Mechanical ventilation – if present – was operated using a fix schedule, with margins of 1h before/after begin of work.
Illuminance comfort
Occupancy dependent, bright
Applied was a lower illuminance setpoint value for occupied offices of 500 lux. No upper limit was defined, assuming that in case of excess incoming solar radiation the user would be able to obtain glare protection by manual adjustment of an internal blind.
Mechanical ventilation – if present – was operated using a fix schedule, with margins of 1h before/after begin of work.
Illuminance comfort
Occupancy dependent, bright
Applied was a lower illuminance setpoint value for occupied offices of 500 lux. No upper limit was defined, assuming that in case of excess incoming solar radiation the user would be able to obtain glare protection by manual adjustment of an internal blind.
BACTool focuses on the exploration of so-called
"non-standardized" control solutions, i.e. solutions
where the control is being tailored to the given building,
combination of automated subsystems and user requirements by means
of corresponding programs that govern the behavior and interplay of
the individual subsystems. Building automation systems with
programmable controllers are typically used for that purpose.
Traditional programs are susbsumized under the term Rule-Based
Control (RBC). A promissing alternative that is currently
undergoing intensive research is co-called Model Predictive Control
(MPC). A brief introduction to RBC and MPC is given below. A more
in-depth discussion of the two approaches and a comprehensive list
of criteria for the evaluation of non-standardized control
solutions is given in [1] (in particular see the
Introduction therein).
All data presented in the BACTool are simulation results.
They were produced using the data and methods described in [1]. The simulations were based on a 12th order
multiple-input-multiple-output bilinear model of the coupled
thermal, light and air quality dynamics of a single room or
building zone. The model is used, firstly, as a "plant
model" to simulate the building zone's response to different control
algorithms. Secondly, the same model is also used as a
"controller model" for Model Predictive Control (see
below). Details on the model can be found in [2] and [5]. Each simulation
covered one year and employed a time step of one hour. The used
weather data sets are documented in [6].
Statistical analyses dealing with trends and patterns across a
large number of simulations are provided in [7],[8],[9],[10]. A more detailed
analysis of selected cases can be found in [8].
Control Algorithms
Rule-Based Control (RBC) determines the control inputs based
on a series of rules of the kind "if condition then
action". The conditions and actions typically involve
numerical parameters (e.g., threshold values), the so-called
control parameters. In BACTool they are determined from
building parameters based on carefully derived, automated
calculation procedures. The used RBC algorithms consist of a
high-level and a low-level part. The high-level part yields
operating modes that determine the "low-cost" actions
(blind positioning, free cooling operation, and energy recovery
operation). The low-level part determines, firstly, the control
actions for the "low-cost" action aggregates. In a
second step it calculates the remaining control outputs for
"high-cost" actions such as active heating or cooling,
and mechanical ventilation. The various RBC variants differ only
in their high-level parts. For further information see [3]
Model Predictive Control (MPC) relies upon a model of the
building that is used together with predictions of relevant
disturbances (e.g., weather, internal gains) to predict the
system's future evolution. At the beginning of each time step
(e.g., every hour) MPC computes the "best possible"
sequence of control actions that minimize a cost function (e.g.,
total energy demand) over a given prediction horizon (e.g., a few
days) while respecting comfort (e.g., illumination levels, room
temperature range) and any other (e.g., maximum power demand)
constraints. The control actions identified for the very first
time step within the prediction horizon are then applied to the
system, and the whole procedure is repeated at the beginning of the
next time step. This "receding horizon" approach ensures
that the control plan is continuously updated using the newest
information on the building's state, thus allowing to account for
model inaccuracies or any unknown disturbances that have meanwhile
acted on the building. See also [4].
The Performance Bound (PB) is a theoretical value that
presents the lowest achievable control cost (in terms of energy or
money) for a given building, cost function, disturbances (weather,
internal gains) and set of comfort requirements. The PB can be
estimated by applying Model Predictive Cnotrol (see below) over a
representative period (e.g., one year) assuming a perfect building
model, and perfect knowledge of all future disturbances. Knowledge
of the PB makes it possible to compare different design variants
for a given system net of any effects related to control.
Theoretical energy savings potential: By definition the PB
presents a theoretical number that can not be beaten by any real
controller. The difference between a real controller's energy
usage and the PB gives a measure of the maximum achievable
improvement for that controller. Nothing can be said about to what
extent the potential can be exploited by a feasible control.
However, the size of the potential indicates for what applications
further control strategy development may be promising.
PB: The PB calculation in BACTool uses a perfect
MPC model and perfectly known disturbances. The optimal
sequence of control inputs is therefore determined only once
every TOL = 48 h (2 d) using a prediction horizon of
TH = 144 h (6 d). The subscript "OL"
stands for "open loop" and this refers to the fact
that the control inputs during the 48 hours following an
optimization are precisely the ones delivered by this
optimization, i.e. during these 48 hours the control inputs are
directly applied to the plant model without any feedback to the
controller. Further information can be found in [7].
RBC-A: A typical, broadly applied, non-predictive
control strategy. Inputs for control are current measurements
of room temperature, outside air temperature, external heat
gains, and the occupancy state. Three blind transmission
values are considered: fully open, fully closed and shading
transmission. Blinds are repositioned depending on threshold
crossings for solar gains. For simulation this behavior is
approximated by setting the blinds for a given time step based
on the time step's average solar gains. This control strategy
correponds to the strategy "RBC-1" reported in [3].
