additionally, the customers' heat satisfaction model is constructed by the variance of water temperature and punishment coefficient. Then, the optimal day-ahead operation model aimed at minimising the total cost is proposed. Constraints of energy purchase, operation of energy converters, loads, temperature and the variation of temperature are all contained. Piecewise linearisation and a standard modelling method are utilised to simplify the initial non-convex and non-linear problem to a quadratic programming problem. Finally, case studies are carried out on a practical calculation example. Results indicate that the total cost can be reduced by 5.6% when considering the dynamic behaviour of heat loads. Also, customers' heat satisfaction exerts a remarkable influence on the total cost. power generation scheduling quadratic programming power distribution economics power generation economics nonlinear programming optimisation power markets user-level integrated energy system dynamic behaviour heat loads customers novel optimal day-ahead operation method energy hub dynamic model optimal day-ahead operation model total cost energy purchase energy converters standard modelling method Electrical engineering. Electronics. Nuclear engineering Shenxi Zhang verfasserin aut Haozhong Cheng verfasserin aut Sidun Fang verfasserin aut In IET Smart Grid Wiley, 2019 (2019) (DE-627)1023132958 (DE-600)2930480-5 25152947 nnns year:2019 https://doi.org/10.1049/iet-stg.2019.0065 kostenfrei https://doaj.org/article/21cd77ab796d4e13a529ce2d9a675c90 kostenfrei https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0065 kostenfrei https://doaj.org/toc/2515-2947 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_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2019
allfieldsGer	10.1049/iet-stg.2019.0065 doi (DE-627)DOAJ014520915 (DE-599)DOAJ21cd77ab796d4e13a529ce2d9a675c90 DE-627 ger DE-627 rakwb eng TK1-9971 Jiawei Lv verfasserin aut Optimal day-ahead operation of user-level integrated energy system considering dynamic behaviour of heat loads and customers' heat satisfaction 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This study proposes a novel optimal day-ahead operation method for the user-level integrated energy system (IES), which can take into account the dynamic behaviour of heat loads and customers' heat satisfaction. First, based on the energy hub, the dynamic model of heat loads is added into IES. Additionally, the customers' heat satisfaction model is constructed by the variance of water temperature and punishment coefficient. Then, the optimal day-ahead operation model aimed at minimising the total cost is proposed. Constraints of energy purchase, operation of energy converters, loads, temperature and the variation of temperature are all contained. Piecewise linearisation and a standard modelling method are utilised to simplify the initial non-convex and non-linear problem to a quadratic programming problem. Finally, case studies are carried out on a practical calculation example. Results indicate that the total cost can be reduced by 5.6% when considering the dynamic behaviour of heat loads. Also, customers' heat satisfaction exerts a remarkable influence on the total cost. power generation scheduling quadratic programming power distribution economics power generation economics nonlinear programming optimisation power markets user-level integrated energy system dynamic behaviour heat loads customers novel optimal day-ahead operation method energy hub dynamic model optimal day-ahead operation model total cost energy purchase energy converters standard modelling method Electrical engineering. Electronics. Nuclear engineering Shenxi Zhang verfasserin aut Haozhong Cheng verfasserin aut Sidun Fang verfasserin aut In IET Smart Grid Wiley, 2019 (2019) (DE-627)1023132958 (DE-600)2930480-5 25152947 nnns year:2019 https://doi.org/10.1049/iet-stg.2019.0065 kostenfrei https://doaj.org/article/21cd77ab796d4e13a529ce2d9a675c90 kostenfrei https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0065 kostenfrei https://doaj.org/toc/2515-2947 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_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2019
allfieldsSound	10.1049/iet-stg.2019.0065 doi (DE-627)DOAJ014520915 (DE-599)DOAJ21cd77ab796d4e13a529ce2d9a675c90 DE-627 ger DE-627 rakwb eng TK1-9971 Jiawei Lv verfasserin aut Optimal day-ahead operation of user-level integrated energy system considering dynamic behaviour of heat loads and customers' heat satisfaction 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This study proposes a novel optimal day-ahead operation method for the user-level integrated energy system (IES), which can take into account the dynamic behaviour of heat loads and customers' heat satisfaction. First, based on the energy hub, the dynamic model of heat loads is added into IES. Additionally, the customers' heat satisfaction model is constructed by the variance of water temperature and punishment coefficient. Then, the optimal day-ahead operation model aimed at minimising the total cost is proposed. Constraints of energy purchase, operation of energy converters, loads, temperature and the variation of temperature are all contained. Piecewise linearisation and a standard modelling method are utilised to simplify the initial non-convex and non-linear problem to a quadratic programming problem. Finally, case studies are carried out on a practical calculation