Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change

With the increasing energy prices and growing concerns over energy security, an accelerated transition to net zero carbon built environment has never been more important. Many studies have shown the capabilities of advanced control strategies such as model predictive control (MPC) to achieve energy...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Wei, Zhichen [verfasserIn] Calautit, John [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Building energy Climate change Future weather conditions Model predictive control (MPC) Occupancy Passive structural thermal energy storage Price response Solar energy Thermal mass TRNSYS

Übergeordnetes Werk:	Enthalten in: Energy - Amsterdam [u.a.] : Elsevier Science, 1976, 269
Übergeordnetes Werk:	volume:269

DOI / URN:	10.1016/j.energy.2023.126791

Katalog-ID:	ELV060839570

Internformat


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245	1	0	\|a Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change
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520			\|a With the increasing energy prices and growing concerns over energy security, an accelerated transition to net zero carbon built environment has never been more important. Many studies have shown the capabilities of advanced control strategies such as model predictive control (MPC) to achieve energy efficiency, balance with thermal comfort and air quality. It has also shown its capability to provide demand flexibility, minimising peak load demands and maximising the production of renewable energy sources in buildings. This work investigates the potential of integrating price-responsive MPC with a low-temperature heating system and passive structural thermal energy storage (STES). Integration with a photovoltaic (PV) system is also explored. The system performance under future climate conditions is evaluated considering different design and operating conditions, including different thermal mass, occupancy patterns and internal heat gains, setpoint strategies and operation temperatures of the low-temperature heating system. The coupled model developed has been verified and validated with numerical and experimental data, and good agreement is observed. The results showed that mediumweight thermal mass and a medium-temperature (45 °C ) under-floor heating inlet temperature provided a higher load shifting ability, based on a realistic occupancy profile for a residential building and a high tolerance setpoint strategy during unoccupied periods. The result also showed that higher low-price energy usage and lower heating energy usage could be achieved in future climate conditions. Finally, an increase in the load shifting ability was observed after the integration of rooftop solar PV system.
650		4	\|a Building energy
650		4	\|a Climate change
650		4	\|a Future weather conditions
650		4	\|a Model predictive control (MPC)
650		4	\|a Occupancy
650		4	\|a Passive structural thermal energy storage
650		4	\|a Price response
650		4	\|a Solar energy
650		4	\|a Thermal mass
650		4	\|a TRNSYS
700	1		\|a Calautit, John \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t Energy \|d Amsterdam [u.a.] : Elsevier Science, 1976 \|g 269 \|h Online-Ressource \|w (DE-627)320597903 \|w (DE-600)2019804-8 \|w (DE-576)116451815 \|x 1873-6785 \|7 nnns
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allfields	10.1016/j.energy.2023.126791 doi (DE-627)ELV060839570 (ELSEVIER)S0360-5442(23)00185-8 DE-627 ger DE-627 rda eng 600 VZ 50.70 bkl Wei, Zhichen verfasserin aut Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the increasing energy prices and growing concerns over energy security, an accelerated transition to net zero carbon built environment has never been more important. Many studies have shown the capabilities of advanced control strategies such as model predictive control (MPC) to achieve energy efficiency, balance with thermal comfort and air quality. It has also shown its capability to provide demand flexibility, minimising peak load demands and maximising the production of renewable energy sources in buildings. This work investigates the potential of integrating price-responsive MPC with a low-temperature heating system and passive structural thermal energy storage (STES). Integration with a photovoltaic (PV) system is also explored. The system performance under future climate conditions is evaluated considering different design and operating conditions, including different thermal mass, occupancy patterns and internal heat gains, setpoint strategies and operation temperatures of the low-temperature heating system. The coupled model developed has been verified and validated with numerical and experimental data, and good agreement is observed. The results showed that mediumweight thermal mass and a medium-temperature (45 °C ) under-floor heating inlet temperature provided a higher load shifting ability, based on a realistic occupancy profile for a residential building and a high tolerance setpoint strategy during unoccupied periods. The result also showed that higher low-price energy usage and lower heating energy usage could be achieved in future climate conditions. Finally, an increase in the load shifting ability was observed after the integration of rooftop solar PV system. Building energy Climate change Future weather conditions Model predictive control (MPC) Occupancy Passive structural thermal energy storage Price response Solar energy Thermal mass TRNSYS Calautit, John verfasserin aut Enthalten in Energy Amsterdam [u.a.] : Elsevier Science, 1976 269 Online-Ressource (DE-627)320597903 (DE-600)2019804-8 (DE-576)116451815 1873-6785 nnns volume:269 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 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_4338 GBV_ILN_4393 GBV_ILN_4700 50.70 Energie: Allgemeines VZ AR 269
