Residential heating, ventilation and air conditioning(HVAC) provides important demand response resources for the new power system with high proportion of renewable energy. Residential HAVC scheduling strategies that a...Residential heating, ventilation and air conditioning(HVAC) provides important demand response resources for the new power system with high proportion of renewable energy. Residential HAVC scheduling strategies that adapt to realtime electricity price signals formulated by demand response program and ambient temperature can significantly reduce electricity costs while ensuring occupants' comfort. However, since the pricing process and weather conditions are affected by many factors, conventional model-based method is difficult to meet the scheduling requirements in complex environments. To solve this problem, we propose an adaptive optimal scheduling strategy for residential HVAC based on deep reinforcement learning(DRL) method. The scheduling problem can be regarded as a Markov decision process(MDP). The proposed method can adaptively learn the state transition probability to make economical decision under the tolerance violations. Specifically, the residential thermal parameters obtained by the leastsquares parameter estimation(LSPE) can provide a basis for the state transition probability of MDP. Daily simulations are verified under the electricity prices and temperature data sets, and numerous experimental results demonstrate the effectiveness of the proposed method.展开更多
When a historic façade needs to be preserved or when the seismic considerations favor use of a concrete wall system and fire considerations limit exterior thermal insulation,one needs to use interior thermal insu...When a historic façade needs to be preserved or when the seismic considerations favor use of a concrete wall system and fire considerations limit exterior thermal insulation,one needs to use interior thermal insulation systems.Interior thermal insulation systems are less effective than the exterior systems and will not reduce the effect of thermal bridges.Yet they may be successfully used and,in many instances,are recommended as a complement to the exterior insulation.This paper presents one of these cases.It is focused on the most successful applications of capillary active,dynamic interior thermal insulation.This happens when such insulation is integrated with heating,cooling and ventilation,air conditioning(HVAC)system.Starting with a pioneering work of the Technical University in Dresden in development of capillary active interior insulations,we propose a next generation,namely,a bio-fiber thermal insulation.When completing the review,this paper proposes a concept of a joint research project to be undertaken by partners from the US(where improvement of indoor climate in exposed coastal areas is needed),China(indoor climate in non-air conditioned concrete buildings is an issue),and Germany(where the bio-fiber technology has been developed).展开更多
Mature technologies exist to reduce the heating,ventilation,and air-conditioning(HVAC) energy associated with ventilation and use ventilation proactively to save energy.This study investigated the energy use impacts i...Mature technologies exist to reduce the heating,ventilation,and air-conditioning(HVAC) energy associated with ventilation and use ventilation proactively to save energy.This study investigated the energy use impacts in U.S.office buildings of multiple alternative ventilation strategies that combined:economizing,demand controlled ventilation(DCV),supply air temperature reset(SR),and/or a doubled ventilation rate.We used energy simulations in a Monte Carlo analysis,sampling 17 building inputs and varying locations to match the climate zone distribution of the U.S.office stock.Results indicated the possibility for significant savings compared to a baseline that ventilated constantly at a minimum rate in both a small office type with a constant air volume(CAV) HVAC system and a medium office type with a variable air volume(VAV) system.In 95%of instances,HVAC source energy savings were 5-25%in the small-CAV office(median:11%) and 6-42%in the medium-VAV office(median:27%).In the small-CAV office,DCV typically saved the most energy,usually from heating,and heating degree days and occupant density were decisive influences.In the medium-VAV office,economizing and SR were most important,DCV usually only had minor impacts,and zone temperature setpoints,along with climate indicators,were the critical influences.Other than infiltration,envelope characteristics did not strongly influence energy impacts.The untapped primary energy savings of alternative ventilation strategies over the 74%of U.S.office floorspace reasonably represented by our modeling was estimated at 36 TWh per year,with an annual value of U.S.$ 1.25 billion.展开更多
For sustainable development, a reduction in energy demand is essential. This could be achieved through improving energy efficiency, effective energy conservation and management. The weather conditions of a given regio...For sustainable development, a reduction in energy demand is essential. This could be achieved through improving energy efficiency, effective energy conservation and management. The weather conditions of a given region are the most important consideration for the proper design of space AC （Air Conditioning） systems. In this study, the typical meteorological year and climatic database of Turkey for the energy analysis of buildings were generated by SQL （Structured Query Language） database programmimg language. The Finkelstein-Schafer statistical method was applied to analyze the hourly measured weather data of a 23-year period （1989-2012） and select representative TMMs （Typical Meteorological Months）. The selection criteria were based on 13 meteorological parameters. These parameters are the daily mean, maximum and minimum values and ranges of temperature, dew-point and wind velocity and the daily values of global solar radiation. According to results of TMY （Typical Meteorological Year）, climatic database of Turkey including daily or hourly climate variables was created in SQL data tables.展开更多
基金supported in part by the Fundamental Research Funds for the Central Universities (No. 2018JBZ004)the National Natural Science Foundation of China (No. 52007004)。
文摘Residential heating, ventilation and air conditioning(HVAC) provides important demand response resources for the new power system with high proportion of renewable energy. Residential HAVC scheduling strategies that adapt to realtime electricity price signals formulated by demand response program and ambient temperature can significantly reduce electricity costs while ensuring occupants' comfort. However, since the pricing process and weather conditions are affected by many factors, conventional model-based method is difficult to meet the scheduling requirements in complex environments. To solve this problem, we propose an adaptive optimal scheduling strategy for residential HVAC based on deep reinforcement learning(DRL) method. The scheduling problem can be regarded as a Markov decision process(MDP). The proposed method can adaptively learn the state transition probability to make economical decision under the tolerance violations. Specifically, the residential thermal parameters obtained by the leastsquares parameter estimation(LSPE) can provide a basis for the state transition probability of MDP. Daily simulations are verified under the electricity prices and temperature data sets, and numerous experimental results demonstrate the effectiveness of the proposed method.
