Uploaded by Kelvin Liadi

CIB DC28305

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ISBN: 978-84-697-1815-5
Importance of orientation in building energy-savings
Speakers:
Ramos Ruiz, G.1; Fernández Bandera, C.2
1
University of Navarra, Department of Building Construction, Services and Structures,
School of Architecture, Pamplona, Spain
2
University of Navarra, Department of Building Construction, Services and Structures,
School of Architecture, Pamplona, Spain
Abstract: In the design of new buildings, project energy efficiency is nowadays one of the
most important parameters on its development. The energy crisis on which we live and the
greater social awareness have allowed efficiency be a major factor when we are thinking in a
new building solution. This search for efficiency must be supported by studies to quantify
these improvements. With this information we can assess which one of the different solutions
is the best.
The building sustainability is closely related to building efficiency. The present analysis
shows through a semi-attached house, the importance of building orientation in heating and
cooling demands. With this knowledge we can choose the orientation with low energy
consumption.
Keywords: Energy efficiency, simulation, orientation, BEM, energy-saving, sustainability.
1
INTRODUCTION
Generally building orientation has been decided by the influence of views, prevailing winds,
housing layouts, site topography, nearby buildings, etc. Other times urban planning depends
on older planning, road existing layout, which purpose is ease of execution, road camber, etc.
Unfortunately sometimes the design of buildings doesn’t consider the energy-savings of this
energy efficient factor (orientation). Take into account prevailing winds to design building
layout to make cross ventilation, or rotate the building to have solar gains in winter are
restricted by above reasons.
Nowadays the new simulation programs shows easily and quickly the influence of these
factors in building energy demands. Today are real design tools that after comparative
analysis show us energy behaviors that aren’t a priory obvious.
The orientation of house layout affects its energy demand, because varies how much influence
has other factors like incident radiation, wind exposure, etc. For example a window opening
west-facing will have more solar gains in the afternoon, and this one will be greater in
summer than in winter because it has more hours of sun exposure. The same window opening
south-facing will have more solar gains in winter than in summer due to solar zenith angle
although solar radiation intensity be greater in summer than in winter. Relative to wind,
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façades with openings facing prevailing winds have more infiltrations due to high wind
pressure.
This paper analyzes one type of house, in particular a semi-attached house, because it is fairly
generalized in the surroundings of Spain capitals. To give more variability, three different
houses was made with different window opening percentages. The increase in window
openings is proportional to the initial opening. The different percentages simulated are 10%,
15% and 20% (this percentage refers to the total area of the façade). In case 1, 10% of the
façade are window openings; in case 2, 15%; and in case 3, 20%. In each simulation, housing
has been rotated 15 degrees which has allowed knowing the optimal orientation and the
different amount of energy between the worst and the best orientations. With this information
we can determine the energy-savings that we can obtain if the building is correctly oriented.
2
GENERAL CONSIDERATIONS
The following describes each one of the aspects have been taken into account when
performing both simulations and analysis.
2.1.
SIMULATION PROGRAMS
For the development of building energy model (BEM), OpenStudio 1.3.0 software has been
used. This program has been developed by NREL (National Renewable Energy Laboratory).
It is a graphical interface that allows users to create the building envelope taking into account
all different input parameters that define it. Moreover this software has the possibility to
analyze the simulation results graphically. The calculation engine of this tool is EnergyPlus
software.
After the model was developed, the simulations have been made with EnergyPlus software
8.1.009. This software is a whole building energy simulation program use to model energy
and water use in building. “Enable building professionals to optimize the building design to
use less energy and water.” It has been developed by U. S. Department of Energy (DOE).
“EnergyPlus models heating, cooling, lighting, ventilation, other energy flows, and water
use.” Enable to obtain information relative to building behavior (indoor space temperature,
loads, heating and cooling demands, etc.). It has passed the verification and validation test of
IEA BESTEST procedure (developed in conjunction with the International Energy Agency
(IEA) Solar Heating and Cooling Programme (SHC)).
2.2.
WEATHER DATA
The choice of weather database to do the simulations is a very important aspect (Ramos. G,
Fernández C., 2013). For this analysis, Meteonorm 7 database was used. This software
generates weather files in many different formats using the data of the weather stations or
interpolated them if don’t have a particular location. For generating results, the program has
different options to establish the typical year that be more closely to the real year. About
temperatures we can choose between different settings 1961-1990, 2000-2009, or future
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years; and about solar radiation between 1981-1990, 1986-2005, or future years. Solar
radiation measurements also can be corrected, add atmospheric turbidity, calculate radiation
data on surfaces with different degrees tilt angle, etc. The simulations of this analysis use the
original values of the weather stations, without any changes, choosing temperatures values
between 2000-2009 years and about solar radiation between 1986-2005 years.
One of the reasons for choosing this weather database is that the existing database on
EnergyPlus web doesn’t have values of wind velocity and wind direction (the values of wind
direction are constant – 0 degrees – and wind velocity 6.4 m/s). Meteonorm database has
different hourly values for wind. These aspects have a great influence on infiltrations, and
thus in heating and cooling consumptions.