spelling	10.1016/j.energy.2023.126791 doi (DE-627)ELV060839570 (ELSEVIER)S0360-5442(23)00185-8 DE-627 ger DE-627 rda eng 600 VZ 50.70 bkl Wei, Zhichen verfasserin aut Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the increasing energy prices and growing concerns over energy security, an accelerated transition to net zero carbon built environment has never been more important. Many studies have shown the capabilities of advanced control strategies such as model predictive control (MPC) to achieve energy efficiency, balance with thermal comfort and air quality. It has also shown its capability to provide demand flexibility, minimising peak load demands and maximising the production of renewable energy sources in buildings. This work investigates the potential of integrating price-responsive MPC with a low-temperature heating system and passive structural thermal energy storage (STES). Integration with a photovoltaic (PV) system is also explored. The system performance under future climate conditions is evaluated considering different design and operating conditions, including different thermal mass, occupancy patterns and internal heat gains, setpoint strategies and operation temperatures of the low-temperature heating system. The coupled model developed has been verified and validated with numerical and experimental data, and good agreement is observed. The results showed that mediumweight thermal mass and a medium-temperature (45 °C ) under-floor heating inlet temperature provided a higher load shifting ability, based on a realistic occupancy profile for a residential building and a high tolerance setpoint strategy during unoccupied periods. The result also showed that higher low-price energy usage and lower heating energy usage could be achieved in future climate conditions. Finally, an increase in the load shifting ability was observed after the integration of rooftop solar PV system. Building energy Climate change Future weather conditions Model predictive control (MPC) Occupancy Passive structural thermal energy storage Price response Solar energy Thermal mass TRNSYS Calautit, John verfasserin aut Enthalten in Energy Amsterdam [u.a.] : Elsevier Science, 1976 269 Online-Ressource (DE-627)320597903 (DE-600)2019804-8 (DE-576)116451815 1873-6785 nnns volume:269 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 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_4338 GBV_ILN_4393 GBV_ILN_4700 50.70 Energie: Allgemeines VZ AR 269
allfields_unstemmed	10.1016/j.energy.2023.126791 doi (DE-627)ELV060839570 (ELSEVIER)S0360-5442(23)00185-8 DE-627 ger DE-627 rda eng 600 VZ 50.70 bkl Wei, Zhichen verfasserin aut Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the increasing energy prices and growing concerns over energy security, an accelerated transition to net zero carbon built environment has never been more important. Many studies have shown the capabilities of advanced control strategies such as model predictive control (MPC) to achieve energy efficiency, balance with thermal comfort and air quality. It has also shown its capability to provide demand flexibility, minimising peak load demands and maximising the production of renewable energy sources in buildings. This work investigates the potential of integrating price-responsive MPC with a low-temperature heating system and passive structural thermal energy storage (STES). Integration with a photovoltaic (PV) system is also explored. The system performance under future climate conditions is evaluated considering different design and operating conditions, including different thermal mass, occupancy patterns and internal heat gains, setpoint strategies and operation temperatures of the low-temperature heating system. The coupled model developed has been verified and validated with numerical and experimental data, and good agreement is observed. The results showed that mediumweight thermal mass and a medium-temperature (45 °C ) under-floor heating inlet temperature provided a higher load shifting ability, based on a realistic occupancy profile for a residential building and a high tolerance setpoint strategy during unoccupied periods. The result also showed that higher low-price energy usage and lower heating energy usage could be achieved in future climate conditions. Finally, an increase in the load shifting ability was observed after the integration of rooftop solar PV system. Building energy Climate change Future weather conditions Model predictive control (MPC) Occupancy Passive structural thermal energy storage Price response Solar energy Thermal mass TRNSYS Calautit, John verfasserin aut Enthalten in Energy Amsterdam [u.a.] : Elsevier Science, 1976 269 Online-Ressource (DE-627)320597903 (DE-600)2019804-8 (DE-576)116451815 1873-6785 nnns volume:269 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 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_4338 GBV_ILN_4393 GBV_ILN_4700 50.70 Energie: Allgemeines VZ AR 269
allfieldsGer	10.1016/j.energy.2023.126791 doi (DE-627)ELV060839570 (ELSEVIER)S0360-5442(23)00185-8 DE-627 ger DE-627 rda eng 600 VZ 50.70 bkl Wei, Zhichen verfasserin aut Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the increasing energy prices and growing concerns over energy security, an accelerated transition to net zero carbon built environment has never been more important. Many studies have shown the capabilities of advanced control strategies such as model predictive control (MPC) to achieve energy efficiency, balance with thermal comfort and air quality. It has also shown its capability to provide demand flexibility, minimising peak load demands and maximising the production of renewable energy sources in buildings. This work investigates the potential of integrating price-responsive MPC with a low-temperature heating system and passive structural thermal energy storage (STES). Integration with a photovoltaic (PV) system is also explored. The system performance under future climate conditions is evaluated considering different design and operating conditions, including different thermal mass, occupancy patterns and internal