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Energy Optimization

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Grasshopper which is integrated with Rhino’s 3-D modeling tools is a graphical algorithm editor for designers exploring various shapes by using generative algorithms (Grasshopper® software 2007). with its algorithmic capabilities, Grasshopper enables the creation of utilities that go beyond the common palette of commands of Rhino. In this research, in order to explore the energy usage and daylight, the Ladybug and Honeybee were utilized which are an open source environmental plug-in for Grasshopper-3D. These plug-ins import standard Energy Plus Weather files (EPW), Radiance, Daysim and Open Studio into Grasshopper and provides a variety of 3D interactive graphics to support the decision-making process during the initial stages of design (Ladybug plugin 2012). The optimization process was carried out by Octopus which is a plug-in for applying evolutionary principles to parametric design and problem solving (Octopus plugin 2012).

Pre-settings for simulations

Geographic location, climate

Tabriz has a semi-arid climate with regular seasons (Köppen BSk). The annual precipitation is around 280 millimeters, a good deal of which falls as snow during the winter months and rain in spring and autumn. Tabriz City is located at (38°04’48” N, 46°17’30” E). averaged value of sunshine is 2616.9 hrs (January 2000- December 2016) and averaged value of frost days (Every day in a year with the lowest temperature below freezing level (0°C / 32 °F) is 81.8 days (Weather online 2016).

Building geometry

In this paper in order to explore the capabilities of the proposed approach, Tabriz municipality office building was selected, which is set at a north-south orientation, and it is a rectangle-shaped office building including 6 floors plus a dome which was not evaluated in the process of this research. The three-dimensional view and plan of the building model are shown in Fig. 1. each floor is divided into 18 perimeter zones and one core zone. The typical floors (from 1 to 5) are simulated with one representative floor and is multiplied to represent other typical floors. The approach for performing the simulations includes the fenestration analysis in order to determine the optimal fenestration due to the energy efficiency of the building. In this process, the evaluation of fenestration was performed separately for each zone. Each modeled zone is adjacent to the facade to assess the annual thermal and lighting conditions produced by the facade region. The plan of zones N2 and N3 at floor 5th are resized, so simulations for these two zones have done separately.

The first phase of the process consists of modeling the building and the zone/s that will be simulated. This phase is subdivided in two different parts: modeling the geometry of the building, modeling the fenestration patterns. For the case study, the basic floor plate of the building was modeled in the form of a polyline and was extruded in order to obtain the 3D model of the building. The parameters that were used to model the building and its zones were the orientation, number of floors, floor-to-floor height, thickness of the roof structure, and rooms (zones). The parameters for simulating windows were window to wall ratio, window height, number of windows and sill height which were modeled by honeybee glazing components.

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Energy optimization. (2018, December 03). GradesFixer. Retrieved October 19, 2021, from
“Energy optimization.” GradesFixer, 03 Dec. 2018,
Energy optimization. [online]. Available at: <> [Accessed 19 Oct. 2021].
Energy optimization [Internet]. GradesFixer. 2018 Dec 03 [cited 2021 Oct 19]. Available from:
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