2.3.
SEMI-ATTACHED HOUSE DESCRIPTION
The chosen semi-attached house has a surface of 460.92 m2. A “semi” is a house that is joined
to another house, so has one sidewall in common with the other house. It has been considered
as a whole so all the envelopes are exterior, enhancing the impact of climate and orientation
(figure 1 & 2). The envelope is made of facing bricks and has been considered 5 cm of
insulation (Expanded Polystyrene - EPS).
These types of houses have a very marked directionality due to the size and position of
window openings. There are two façades with great prominence, the main façade (facing the
street), and the rear façade (facing the garden). The other two are a sidewall linking with the
other house and a very opaque façade. This distribution of window openings makes the
influence of orientation be greater than if we had a more uniform distribution.
Fig. 1.- Layout of the semi-attached house under study
2.4.
Fig 2.- Semi-attached house OpenStudio Render
SIMULATION PARAMETERS
In the simulation there are many aspects to take into account: heating and cooling set point
temperatures, use schedules, people activity levels, internal loads, lights, equipment (TV,
computers, fridge, etc.). There are many different criteria to define each one, so it has been
decided to choose the normalized residential use profile of the new Spain code CTE-DB-HE
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(“Código Técnico de la Edificación, Documento Básico HE – Ahorro de Energía” September 2013). The following describes each one of these aspects.
Housing occupancy: Weekdays from 0:00h to 7:00h and from 23:00h to 0:00h the occupancy
is 100%; from 7:00h to 15:00h, is 25%; and from 15:00h to 23:00h is 50%. On weekends the
occupancy is 100%. It has been considered that 12 people live in the houses whose load is 90
W/person.
Equipment: The use of these equipment is 20% from 0:00h to 7:00h, 50% from 7:00h to
23:00h, and 100% from 23:00h to 24:00h. The loads of these equipment are 2.2 W/m2.
Lights: The use of these lights is 20% from 0:00h to 7:00h, is 50% from 7:00h to 23:00h, and
100% from 23:00h to 24:00h. The loads of these lights are 2.2 W/m2.
Infiltrations: It is the flow of outdoor air into a building from outside unintentionally. There
are mainly due to shutter boxes, windows sealing (window, frame and divider), kitchen and
bathrooms vents, cracks in the building envelope, etc. It depends on wind velocity, pressure
and depression between the main and the rear façade, building airtightness, etc. It is measured
in air changes per hour (ACH). It has been considered the values established in “Condiciones
de Aceptación de Procedimientos Alternativos a LIDER y CALENER”, these rate is 0,3 ACH
for detached houses.
Ventilation: It is intentional introduction of air from the outside into a building. It is further
subdivided into natural and mechanical ventilation. The document sets a value of 4 ACH from
0:00h to 8:00h in summer (it supposed that the windows are open), and for all other cases
refers to the Spain code CTE-DB-HS3. The rate of ventilation in this case is 0,63 ACH.
Cooling set point temperature: (summer) (from June to September). The set point is 27ºC
from 23:00h to 7:00h, and 25ºC from 15:00h to 23:00h. It is supposed that from 7:00h to
15:00h the house is empty and unused, so doesn’t have cooling set point. Nowadays due to
the actual economic situation, the possibility that these houses be in use are high.
Heating set point temperature: (winter) (from January to May and from October to
December). The set point is 17ºC from 23:00h to 7:00h, and 20ºC from 7:00h to 23:00h.
3
METHODOLOGY
The EnergyPlus model generated in OpenStudio take into account all considerations
described above. A parametric study has been made with the simulations of the three different
energy models (10% window openings, 15%, and 20%), in 52 capitals of Spain, and in 24
different orientations (between 0º and 360º range, in 15º intervals). The simulations have been
made with ideal loads that supposed an HVAC (heating, ventilation and air conditioning)
performance of 100%. This is a comparative analysis and we are interested in the influence of
orientation and not in the behavior of HVAC equipment. This analysis compares the outputs
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of these simulations (3744 cases), particularly the heating and cooling demands in
kWh/m2/year.
Fig. 3.- Orientation of the building
(Each value is North direction)
Fig. 4.- Correlation between degrees of orientations and the
orientation of the main and rear façade
Also, a sensitive analysis has been made to view the importance that orientation have in the
building energy consumption (Robertson, J., Polly, B., & Collis, J., 2013). Figure 3 explains
the meaning of each simulated orientations. Each value is North direction, and the main
façade is the largest. Figure 4 shows the correspondence of main and rear façade with
orientation. There is a little difference between them, because the main façade has smaller
openings than rear façade (60%). The rear façade have the greatest window opening surface
of the building.