example. Results indicate that the total cost can be reduced by 5.6% when considering the dynamic behaviour of heat loads. Also, customers' heat satisfaction exerts a remarkable influence on the total cost. power generation scheduling quadratic programming power distribution economics power generation economics nonlinear programming optimisation power markets user-level integrated energy system dynamic behaviour heat loads customers novel optimal day-ahead operation method energy hub dynamic model optimal day-ahead operation model total cost energy purchase energy converters standard modelling method Electrical engineering. Electronics. Nuclear engineering Shenxi Zhang verfasserin aut Haozhong Cheng verfasserin aut Sidun Fang verfasserin aut In IET Smart Grid Wiley, 2019 (2019) (DE-627)1023132958 (DE-600)2930480-5 25152947 nnns year:2019 https://doi.org/10.1049/iet-stg.2019.0065 kostenfrei https://doaj.org/article/21cd77ab796d4e13a529ce2d9a675c90 kostenfrei https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0065 kostenfrei https://doaj.org/toc/2515-2947 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_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2019
language	English
source	In IET Smart Grid (2019) year:2019
sourceStr	In IET Smart Grid (2019) year:2019
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	power generation scheduling quadratic programming power distribution economics power generation economics nonlinear programming optimisation power markets user-level integrated energy system dynamic behaviour heat loads customers novel optimal day-ahead operation method energy hub dynamic model optimal day-ahead operation model total cost energy purchase energy converters standard modelling method Electrical engineering. Electronics. Nuclear engineering
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container_title	IET Smart Grid
authorswithroles_txt_mv	Jiawei Lv @@aut@@ Shenxi Zhang @@aut@@ Haozhong Cheng @@aut@@ Sidun Fang @@aut@@
publishDateDaySort_date	2019-01-01T00:00:00Z
hierarchy_top_id	1023132958
id	DOAJ014520915
language_de	englisch
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callnumber-first	T - Technology
author	Jiawei Lv
spellingShingle	Jiawei Lv misc TK1-9971 misc power generation scheduling misc quadratic programming misc power distribution economics misc power generation economics misc nonlinear programming misc optimisation misc power markets misc user-level integrated energy system misc dynamic behaviour misc heat loads misc customers misc novel optimal day-ahead operation method misc energy hub misc dynamic model misc optimal day-ahead operation model misc total cost misc energy purchase misc energy converters misc standard modelling method misc Electrical engineering. Electronics. Nuclear engineering Optimal day-ahead operation of user-level integrated energy system considering dynamic behaviour of heat loads and customers' heat satisfaction
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topic_title	TK1-9971 Optimal day-ahead operation of user-level integrated energy system considering dynamic behaviour of heat loads and customers' heat satisfaction power generation scheduling quadratic programming power distribution economics power generation economics nonlinear programming optimisation power markets user-level integrated energy system dynamic behaviour heat loads customers novel optimal day-ahead operation method energy hub dynamic model optimal day-ahead operation model total cost energy purchase energy converters standard modelling method
topic	misc TK1-9971 misc power generation scheduling misc quadratic programming misc power distribution economics misc power generation economics misc nonlinear programming misc optimisation misc power markets misc user-level integrated energy system misc dynamic behaviour misc heat loads misc customers misc novel optimal day-ahead operation method misc energy hub misc dynamic model misc optimal day-ahead operation model misc total cost misc energy purchase misc energy converters misc standard modelling method misc Electrical engineering. Electronics. Nuclear engineering
topic_unstemmed	misc TK1-9971 misc power generation scheduling misc quadratic programming misc power distribution economics misc power generation economics misc nonlinear programming misc optimisation misc power markets misc user-level integrated energy system misc dynamic behaviour misc heat loads misc customers misc novel optimal day-ahead operation method misc energy hub misc dynamic model misc optimal day-ahead operation model misc total cost misc energy purchase misc energy converters misc standard modelling method misc Electrical engineering. Electronics. Nuclear engineering
topic_browse	misc TK1-9971 misc power generation scheduling misc quadratic programming misc power distribution economics misc power generation economics misc nonlinear programming misc optimisation misc power markets misc user-level integrated energy system misc dynamic behaviour misc heat loads misc customers misc novel optimal day-ahead operation method misc energy hub misc dynamic model misc optimal day-ahead operation model misc total cost misc energy purchase misc energy converters misc standard modelling method misc Electrical engineering. Electronics. Nuclear engineering
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title	Optimal day-ahead operation of user-level integrated energy system considering dynamic behaviour of heat loads and customers' heat satisfaction
