1. Presenter: Christopher Tsang University: Loughborough University Email: h.h.c.tsang@lboro.ac.uk RETROFIT OF DWELLINGS IN CHINESE CITIES

2. BACKGROUND Climate zones in ChinaHot summer and cold winterAir conditioners for heating and cooling Fan heaters and electric blanket for heating Indoor temperature versus outdoor temperature in north and south China Increase comfort may lead to tremendous increase in energy use

3. SCALE OF THE RESEARCH Chongqing 33 million 82400 km² City area ~7 million 5473 km² Core area ~0.64 million 18.54 km² ~200 buildings

4. RESEARCH QUESTION To investigate retrofit options for dwellings in cities located in Hot Summer Cold Winter (HSCW) climate zone in China By choosing the appropriate active and passive system In order to improve thermal comfort and minimise heating & cooling energy use

5. METHODS USED Model Monthly quasi-steady-state calculation method from BS EN ISO 13790:2008 Boundary conditions External temperature, solar radiation, occupancy, casual gains Parameters Geometry of building, construction characteristics, heating & ventilation specifications Output variables Heating and cooling energy demand per unit floor area

6. METHODOLOGY AND RESULTS Fig.1: Annual energy consumption in London and Chongqing Fig.2: Monthly energy consumption in London and Chongqing

7. METHODOLOGY AND RESULTS RegimeNo. of occupants Internal heat gain % hours with heating % hours with cooling Heating setpoint Cooling setpoint 127W/m 2 25%20%23°C27°C 2 (Base Case) 39W/m 2 20%25%22°C26°C 3411W/m 2 15%30%21°C25°C TierExplanationExample 1Parameters that are easier to changeU-value window, air change 2Parameters that need to adjust occupant behaviour Fraction of hours heating present, cooling setpoint 3Parameters that are difficult to changeThermal mass, U-value wall Table 1: Evaluation of the impact of input parameters Table 2: Development of occupancy regimes

8. METHODOLOGY AND RESULTS ParameterUnitValue change U-value windowW/m 2 K2.8 -> 2 Air change per hourach -1 1 -> 0.823 G-value glazing-0.2 -> 0.2 External shade factor-1 -> 0.6 Internal shade factor-1 -> 0.6 Table 3: Optimization of Tier 1 input parameters Fig.3. Change in energy consumption after optimization Fig.4. Change in energy consumption with different occupancy regimes

9. METHODS INTENDED TO BE USED Using the above retrofit options, extend the study to tower blocks and city scale Using optimization to find out retrofit options to achieve minimum energy use Using sensitivity analysis to find out important input parameters Using monitored data over two seasonal cycles to validate base case models Using EnergyPlus to design base case models in different types of flats Using monthly quasi-steady-state calculation method to estimate energy use in a flat

10. BENEFITS AND CHALLENGES Benefits Provide representative predictions Provide optimum solution to retrofit dwellings in China Provide micro and macro view of the problem Challenges Sensitivity analysis for each base case models lead to long simulation time Selection of the design solution after optimization is difficult to perform The scale for tower block and city scale study is huge, therefore many data need to be collected and analyse