4
RESULTS ANALYSIS
Figure 5 shows summary graphs of the obtained outputs of simulations. From top to bottom
are sorted by latitude the different cities of Spain. High latitudes are on top (Santander,
Oviedo …) and low latitudes on bottom (… Tenerife, Gran Canaria). From left to right are
sorted by the percentage of energy difference existing with different orientations in 15º
intervals (0º left side to 345º right side). For better clarity (due to the size of graphs), cells in
deep red represent the orientation of the greater values of heating demand, and in deep blue
the cooling demand. Cells in light red and blue represent the values with lower heating and
cooling demands respectively.
Figure 6 shows the relation between the orientation in which the maximum and minimum
energy demands have been produced, and the number of corresponding cities. From the center
of the circle to the edge is the number of cities (0-52). Each of radii of the circle represents the
North direction angle. The selected color code to distinguish each one of the demands is the
same than in figure above.
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10% openings
15% openings
20% openings
Fig. 5.- Perceptual difference in energy consumption with different orientations
As can be observed in the various graphs, in all cases when the main façade is South-West
facing (between 60º to 75º) the maximum heating demands occur, and if it is North-East
facing (between 255º to 270º) occurs the maximum cooling demand. The optimal orientation
for this kind of building, with minimum heating and cooling demands, are when the main
façade is North facing (between 165º to 195º) (remember that the rear façade has more
opening windows surface than the other ones). With 20% of window surface, the optimal
orientation for cooling is 0º. The reason of this change is that as we increase the size of
windows, the rear façade (with the biggest windows) need more cooling to reach the assigned
set point. However the difference with 165º to 195º is really low.
The reduction in heating demand occurs when façade with big openings is South facing (rear
façade with 180º). In winter and in this latitude, the sun is low in the sky and the building has
more solar gains. In summer, the optimal orientation matches with winter orientation because
in these months the sun is high in the sky and has lower cooling demands. Keep in mind that
the simulated building has cantilever slabs in the main and rear façade, so in summer these
slabs are like sunscreens that project shades on the façade and thus reduces the cooling
demand.
Nonetheless the difference between the maximum and minimum energy demand in
kWh/m2/year is very low. Statistically, for 10% opening case the second quartile is 2.57
kWh/m2/year; for 15% opening case is 3.59 kWh/m2/year; and for 20% opening case is 4.71
kWh/m2/year. Its sensitive coefficients are 0.123 for cooling and 0.0175 for heating in 10%
opening case; 0.128 for cooling and 0.026 for heating in 15% opening case; and 0.145 for
cooling and 0.0368 for heating in 20% opening case. This indicates that although the
orientation it is a factor to consider if energy saving is the objective, its influence on the total
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energy demand is not as important as other factors (infiltrations, thermal inertia, insulations,
etc.)
10% openings
15% openings
20% openings
Render with shadows of the rear façade (180º - July)
Fig. 6.- Relation between different orientations
Is noteworthy that for Spanish latitudes there is no difference in the optimal orientation when
changes the location. For this particular case all the optimal orientations are the same.
5
CONCLUSIONS
After analyzing the results it can be concluded that for the case of semi-attached houses, with
high sizes of windows in the main and rear façade, the optimal orientation to obtain lower
heating and cooling demands occurs when the façade with bigger windows is South facing
(obviously with sunscreens for summer).
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This optimal orientation is fulfilled in all Spanish territory. The reason is the low latitude
variability in Iberian Peninsula. For this reason, after this analysis it has been simulated the
same cases in the 28 capitals of the European member countries, with the same orientations
and sizes of window openings (2016 simulations). The obtained results do not differ
significantly from the ones obtained in Spain simulations. Although the optimal orientation of
the cities with high latitudes is displaced to 195º-210º (façade with bigger windows is SouthWest facing). The orientations with maximum demand values are similar to Spain case, but
with higher latitudes than 53º North there is a high dispersion of results.
Finally, although the building orientation is not a determining factor in the design of buildings
(due to the low energy savings), take into account these orientations allow us to have low
energy consumptions to reach thermal comfort.
6
BIBLIOGRAPHY
Ruiz, G. R., & Bandera, C. F. (2013). Importancia del clima en la simulación energética de
edificios. In Jornadas internacionales de investigación en construcción. Vivienda: pasado,
presente y futuro: resúmenes y actas. Instituto Eduardo Torroja.
Ministerio de Industria, Turismo y Comercio (2009). Condiciones de aceptación de
procedimientos alternativos a LIDER y CALENER. Anexos. Madrid. IDAE, Serie
“Calificación de Eficiencia Energética de Edificios”, nº9
de la Edificación, C. T. (2013). Documento Básico HE Ahorro de Energía. BOE 12/09/2013 –
corrección errores BOE 08/11/2013.
Robertson, J., Polly, B., & Collis, J. (2013). Evaluation of Automated Model Calibration
Techniques for Residential Building Energy Simulation.
Tian, W. (2013). A review of sensitivity analysis methods in building energy analysis.
Renewable and Sustainable Energy Reviews, 20, 411-419.
Saltelli, A., Tarantola, S., Campolongo, F., & Ratto, M. (2004). Sensitivity analysis in
practice: a guide to assessing scientific models. John Wiley & Sons.
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