heat gains, setpoint strategies and operation temperatures of the low-temperature heating system. The coupled model developed has been verified and validated with numerical and experimental data, and good agreement is observed. The results showed that mediumweight thermal mass and a medium-temperature (45 °C ) under-floor heating inlet temperature provided a higher load shifting ability, based on a realistic occupancy profile for a residential building and a high tolerance setpoint strategy during unoccupied periods. The result also showed that higher low-price energy usage and lower heating energy usage could be achieved in future climate conditions. Finally, an increase in the load shifting ability was observed after the integration of rooftop solar PV system. Building energy Climate change Future weather conditions Model predictive control (MPC) Occupancy Passive structural thermal energy storage Price response Solar energy Thermal mass TRNSYS Calautit, John verfasserin aut Enthalten in Energy Amsterdam [u.a.] : Elsevier Science, 1976 269 Online-Ressource (DE-627)320597903 (DE-600)2019804-8 (DE-576)116451815 1873-6785 nnns volume:269 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 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_4338 GBV_ILN_4393 GBV_ILN_4700 50.70 Energie: Allgemeines VZ AR 269
allfieldsSound	10.1016/j.energy.2023.126791 doi (DE-627)ELV060839570 (ELSEVIER)S0360-5442(23)00185-8 DE-627 ger DE-627 rda eng 600 VZ 50.70 bkl Wei, Zhichen verfasserin aut Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the increasing energy prices and growing concerns over energy security, an accelerated transition to net zero carbon built environment has never been more important. Many studies have shown the capabilities of advanced control strategies such as model predictive control (MPC) to achieve energy efficiency, balance with thermal comfort and air quality. It has also shown its capability to provide demand flexibility, minimising peak load demands and maximising the production of renewable energy sources in buildings. This work investigates the potential of integrating price-responsive MPC with a low-temperature heating system and passive structural thermal energy storage (STES). Integration with a photovoltaic (PV) system is also explored. The system performance under future climate conditions is evaluated considering different design and operating conditions, including different thermal mass, occupancy patterns and internal heat gains, setpoint strategies and operation temperatures of the low-temperature heating system. The coupled model developed has been verified and validated with numerical and experimental data, and good agreement is observed. The results showed that mediumweight thermal mass and a medium-temperature (45 °C ) under-floor heating inlet temperature provided a higher load shifting ability, based on a realistic occupancy profile for a residential building and a high tolerance setpoint strategy during unoccupied periods. The result also showed that higher low-price energy usage and lower heating energy usage could be achieved in future climate conditions. Finally, an increase in the load shifting ability was observed after the integration of rooftop solar PV system. Building energy Climate change Future weather conditions Model predictive control (MPC) Occupancy Passive structural thermal energy storage Price response Solar energy Thermal mass TRNSYS Calautit, John verfasserin aut Enthalten in Energy Amsterdam [u.a.] : Elsevier Science, 1976 269 Online-Ressource (DE-627)320597903 (DE-600)2019804-8 (DE-576)116451815 1873-6785 nnns volume:269 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 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_4338 GBV_ILN_4393 GBV_ILN_4700 50.70 Energie: Allgemeines VZ AR 269
language	English
source	Enthalten in Energy 269 volume:269
sourceStr	Enthalten in Energy 269 volume:269
format_phy_str_mv	Article
bklname	Energie: Allgemeines
institution	findex.gbv.de
topic_facet	Building energy Climate change Future weather conditions Model predictive control (MPC) Occupancy Passive structural thermal energy storage Price response Solar energy Thermal mass TRNSYS
dewey-raw	600
isfreeaccess_bool	false
container_title	Energy
authorswithroles_txt_mv	Wei, Zhichen @@aut@@ Calautit, John @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	320597903
dewey-sort	3600
id	ELV060839570
language_de	englisch
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author	Wei, Zhichen
spellingShingle	Wei, Zhichen ddc 600 bkl 50.70 misc Building energy misc Climate change misc Future weather conditions misc Model predictive control (MPC) misc Occupancy misc Passive structural thermal energy storage misc Price response misc Solar energy misc Thermal mass misc TRNSYS Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change
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topic_title	600 VZ 50.70 bkl Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change Building energy Climate change Future weather conditions Model predictive control (MPC) Occupancy Passive structural thermal energy storage Price response Solar energy Thermal mass TRNSYS
topic	ddc 600 bkl 50.70 misc Building energy misc Climate change misc Future weather conditions misc Model predictive control (MPC) misc Occupancy misc Passive structural thermal energy storage misc Price response misc Solar energy misc Thermal mass misc TRNSYS
topic_unstemmed	ddc 600 bkl 50.70 misc Building energy misc Climate change misc Future weather conditions misc Model predictive control (MPC) misc Occupancy misc Passive structural thermal energy storage misc Price response misc Solar energy misc Thermal mass misc TRNSYS
topic_browse	ddc 600 bkl 50.70 misc Building energy misc Climate change misc Future weather conditions misc Model predictive control (MPC) misc Occupancy misc Passive structural thermal energy storage misc Price response misc Solar energy misc Thermal mass misc TRNSYS
