Delft University of Technology
Analysis of comfort related behavior for better prediction of heating and electricity
consumption in residential dwellings
Ioannou, Taso; Itard, Laure; Kornaat, Wim DOI
10.13140/RG.2.1.3561.8167
Publication date 2016
Document Version Final published version
Citation (APA)
Ioannou, T., Itard, L., & Kornaat, W. (2016). Analysis of comfort related behavior for better prediction of heating and electricity consumption in residential dwellings. Poster session presented at CLIMA 2016 - 12th REHVA World Congress, Aalborg, Denmark. https://doi.org/10.13140/RG.2.1.3561.8167
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RESEARCH POSTER PRESENTATION DESIGN © 2015
www.PosterPresentations.com
•Which measurable parameters (including occupant behaviour)
influence the actual energy use in dwellings?
•How can prediction models for energy consumption be improved?
Sub-questions:
•What is the bandwidth and average behaviour for use of electrical appliances, thermostat settings,
occupancy of rooms, ventilation, radiator settings, hot tap water use, sun shades and how do these data
relate to actual energy use?
•Is it possible to define behavioural groups in relation to actual energy use?
•Is there a relationship between type of installation, dwelling characteristics , behaviour and energy use?
•Is it possible to determine a bandwidth of user profiles to be fed in calculation software in order to get a
probability of energy use (distribution) instead of one value?
•How can prediction (simulation) models be improved in order to match better actual statistical data?
•What is the relationship between predicted and actual comfort in Dutch residential dwellings, how can
comfort models be improved and how do they relate with the energy consumption of the residential
sector.
Research Questions
Research Campaign
Conclusions
•Differences in the temperature spread between living rooms and bedrooms which leads to the
conclusion that simplified one zone models for the energy calculations of dwellings are flawed
.
•With the exception of a few hours in two living rooms (W031 and W032) all other living
rooms and for the whole day the temperature lies above 18
o
C which is the temperature
suggested for the calculations of the national simulation software.
•The Dutch notion that bedrooms are not heated during the night seems to be false. Apart
from 3 bedrooms (W002, W017 and W032) all the other ones have either a more or less
constant temperature profile or a fluctuating one with temperatures well above 18
o
C. More
than half of these dwellings are F labeled which means that there must be heating during the
night.
•A combination of motion detection and CO2 gives a good prediction of the actual presence.
This can be expanded based on the monitoring data and can give further possibilities for
analysis. The occupancy profile calculations focus on the presence and not on the number of
persons present. In case the number of persons in the household is known, rules can be added
for this purpose. For instance if a person is detected in a bedroom, there should be at least
one occupant less in for instance the living room. Furthermore 1 and 2 person bedrooms can
be defined. This gives additional information about the possible number of persons when
there is presence predicted in a room.
Sensors in each house:
•Living Room, Kitchen, Bedroom 1 and 2: Honeywell CO2, T, Hu and PIR
•Boiler, Heat pump, Mechanical Ventilation Pumps: Eltako Electricity Meter
•I/O Comfort Dial
•Youless online electricity monitoring on the meter
1,2
OTB/DWK, TU Delft 2628 bl, Julianalaan 134, 2628 BL Delft, The Netherlands
1
a.ioannou@tudelft.nl
2
l.c.m.itard@tudelft.nl
3
TNO Van Mourik Broekmanweg 6, 2628 XE Delft
3
wim.kornaat@tno.nl
Anastasios Ioannou
1
, Laure Itard
2
, Wim Kornaat
3
Analysis of comfort related behavior for better prediction of
heating and electricity consumption in residential dwellings
Heating System
House Label
Heat
Pump
HR
boiler
Local
stove
A+B
4
9
-
F
-
17
2
Data
•Initial Survey for Qualitative data (age, income level,
sex, type of thermostat, type of heating system,
ventilation patterns, thermostat level etc.)
•Quantitative data every 5 minutes (CO
2
, T, RH,
motion, heating/ventilation systems’ pump
consumption)
•Qualitative Comfort data for a period of 2 weeks for
each household
Results
14.0 15.0 16.0 17.0 18.0 19.0 20.0 21.0 22.0 23.0 24.0 25.0 26.0 27.0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Tem p e ratu re oC Hour24 Hour Averages--Dwellings with Mech. Extraction Point--Living Room
W001--Living Room--T W002--Living Room--T W010--Living Room--T W011--Living Room--T W015--Living Room--T W016--Living Room--T W017--Living Room--T W021--Living Room--T W022--Living Room--T W024--Living Room--T W028--Living Room--T W029--Living Room--T W031--Livigng Room--T W032--Living Room--T 14.0 15.0 16.0 17.0 18.0 19.0 20.0 21.0 22.0 23.0 24.0 25.0 26.0 27.0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Tem p e ratu re oC Hour
24 Hour Averages--Natural Ventilated Dwellings with Mechanical Extraction
Points--Bedroom 1
W001--Bedroom 1--HR boilerW002--Bedroom 1--HR boiler W010--Bedroom 1--HR boiler W011--Bedroom 1--HR boiler W015--Bedroom 1--HR boiler W016--Bedroom 1--HR boiler W017-Bedroom 1--HR boiler W021--Bedroom 1--HR boiler W022--Bedroom 1--HR boiler W024--Bedroom 1--HR boiler W028--Bedroom 1--HR boiler W029--Bedroom 1--HR boiler W031--Bedroom 1--HR boiler W032--Bedroom 1--HR boiler 1 4 22 6 6 2 2 3 11 17 7 4 4 27 89 15 6 2 3 5 9 2 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Cl o th in g t yp e % fo r e ac h c o m for t le ve l Comfort level
Clothing type for all comfort levels
jacket and hood jacket
long sleeved sweat shirt knit sport shirt
t-shirt sleeveless t-shirt 6 10 22 5 1 2 3 17 70 18 4 2 12 43 14 1 4 14 60 13 4 1 6 8 4 2 3 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
cold cool a bit cool neutral a bit warm warm hot M e tab o lic ac tiv ity % fo r e ac h c o m for t le ve l Comfort level
Metabolic activity for all comfort levels
running jogging walking light desk work sitting relaxed lying/sleeping 1 14 14 4 3 2 14 4 2 7 50 78 15 2 9 25 18 3 2 2 5 5 1 2 10 8 2 2 7 34 17 3 2 5 17 14 1 2 5 3 1 1 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
cold cool a bit cool neutral a bit warm warm hot A ction s l ast h al f h o u r % for e ac h c o m for t le ve l Comfort level
Actions last half hour for all comfort levels
cold shower warm shower thermostat down thermostat up put off clothes put on clothes cold drink hot drink closing window opening window 16.0 17.0 18.0 19.0 20.0 21.0 22.0
cold cool a bit cool neutral a bit warm warm hot Tem p e ratu re (C o) Comfort level
Average temperature for all rooms per comfort
level
Kitchen Living Room Bedroom 1 Bedroom 2 0 1 2 3 4 5 0 200 400 600 800 1000 1200 1400 1600 180013-Jan-15 13-Jan-15 13-Jan-15 13-Jan-15 14-Jan-15
