Improved space heating in smart residential buildings by applying dynamic hydraulic balancing.
Teich, Tobias ; Szendrei, Danny ; Franke, Susan 等
Abstract: Through the hydraulic balancing of heating systems,
significant energy savings in residential buildings can be achieved.
These savings refer to (primary) heating energy, as well as to
(secondary) electric energy for the supporting building services. This
paper addresses the use of KNX-technology and networks (Smart Buildings)
in multi-storey residential buildings to ensure a dynamic adaption of
hydraulic system performance in order to increase the heating system
"s efficiency. In this paper the authors present the procedure of
heating system segmentation into hydraulically independent units
(meshes). Within these meshes, a dynamic hydraulic adaption towards
homogenous mass flow allocation is achieved by positioning the valve
ranges in each storey according to the current heating load via
installed valve drivers. The control procedures are conducted by a
central facility server algorithm. Heating loads are generated from the
digital temperature settings in all corresponding rooms. The evaluation
of current heat up demands enables maintaining hydraulic uniformity. In
this paper, standards, requirements and determinants of the control
algorithm are presented
Key words: energy-efficiency, space heating, dynamic hydraulic
balance, building automation
1. INTRODUCTION
One of today's most challenging, global problem is providing
clean and sufficient energy for increasing industrial and residential
demands. Industry and service companies try to meet these developments
with so called "green solutions". Facility management,
especially in the residential housing sector, can contribute large
potentials to increase energy efficiency. A share of about 70% of the
overall energy consumption is used for heating systems. Invests in high
efficient heat generators are deferred especially in the residential
housing sector. Next to heat generation, the probabilities of energy
savings in heat distribution systems are not used adequately. In the
future, the importance of hydraulic balanced systems is expected to
increase, due to tightened legal restrictions (German Ministry Of
Justice, 2007). The current dispute about the public energy concept
forces facility management to accelerate its efforts in energetic
reconstruction of buildings (German Ministry For Environmental
Protection, 2010).
Conventional distribution systems, such as the
double-pipe-networks, are technically mature and of high durability.
Still, there are opportunities for energy savings in about 90% of all
operated heating systems. This is caused by the missing hydraulic
balance within those systems. The after-effects are delayed heating over
the building, variable hydraulic conditions, increasing energy
consumption (primary and secondary energy) and disturbing floating
noises. In simulations, Felsmann and Hirschberg, 2007 found, that
hydraulically imbalanced buildings cause 8% higher mass-flow-turnover
than optimized buildings. This additional turnover results in 25% higher
electrical energy demand for the circulation pumps. One major influence
on energy consumption is caused by false hydraulic allocation.
KNX-technology enables controlling local networks in a variety of
functions (power distribution, heating control, security installation
and others). The KNX (Konnex) standard enables secure operation of
various appliances on the platform of the European Installation Bus
(EIB). Current room temperature control systems anticipate many
environmental parameters and self-adjust heat generator settings as well
as heating valve settings within the rooms. Caused by numerous,
temperature settings through the users, the hydraulic conditions within
a single pipe vary and influence the proper hydraulic supply of
remaining heating devices within the same line (Yao et. al., 2005).
Conventional measures of hydraulic balance (static) fail to compensate
dynamic changes of difference pressure, caused by the named reason in
most conditions. Via valve drivers on each heating device and the
intelligent integration of the drivers in bus structures, the valve
settings can be used to compensate these dynamics. As far as the
hydraulic specifications (i.e. difference pressures throughout all
working conditions, characteristic diagrams of heating valves, valve
driver positions) of the pipes are known, the valve positioning can be
controlled by a central facility server application. Thus, different
load scenarios of the heating system can be considered in the
controlling algorithms for each room in a specific pipe and dynamic
hydraulic balance can be performed.
2. REQUIREMENTS AND DETERMINANTS OF THE SPACE HEATING SYSTEM
2.1 Building Services (BS) Standards
Smart home infrastructures or holistic control systems have not
been installed in most multi-storey dwellings (Teich et. al., 2010). So
far, most installations and their control systems have been conducted by
companies of different crafts or branches. Integrative control
procedures were hard to achieve that way. In the field of heating,
integrative building control was impossible to maintain, due to the
named reasons.
Heat transmission systems and their control are structured
according to the dwelling units of the buildings (Liu et. al.,2010). Due
to heterogeneous heat allocation (mass flow), most heating systems work
inefficiently (Szendrei, 2010). This effect appears most notably in
large heating systems (Felsmann & Hirschberg, 2007). Most
residential buildings are -equipped with central heating systems (Guzek,
2010). Rising pipes supply the corresponding heating devices with mass
flow of water and represent a single mesh. Within a mesh, the hydraulic
conditions vary according to mesh-distance to circulation pump, storey
height, installed system components and user settings. Beside physical
influences of the building (hull damping, internal heat transmission
etc.), user settings determine the primary energy demand significantly
(Baopin et. al., 2009, Liu et. al., 2010). Hydraulic balancing of the
heating ensures efficient heat distribution. Still, there are about 90%
of all operated systems, where such measures have not been conducted
(Guzek, 2010). Standard procedures of hydraulic balancing cover
hydro-static adjustments for heating loads under extreme circumstances
(full load). In this condition, the proper mass flow distribution can be
obtained throughout the system by adjusting proper hydraulic resistance
at the heating valves. In that case, every opened valve enables a
homogeneous heat supply of all heating devices.