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title	Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change
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title_full	Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change
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title_sort	predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: impact of occupancy patterns and climate change
title_auth	Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change
abstract	With the increasing energy prices and growing concerns over energy security, an accelerated transition to net zero carbon built environment has never been more important. Many studies have shown the capabilities of advanced control strategies such as model predictive control (MPC) to achieve energy efficiency, balance with thermal comfort and air quality. It has also shown its capability to provide demand flexibility, minimising peak load demands and maximising the production of renewable energy sources in buildings. This work investigates the potential of integrating price-responsive MPC with a low-temperature heating system and passive structural thermal energy storage (STES). Integration with a photovoltaic (PV) system is also explored. The system performance under future climate conditions is evaluated considering different design and operating conditions, including different thermal mass, occupancy patterns and internal heat gains, setpoint strategies and operation temperatures of the low-temperature heating system. The coupled model developed has been verified and validated with numerical and experimental data, and good agreement is observed. The results showed that mediumweight thermal mass and a medium-temperature (45 °C ) under-floor heating inlet temperature provided a higher load shifting ability, based on a realistic occupancy profile for a residential building and a high tolerance setpoint strategy during unoccupied periods. The result also showed that higher low-price energy usage and lower heating energy usage could be achieved in future climate conditions. Finally, an increase in the load shifting ability was observed after the integration of rooftop solar PV system.
abstractGer	With the increasing energy prices and growing concerns over energy security, an accelerated transition to net zero carbon built environment has never been more important. Many studies have shown the capabilities of advanced control strategies such as model predictive control (MPC) to achieve energy efficiency, balance with thermal comfort and air quality. It has also shown its capability to provide demand flexibility, minimising peak load demands and maximising the production of renewable energy sources in buildings. This work investigates the potential of integrating price-responsive MPC with a low-temperature heating system and passive structural thermal energy storage (STES). Integration with a photovoltaic (PV) system is also explored. The system performance under future climate conditions is evaluated considering different design and operating conditions, including different thermal mass, occupancy patterns and internal heat gains, setpoint strategies and operation temperatures of the low-temperature heating system. The coupled model developed has been verified and validated with numerical and experimental data, and good agreement is observed. The results showed that mediumweight thermal mass and a medium-temperature (45 °C ) under-floor heating inlet temperature provided a higher load shifting ability, based on a realistic occupancy profile for a residential building and a high tolerance setpoint strategy during unoccupied periods. The result also showed that higher low-price energy usage and lower heating energy usage could be achieved in future climate conditions. Finally, an increase in the load shifting ability was observed after the integration of rooftop solar PV system.
abstract_unstemmed	With the increasing energy prices and growing concerns over energy security, an accelerated transition to net zero carbon built environment has never been more important. Many studies have shown the capabilities of advanced control strategies such as model predictive control (MPC) to achieve energy efficiency, balance with thermal comfort and air quality. It has also shown its capability to provide demand flexibility, minimising peak load demands and maximising the production of renewable energy sources in buildings. This work investigates the potential of integrating price-responsive MPC with a low-temperature heating system and passive structural thermal energy storage (STES). Integration with a photovoltaic (PV) system is also explored. The system performance under future climate conditions is evaluated considering different design and operating conditions, including different thermal mass, occupancy patterns and internal heat gains, setpoint strategies and operation temperatures of the low-temperature heating system. The coupled model developed has been verified and validated with numerical and experimental data, and good agreement is observed. The results showed that mediumweight thermal mass and a medium-temperature (45 °C ) under-floor heating inlet temperature provided a higher load shifting ability, based on a realistic occupancy profile for a residential building and a high tolerance setpoint strategy during unoccupied periods. The result also showed that higher low-price energy usage and lower heating energy usage could be achieved in future climate conditions. Finally, an increase in the load shifting ability was observed after the integration of rooftop solar PV system.
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title_short	Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change
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up_date	2024-07-06T16:53:57.916Z
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Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change

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