RBC-B: A novel, non-predictive control strategy. The
controller inputs are the same as for RBC-A; in addition are
used historical heat and cold demand signals, and historical
room temperature data. Blind transmission varies continuously
between a minimum (blinds fully closed) and maximum (blinds
fully opened) value. Blinds are repositioned once per hour
(once per control step), based on the historical signals and
data. See control strategy "RBC-4" in [3].
Note, the set of subsystems actually controlled by a given control
algorithm depends on the currently chosen HVAC System variant.
Sites
Site Name
Latitude
Longitude
Elevation [m a.s.l.]
Annual Mean Temperature [°C]
Annual Mean Global Radiation [W/m2]
Zurich
47.4° N
8.6° E
556
9.3
125
Vienna
48.3° N
16.4° E
209
11.4
140
Lugano
46.0° N
9.0° E
273
12.7°
140
Marseille
43.4° N
5.2° E
5
15.3°
182
Internal Gains
The occupancy density of the building (a number ranging from 0-100%)
was used as the key quantity to determine the internal heat gains
from persons and equipment, plus CO2 production.
Considered were two internal gains levels based on the Swiss standard
SIA 2024 [11].
Parameter
Unit
Internal Gains Level
Low
High
Floor area per person
m2
14
7.8
Internal gains due to persons
W/m2
5
9
Internal gains due to equipment
W/m2
7
15
CO2 production
m3/h/m2
1.1e-3
1.9e-3
Diurnal and weekly variations in internal gains were obtained
from the Swiss standard SIA 2024 [11] for cellular
offices. During weekends no persons were assumed to be present and
the person gains were set to zero. The equipment gains were set to
the weekdays' night-time value.
Thermal Comfort
The used minimum and maximum room temperature set points for heating and
cooling were similar to the definitions in SIA 382/1 [12].
The actual range at a given point in time was determined as a
function of the exponentially weighted running mean of the past
measured outside air temperature values. The running mean was
calculated in a similar manner as described in EN 15251 [13]. The comfort settings were applied 24 hours a
day and 7 days a week.
References
Gyalistras, D. & Gwerder, M. (Eds.) (2010). Use of weather
and occupancy forecasts for optimal building climate control
(OptiControl): Two years progress report. Terrestrial Systems
Ecology ETH Zurich, Switzerland and Building Technologies
Division, Siemens Switzerland Ltd., Zug, Switzerland, 158 pp,
Appendices. ISBN 978-3-909386-37-6.
Lehmann, B., Wirth, K., Dorer, V., Frank, Th. & Gwerder, M.
(2010a). Control problem and experimental set-up. In
[1], Chapter 2, pp 15–28.
Gwerder, M., Tödtli, J. & Gyalistras, D. (2010).
Rule-based control strategies. In [1], Chapter 3,
pp 29–42.
Oldewurtel, F., Jones, C.N., Parisio, A. & Morari, M. (2010).
Model predictive control strategies. In [1],
Chapter 4, pp 43–58.
Lehmann, B., Wirth, K., Carl, S., Dorer, V., Frank, Th. &
Gwerder, M. (2010b). Modeling of buildings and building systems.
In [1], Chapter 5, pp 59–66.
Stauch, V., Schubiger, F. & Steiner, P. (2010). Local weather
forecasts and observations. In [1], Chapter 6, pp 67–78.
Gyalistras, D., Lehmann, B., Wirth, K., Gwerder, M.,
Oldewurtel, F. & Stauch, V. (2010). Performance bounds and
potential assessment. In [1], Chapter 7, pp 79–106.
Gyalistras, D., Wirth, K. & Lehmann, B. (2010). Analysis of
savings potentials and peak electricity demand. In [1],
Chapter 8, pp 107–134.
Gyalistras, D., Gwerder, M., Oldewurtel, F., Jones, C.N.,
Morari, M., Lehmann, B., Wirth, K., & Stauch, V. (2010).
Analysis of energy savings potentials for Integrated Room
Automation. Paper presented at the 10th REHVA World Congress
Clima 2010, 9-12 May 2010, Antalya, Turkey, 8pp.
Gwerder, M., Gyalistras, D., Oldewurtel, F., Lehmann, B.,
Wirth, K., Stauch, V. & Tödtli, J. (2010). Potential
assessment of rule-based control for Integrated Room
Automation. Paper presented at the 10th REHVA World Congress
Clima 2010, 9-12 May 2010, Antalya, Turkey, 8pp.
SIA 2024 (2006). Standard-Nutzungsbedingungen für die
Energie- und Gebäudetechnik, Raumnutzungen "Einzel-,
Gruppenbüro" und "Grossraumbüro", pp. 34-37.
SIA 382/1 (2007). Lüftungs- und Klimaanlagen –
Allgemeine Grundlagen und Anforderungen.
Standard EN 15251 (2007). Eingangsparameter für das
Raumklima zur Auslegung und Bewertung der Energieeffizienz von
Gebäuden – Raumluftqualität, Temperatur, Licht und Akustik.
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