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After modeling the
zones and windows, the next step was to evaluate the performance of annual
energy consumption and lighting which two standards UDI and EUI were applied in
this regard.


Useful Daylight Illuminance

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Simulation was performed using the Honeybee V
0.0.56, a plug-in for Grasshopper modeling software. It was used to interface
Radiance and Daysim for an­nual simulation and illuminance computation (Ladybug plugin 2012). Analysis was carried out by
making use of Useful Daylight Illuminance metric (UDI) developed by Nabil and
Mardaljevic (Nabil
and Mardaljevic 2006).
The UDI measures how often the daylight on the working plane is within a
specific illuminance range. The aim of this research is to achieve the
percentage of working hours during the year in which the daylight illuminance
level within the space is between 100 and 2000 lux. This limits were chosen
according to occupant behaviors in daylit offices with user-operated shading
devices (konis
2012) and used as the threshold
criteria for the UDI. In this threshold spaces with illuminance lower than 100
lux are below useful illuminance and needed for
artificial lighting sources and spaces with illuminance higher than 2000 lux
are a proxy indicator for glare.

Simulation was conducted an­nually for
weekdays from 8:00 AM to 4:00 PM which represents a typical Iranian eight-hour
working time. The reference plane on which daylight performance was simulated
is a grid of 0.5m* 0.5m, at a working plane of height 0.8 m. A set of parameters were defined to specify the type of
simulation and outputs. In the final step epw weather file for Tabriz was used
to run the simulation.


Energy Use Intensity

Among the existing energy simulation tools,
Honeybee was chosen to perform the evaluation of the building energy need. It performs
calculations of thermal behaviors using the validated Energy Plus simulation
program. It allows annual climate-based simulation outcomes informed from
hourly weather data. In this study the annual energy demand of a building for
heating (EH), cooling and (EC), and lighting (EL) were considered. The method
used is similar the daylight analysis with the difference that the calculations
of energy demand was applied. In order to reduce the energy need for cooling an
additional simulation was performed that incorporates the benefits of natural
ventilation through windows. This simulation consists of using design geometry
and climate data to estimate the periods during the year where natural
ventilation could meet the cooling demands of the indoor space. The settings
are based on minimum and maximum indoor and outdoor temperatures (Table 1).

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