Doctoral Seminar - School of Civil and Building Engineering
Heating control technology optimization for energy demand
reduction in UK homes using smart home technology
Arash Beizaee
2nd Year PhD Researcher
Supervisors: Dr. David Allinson, Prof. Kevin Lomas, Prof. Dennis Loveday
17 December 2013
Background:
• Climate change act 2008:
 By the year 2050: 80% reduction in GHG emissions compared to 1990 levels.
• Residential fossil fuel: large contribution to total CO2 emissions.
(DECC, 2012)
• Space heating accounted for 61% of total energy consumption and
Co2 emissions in residential sector. (DECC, 2011)
Background:
• A standard domestic gas central heating system in comply with
Building Regulations
Part L:
Total number of households with at least one resident
23 Million
Percentage of households with gas central heating
79%
Percentage of homes which do not reach minimum levels of control
70%
Number of homes with no room thermostat
8 Million
Number of homes with no TRV
10 Million
Number of homes with a boiler and no control at all
800 000
Source: (Census 2011 & TACMA)
Background:
• Energy is being wasted in UK homes due to poor space heating
control strategies (even in those which are in comply with
minimum requirements of Building Regulations):
 Heating the whole house (including
unoccupied spaces) when only
a fraction of the house is actually in use.
• Question: Is it possible to heat
different zones individually without requiring
additional pipe work which would be disruptive, expensive and
where the pipework layout is often not available!
• Digital programmable
TRVs enable the
application of ZC:
 Each zone can be controlled
to be heated only at the time
needed and to the level required.
Question: How much energy ZC can potentially save?
•
•
Well insulated house / leaky house: different heat transfer between zones
Family home / home with elderly occupants: different heating patterns
Methodology:
• Comparing ZC and Building Reg Part L control requirements:
• Space heating trials over a winter:
Two identical test houses: indoor temperature and energy
consumption measurement, occupancy simulation.
• Dynamic models will be developed & calibrated using the
measured data.
• Models will be used to quantify the potential savings from
houses of different insulation levels and occupancy patterns.
Progress so far:
• Heating control experiments in two identical test houses are in
progress:
• Considerable amount of time has been spent on matching the
two houses and experimental set up:




Building characteristics (size, fabric, insulation, etc…)
Heating systems (Boilers, radiators, thermostats)
Occupant behaviour
Weather conditions
 Building characteristics (size, fabric, insulation, etc…):
Initial inspections: Remove the loft insulation
& Co-heating test side by side
• ~ 8% difference between the
two houses (KWH/DT)
 Heating systems (Boilers, radiators, thermostats)
• All the old & rusty radiators were replaced by the new
radiators with the same size in both houses.
• New identical thermostats were installed in both homes.
• Pumps needed to be replaces to be the same in both boilers.
 Occupant behaviour: Simulate the presence of occupants
• Internal heat gains from the occupants, lighting and equipment
using tubular green house heaters and light bulbs.
• Automatic windows, blinds & internal doors.
• Using Z-wave devices and
controller to operate the
automation devices based on
defined schedules
 Weather conditions
• minimize the solar radiation at East / West facades by
insulating the glazing (still heat transfer through the walls
would cause a little different)
• What I’m measuring:
 Indoor air temperatures at zone level: Sensors with high
response and accuracy needed: 10 thermistors at each house,
located at the centre of different zones at mid height.
 Outdoor temperature using a water
resistance thermistor shaded from solar
radiation and facing the sky.
• What I’m measuring:
 Flow and return water temperature at the boiler and each
radiator using thermocouples attached on the flow and return
pipe surfaces.
 Water flow rate of the central heating using
flow meters with pulse output.
 Gas consumption every 10 minutes.
 Data logger with ability to
live monitoring data on the web was
required.
• What’s next?
• Analyse the data collected from the space heating trials.
• Develop dynamic models of the test houses and calibrate them
using the experimental data collected.
• Quantify the potential savings which could be achieved in
houses with different levels of building envelope thermal
efficiency and occupancy patterns.
Thank You!
Any question ???