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Multi objective optimization of existing buildings: “A Study of a Higher Educational Laboratory in Cairo, Egypt”
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This research presents a comprehensive methodology for optimizing building performance in the context of visual and thermal comfort of a computer laboratory in higher educational buildings in hot dry climates, focuses on minimizing energy use intensity (EUI) and maximizing annual thermal comfort ratio and daylighting through maximizing useful daylighting illumination (UDI) and spatial daylighting Autonomy (sDA). This study conducts a parametric optimization approach of building envelope openings and materials to integrate multi-objective optimization (MOO), aiming to explore and find optimal solutions for improving the laboratory's overall performance. Throughout Rhino Grasshopper platform for simulation purpose. The methodology begins with the development of a parametric model of the computer laboratory, which allows for the manipulation of key design variables, including window size, Window wall ratio (WWR) orientation, shading devices, wall materials and properties, glazing types. These variables are used as design parameters linked to performance metrics that capture the visual comfort (via daylighting analysis), thermal comfort (evaluating indoor temperature variations and HVAC loads), and EUI (calculated through energy simulation). The design space is explored using multi-objective optimization by Genetic algorithms NSGAII with Wallacie solver, which balance trade-offs between the 124 key design parameters to enhance five objective functions performance criteria. The results show that significant improvements can be achieved in the computer laboratory’s visual and thermal comfort, while simultaneously reducing energy use intensity by around 2.35% maximizing (sDA) and (UDI) to 1.3%, maximizing annual thermal comfort ratio (ATCR) to 1.9%. The optimized solutions exhibit a balance between natural and artificial lighting, effective thermal insulation, and strategic shading. In some cases, up to a 26% reduction in energy consumption (EUI) is observed, with notable improvements in both daylight quality and occupant thermal satisfaction.
Title: Multi objective optimization of existing buildings: “A Study of a Higher Educational Laboratory in Cairo, Egypt”
Description:
This research presents a comprehensive methodology for optimizing building performance in the context of visual and thermal comfort of a computer laboratory in higher educational buildings in hot dry climates, focuses on minimizing energy use intensity (EUI) and maximizing annual thermal comfort ratio and daylighting through maximizing useful daylighting illumination (UDI) and spatial daylighting Autonomy (sDA).
This study conducts a parametric optimization approach of building envelope openings and materials to integrate multi-objective optimization (MOO), aiming to explore and find optimal solutions for improving the laboratory's overall performance.
Throughout Rhino Grasshopper platform for simulation purpose.
The methodology begins with the development of a parametric model of the computer laboratory, which allows for the manipulation of key design variables, including window size, Window wall ratio (WWR) orientation, shading devices, wall materials and properties, glazing types.
These variables are used as design parameters linked to performance metrics that capture the visual comfort (via daylighting analysis), thermal comfort (evaluating indoor temperature variations and HVAC loads), and EUI (calculated through energy simulation).
The design space is explored using multi-objective optimization by Genetic algorithms NSGAII with Wallacie solver, which balance trade-offs between the 124 key design parameters to enhance five objective functions performance criteria.
The results show that significant improvements can be achieved in the computer laboratory’s visual and thermal comfort, while simultaneously reducing energy use intensity by around 2.
35% maximizing (sDA) and (UDI) to 1.
3%, maximizing annual thermal comfort ratio (ATCR) to 1.
9%.
The optimized solutions exhibit a balance between natural and artificial lighting, effective thermal insulation, and strategic shading.
In some cases, up to a 26% reduction in energy consumption (EUI) is observed, with notable improvements in both daylight quality and occupant thermal satisfaction.
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