room temperature profiles, the time and spatial variations of thermostat settings, such as turned on and off, operated continuously or periodically, adjustment and controlling of equipment settings could then be described and further recognized combining with questionnaire, Usage patterns across the monitoring period, for example, time( daytime, nighttime), duration( always on, on continuously), frequency, and temperature settings( high, low in value, time variation), adjustment( active / inactive), zonal control( room variation) were identified and then categorized by profile characteristics. For example, as shown in Tab. 2, in sample household No. 11, family members were absence at daytime and heating equipment was running periodically. Room temperatures were adjustable according to the user demand from 19 ~ 23 ° C. Household room temperatures varied independently during monitoring period. Although the heating energy consumption( ENG) of No. 11 was relatively low in value, 0.8 m3 /( m2 · month), it actually had a rather high value of indoor thermal comfort temperature hours percentage( Pcth, 100 %, mean value 83 %). As for household No. 5, on the other hand, the heating system was running continuously and not active in temperature setting adjustment. It had a much higher value of energy consumption( ENG) 3.1m3 /( m2 · month) and yet a slightly lower Pcth( 93.9 %) than that of No. 11( 100 %).
Table 2: Superposition of room temperature profiles, boiler controlling patterns and gas consumption
No.
Room temperature profiles( Dec. 2012 ~ Apr. 2013 and Feb. 1 ~ Feb. 14 2013)
Controlling patterns, gas consumption and thermal comfort
5 Controlling patterns: Heating system was running continuously, and periodically. Room temperatures were ranged from 17 to 25 ° C. Settings were not adjusted actively. Not zonal controlled and room temperatures were varied independently. Temperature of living room was always higher than bedrooms.
ENG: 3.1( mean value 2), m3 /( m2 · month); Pcth: 93.9 %( mean value 83 %);
Household lifestyle and its impacts on energy consumption in Beijing 95