2.2 KNX-integrated Building Services
In about 95% of the heating season, significantly smaller mass
flows have to be circulated by the pumps. (Zou, 2008). The mass flow is
object to dynamic user settings. Accordingly, the statically adjusted
resistances become out of tolerance and do not ensure homogeneous mass
flows.
In the mesh-configuration however, physical determinants of the
hydraulic components have to be considered. For each rising pipe/mesh,
calculations of:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (1)
and
[DELTA]p mesh = [summation](R x l) - [summation] ([zeta] x [rho] x
[[omega].sup.2]/2) (2)
are to be performed. With these information, different load
scenarios can be modelled and deposited for facility server
applications, as table 1 illustrates:
According to heating demand in the meshes, valve ranges can be
tuned in to dynamically balance the meshes mass flow and ensuring
adequate heat supply. The implementation of this control requires
accurately working valve drivers. Valve positions represent specific
flow rates. Sufficient drivers are to be found among KNX-based,
continuously controlled drivers (Szendrei, 2011). The valve position is
continuous-controlled by addressing the drivers via KNX-bus. This
procedure integrates the heat utilisation and loads of whole facilities
and effects hydraulic uniformity positively.
3. RESULTS
Two residential facilities have been equipped with an entire KNX
infrastructure for heating and appliance control. The topology of the
dwellings was configured with the ETS. The whole structure of all
relevant building services, however, is deposited.
With the value requests by the application FacilityManager, the
single room temperature control could be accomplished. The proposed
control-sequence achieves hydraulic uniformity over and in between the
meshes. Additionally, the aggregation of heat up demands (intensity of
required heat up load) indicates a potential for reducing forward-motion
temperatures in near field heating. This analysis is part of further
research. First evaluations of the convergency of actual and set
temperature values indicate a uniform heat-up of the dwellings within
the meshes. According to user interviews, a more comfortable heat-up of
the rooms is achieved by now.
The electrical power consumption of circulation pumps could be
reduced by 6% in comparison to similar systems. As an indicator, the
called revolution per minute rate was compared against pumps in
imbalanced systems.
4. REFERENCES
Baopin, X.; Fu, L. & Hongfa, D. (2009). Field investigation on
consumer behavior and hydraulic performance of a district heating system
in Tianjin, China. Building and Environment, Vol. 44, Issue 2, 249-259,
ISSN 0360-1323
Felsmann, C. and Hirschberg, R. (2007). Das Rohrnetz in
Heizungsanlagen:eine Analyse des Teillastverhaltens und der Effizienz
von Rohrnetzen. VDI-Verlag, ISBN 978-3183155194, Dusseldorf
Guzek, G. (2010). Zur Energieeinsparung in Heizungsanlagen durch
den hydraulischen Abgleich. TUD-Verlag, ISBN 978-3941298590, Dresden
Liu, L.; Fu, L., Jiang, Y. & Gou, S. (2010).Maintaining uniform
hydraulic conditions with intelligent on-off regulation. Building and
Environment, Vol. 45, Issue 12,2817-2822, ISSN 0360-1323
Szendrei, D. (2011). Feasibility of integrating heating valve
drivers with KNX-standard for performing dynamic hydraulic balance in
domestic buildings. Proceedings of World Academy Of Science, Engineering
And Technology. International Conference on Electrical Power and Energy
Systems 2011, Dubai, VAE, eISSN 2010-3778
Teich, T., Zimmermann, M. and Other. (2010). Intelligent Building
Automation. In Karras, D.A., Moustafa K.A.F., Tang, D. (ed.),
International Conference on Automation, Robotics and Control Systems.
53-57. ISRST. Orlando, Florida
Zou, Y. (2008).Unstetige Warmeversorgung im Mehrfamilienhaus.
Universitatsverlag Karlsruhe, 978-3866443648, Karlsruhe
Tab. 1. possible heating load profiles
decision variable
value (HD) for heat
in demand valve range R [%]
ground 1st 2nd R_GF R_1st R_2nd
floor floor floor
0 0 0 0 0 0
0 0 1 0 0 100
0 1 0 0 100 0
0 1 1 0 75 100
1 0 0 100 0 0
1 0 1 75 0 100
1 1 0 75 100 0
1 1 1 65 75 100