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title_full	Optimal day-ahead operation of user-level integrated energy system considering dynamic behaviour of heat loads and customers' heat satisfaction
author_sort	Jiawei Lv
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author_browse	Jiawei Lv Shenxi Zhang Haozhong Cheng Sidun Fang
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title_sort	optimal day-ahead operation of user-level integrated energy system considering dynamic behaviour of heat loads and customers' heat satisfaction
callnumber	TK1-9971
title_auth	Optimal day-ahead operation of user-level integrated energy system considering dynamic behaviour of heat loads and customers' heat satisfaction
abstract	This study proposes a novel optimal day-ahead operation method for the user-level integrated energy system (IES), which can take into account the dynamic behaviour of heat loads and customers' heat satisfaction. First, based on the energy hub, the dynamic model of heat loads is added into IES. Additionally, the customers' heat satisfaction model is constructed by the variance of water temperature and punishment coefficient. Then, the optimal day-ahead operation model aimed at minimising the total cost is proposed. Constraints of energy purchase, operation of energy converters, loads, temperature and the variation of temperature are all contained. Piecewise linearisation and a standard modelling method are utilised to simplify the initial non-convex and non-linear problem to a quadratic programming problem. Finally, case studies are carried out on a practical calculation example. Results indicate that the total cost can be reduced by 5.6% when considering the dynamic behaviour of heat loads. Also, customers' heat satisfaction exerts a remarkable influence on the total cost.
abstractGer	This study proposes a novel optimal day-ahead operation method for the user-level integrated energy system (IES), which can take into account the dynamic behaviour of heat loads and customers' heat satisfaction. First, based on the energy hub, the dynamic model of heat loads is added into IES. Additionally, the customers' heat satisfaction model is constructed by the variance of water temperature and punishment coefficient. Then, the optimal day-ahead operation model aimed at minimising the total cost is proposed. Constraints of energy purchase, operation of energy converters, loads, temperature and the variation of temperature are all contained. Piecewise linearisation and a standard modelling method are utilised to simplify the initial non-convex and non-linear problem to a quadratic programming problem. Finally, case studies are carried out on a practical calculation example. Results indicate that the total cost can be reduced by 5.6% when considering the dynamic behaviour of heat loads. Also, customers' heat satisfaction exerts a remarkable influence on the total cost.
abstract_unstemmed	This study proposes a novel optimal day-ahead operation method for the user-level integrated energy system (IES), which can take into account the dynamic behaviour of heat loads and customers' heat satisfaction. First, based on the energy hub, the dynamic model of heat loads is added into IES. Additionally, the customers' heat satisfaction model is constructed by the variance of water temperature and punishment coefficient. Then, the optimal day-ahead operation model aimed at minimising the total cost is proposed. Constraints of energy purchase, operation of energy converters, loads, temperature and the variation of temperature are all contained. Piecewise linearisation and a standard modelling method are utilised to simplify the initial non-convex and non-linear problem to a quadratic programming problem. Finally, case studies are carried out on a practical calculation example. Results indicate that the total cost can be reduced by 5.6% when considering the dynamic behaviour of heat loads. Also, customers' heat satisfaction exerts a remarkable influence on the total cost.
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title_short	Optimal day-ahead operation of user-level integrated energy system considering dynamic behaviour of heat loads and customers' heat satisfaction
url	https://doi.org/10.1049/iet-stg.2019.0065 https://doaj.org/article/21cd77ab796d4e13a529ce2d9a675c90 https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0065 https://doaj.org/toc/2515-2947
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up_date	2024-07-03T23:24:58.047Z
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First, based on the energy hub, the dynamic model of heat loads is added into IES. Additionally, the customers' heat satisfaction model is constructed by the variance of water temperature and punishment coefficient. Then, the optimal day-ahead operation model aimed at minimising the total cost is proposed. Constraints of energy purchase, operation of energy converters, loads, temperature and the variation of temperature are all contained. Piecewise linearisation and a standard modelling method are utilised to simplify the initial non-convex and non-linear problem to a quadratic programming problem. Finally, case studies are carried out on a practical calculation example. Results indicate that the total cost can be reduced by 5.6% when considering the dynamic behaviour of heat loads. 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