posted on 2020-10-09, 08:40authored byChristopher Tsang
Urban areas in the Hot Summer and Cold Winter (HSCW) zone in China are home to 8% of the world’s population. Existing residential buildings in the HSCW zone in China are cold in winter and overheat in summer, due to a lack of adequate building fabric and central space heating in response to current legislation. As living standards increase, the number of residential buildings with installed air conditioning (AC) systems is also growing, which leads to a sharp increase in energy consumption. Building retrofit plays a vital role in reducing energy consumption and carbon dioxide emissions while increasing occupants’ thermal comfort. This study aims to develop retrofit measures for urban residential buildings and quantify the potential annual space-conditioning energy savings with regards to kWh at a city scale in the HSCW zone in China.
A typical urban multi-storey residential building in Chongqing, a city in the HSCW zone of China, was used to develop a dynamic thermal model (DTM), following a systematic review to characterise building parameters. Then, a single flat was calibrated using indoor air temperature measured over one week. Afterwards, energy and thermal comfort performance was evaluated before and after energy saving retrofits using the calibrated DTM of the single flat, and twelve different flats location with regards to the building. To represent typical residential users, three types of households with different AC operating schedules were developed: high, medium, and low. After that, an optimum combination of retrofit measures able to reduce energy consumption and thermal discomfort of the typical building was selected for each of the seven retrofit measures accordingly: external wall insulation, roof insulation, double-glazed windows, air infiltration control, additional window overhang, enclosed communal staircase, and energy-efficient AC. Finally, a DTM of the typical building was created at nine levels of computational detail. The most computationally efficient DTM was then identified to devise twelve residential building archetypes, to quantify the energy reduction due to energy saving retrofits at a city scale for 321 residential buildings in Chongqing.
The results showed that a substantial amount of annual space-conditioning energy is required to maintain comfortable conditions for existing residential buildings in the HSCW zone. Despite a high energy consumption for comfort was theoretically required, results predicted that energy used was only 9.2 to 18.8 kWh/m2, depended on the use that was made of the AC system. As the predicted mean indoor air temperature in winter was 14°C and in summer was 29°C due to the occupants’ adaption to the environment. Not surprisingly, retrofitting these buildings was not cost-efficient, with a payback period of 56 years, when adaptive behaviour was considered. Yet, thermal comfort was improved significantly in winter and at the same time summertime overheating was prevented under the proposed retrofit measures. To evaluate large-scale residential energy saving retrofits, DTM with different level of computational detail were created, the most suitable DTM was used to wider applicability of outputs of the typical building; results showed that it reduced simulation time by 70% and achieved a 5% prediction difference of energy demand when compared to the case study building (DTM with the greatest level of computational detail).
The devised residential building archetypes predicted an annual 73% to 76% reduction for heating, 39% to 45% reduction for cooling, and 50% to 57% reduction for total energy consumption. At a city-scale for 321 residential buildings with built area of 4.07 million m2, 17 TWh of annual space-conditioning energy can be reduced if the proposed retrofit measures are employed. More importantly, the potential long-term energy savings do outweigh the cost, given the Chinese government pursuit of net-zero emissions by 2050.
Funding
Low carbon climate-responsive Heating and Cooling of Cities (LoHCool)
Engineering and Physical Sciences Research Council