IBP
FRAUNHOFER INSTITUTE FOR BUILDING PHYSICS IBP
IBP REPORT
527
40 (2013) NEW REASEARCH RESULTS IN BRIEF
Matthias Kersken,
Herbert Sinnesbichler
SIMULATION STUDY ON THE ENERGY SAVING POTENTIAL OF A HEATING CONTROL SYSTEM FEATURING
PRESENCE DETECTION AND WEATHER FORECASTING
Fraunhofer Institute for
BACKGROUND
their arrival the heating is activated. That
Building Physics IBP
Conventional heating control systems
determines what level of comfort has al-
Nobelstr. 12, 70569 Stuttgart, Germany
regulate the temperature based solely on
ready been reached by the time they arrive.
Phone +49 711 970-00
local measurements – indoor or outdoor
Furthermore, the system has access to local
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air temperature. Advanced systems allow
weather forecasts and records data on how
users to programme schedules. During
the forecasted solar radiation influences
Holzkirchen Branch
defined periods of absence, lower set
the room air temperatures. Based on these
Fraunhoferstr. 10, 83626 Valley, Germany
temperatures in the rooms reduce the
data, the system turns down the heating
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energy consumption for heating. However,
in advance when sufficient sun is expected
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these systems can neither react to periods
within the next hour.
of user presence or absence that have not
Kassel Branch
been programmed, nor take the climatic
METHOD OF EVALUATION
Gottschalkstr. 28a, 34127 Kassel, Germany
conditions for the coming hours into
The study described here is based on
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account.
transient calculations (TRNSYS 17). The
[email protected]
www.ibp.fraunhofer.de
Literature
[1] DIN V 18599-10:2007-02. Energy efficiency of buildings – Calculation of the energy needs, delivered energy
and primary energy for heating, cooling, ventilation,
domestic hot water and lighting – Part 10: Boundary
conditions of use, climatic data.
[2] Christoffer, Jürgen; Deutschländer, Thomas; Webs,
Monika: Testreferenzjahre von Deutschland für mittlere
und extreme Witterungs-verhältnisse TRY. Offenbach a.
Main: Selbstverlag des Deutschen Wetterdienstes, 2004.
© Fraunhofer Institute for Building Physics IBP - Any reproduction or use of text and graphics (in full or in part)
requires prior written permission of the Fraunhofer IBP.
algorithm of the evaluated system is
EVALUATED SYSTEM
replicated in simplified form and linked
In addition to the features of conventional
with TRNSYS. This study is carried out on
heating controls such as programmable
a typical single family house and a typical
periods of absence, the system evaluated
apartment with 5 rooms. In addition, it
here is able to detect the position of the
evaluates two different construction ages.
residents’ smartphones via GPS. Using this
data, it statistically calculates each resident’s
A single and a family household serve as
estimated time of arrival at home. The
scenarios to evaluate different kinds of
intelligent system also learns how long it
usage. Realistic set temperature profiles are
takes to heat the home so the heating can
specified for each scenario.
be activated early enough before the first
user gets home. By choosing a comfort set-
In order to simulate the heating behaviour
ting the users can specify how long before
in conjunction with realistic supply tem-
2
1
peratures, the simulation model includes
RESULTS
a heating curve based on the outside
It can be shown that the evaluated system
temperature and detailed models of the
can reduce the heating energy requirements
radiators and their controls. This study uses
of the investigated homes by 14-26 %
one of the system’s lower comfort settings.
through intelligent control of the heat
Fig. 1: Net heating energy savings for an unrefurbished appartment occupied by a single and
for a single family house, occupied by a family.
200
Reference house
Test house
source (e.g. boiler or heat pump). Since a
150
100 %
162,4
100 %
155,1
lower comfort setting is used in this study,
The reference building is the baseline the
the home is sometimes not fully heated
results of the test building are compared to.
when the first resident arrives. Therefore in
It is the exact equivalent of the test building
some periods the actual temperature falls
apart from one detail: the conventional
below the target temperature. Aside from
radiator thermostats in all rooms are set
the chosen comfort setting, the achievable
so as to maintain a constant temperature
energy savings primarily depend on the
of 20 °C during the day. To reduce the
amount of time the users are at home each
temperatures for the night the heating
day, the chosen room air temperatures dur-
system’s supply temperature is reduced by
ing absence, and the level of the internal
It has been shown that the presence
10 K [1].
heat sources (refrigerator, oven, etc.). The
detection alone can bring about a heating
more frequently the users leave the home
energy saving of up to 24 %. Furthermore,
SIMULATING THE WEATHER FORECAST
and the longer they are absent, the larger
by turning down the heating only based
The evaluated system uses a forecast of
the system’s potential energy savings are,
on the weather forecast, the system also
the solar global radiation. Naturally there is
as this increases the length and frequency
can make additional savings of up to 7 %,
some deviation between this forecast and
of the periods with reduced room air
based on the window sizes chosen here.
the actual level of radiation. The “real”
temperatures. In the case of systems using
If the window surfaces are relatively large,
radiation, like all the climate data, is repre-
preprogrammed usage periods, it is possi-
this effect will increase accordingly. The
sented in this study by the Test Reference
ble that the user will arrive to a cool home
system evaluated here, called “tado°”, has
Year (2004) for Munich [2]. To include the
if he comes back at an unexpected time.
been available since November 2012.
discrepancies between the forecast and
Therefore, the periods of presence have to
actual values, this study uses the deviations
be set generously in order for the home to
between the forecast for the town of
reliably be warm when the user is present.
Holzkirchen and the measured data from
As such, the evaluated system, with its
the institute’s own weather station. Based
automatic presence detection, really shows
on this data, an appropriate mathematical
its strengths when periods of presence
deviation model is developed. The study
are irregular. In this case, the temperature
uses the solar global radiation forecast
reduction times are adjusted to the actual
from the TRY data set, adjusted according
user and there is no need to assume longer
phone.
to this deviation model.
periods of use.
2 illustration of the tado° presence detection.
Heating energy need [kWh/(m²a)]
THE REFERENCE BUILDING
-26 %
120,8
-21 %
122,6
100
50
0
Unrefurbished building
Appartment
Single usage
Unrefurbisched building
Single family house
Family usage
1 tado° mobile App report function on a smart