文摘When a historic façade needs to be preserved or when the seismic considerations favor use of a concrete wall system and fire considerations limit exterior thermal insulation,one needs to use interior thermal insulation systems.Interior thermal insulation systems are less effective than the exterior systems and will not reduce the effect of thermal bridges.Yet they may be successfully used and,in many instances,are recommended as a complement to the exterior insulation.This paper presents one of these cases.It is focused on the most successful applications of capillary active,dynamic interior thermal insulation.This happens when such insulation is integrated with heating,cooling and ventilation,air conditioning(HVAC)system.Starting with a pioneering work of the Technical University in Dresden in development of capillary active interior insulations,we propose a next generation,namely,a bio-fiber thermal insulation.When completing the review,this paper proposes a concept of a joint research project to be undertaken by partners from the US(where improvement of indoor climate in exposed coastal areas is needed),China(indoor climate in non-air conditioned concrete buildings is an issue),and Germany(where the bio-fiber technology has been developed).
文摘Mature technologies exist to reduce the heating,ventilation,and air-conditioning(HVAC) energy associated with ventilation and use ventilation proactively to save energy.This study investigated the energy use impacts in U.S.office buildings of multiple alternative ventilation strategies that combined:economizing,demand controlled ventilation(DCV),supply air temperature reset(SR),and/or a doubled ventilation rate.We used energy simulations in a Monte Carlo analysis,sampling 17 building inputs and varying locations to match the climate zone distribution of the U.S.office stock.Results indicated the possibility for significant savings compared to a baseline that ventilated constantly at a minimum rate in both a small office type with a constant air volume(CAV) HVAC system and a medium office type with a variable air volume(VAV) system.In 95%of instances,HVAC source energy savings were 5-25%in the small-CAV office(median:11%) and 6-42%in the medium-VAV office(median:27%).In the small-CAV office,DCV typically saved the most energy,usually from heating,and heating degree days and occupant density were decisive influences.In the medium-VAV office,economizing and SR were most important,DCV usually only had minor impacts,and zone temperature setpoints,along with climate indicators,were the critical influences.Other than infiltration,envelope characteristics did not strongly influence energy impacts.The untapped primary energy savings of alternative ventilation strategies over the 74%of U.S.office floorspace reasonably represented by our modeling was estimated at 36 TWh per year,with an annual value of U.S.$ 1.25 billion.
文摘For sustainable development, a reduction in energy demand is essential. This could be achieved through improving energy efficiency, effective energy conservation and management. The weather conditions of a given region are the most important consideration for the proper design of space AC （Air Conditioning） systems. In this study, the typical meteorological year and climatic database of Turkey for the energy analysis of buildings were generated by SQL （Structured Query Language） database programmimg language. The Finkelstein-Schafer statistical method was applied to analyze the hourly measured weather data of a 23-year period （1989-2012） and select representative TMMs （Typical Meteorological Months）. The selection criteria were based on 13 meteorological parameters. These parameters are the daily mean, maximum and minimum values and ranges of temperature, dew-point and wind velocity and the daily values of global solar radiation. According to results of TMY （Typical Meteorological Year）, climatic database of Turkey including daily or hourly climate variables was created in SQL data tables.
