OPTIMIZATION OF BUILDING ENERGY PERFORMANCE THROUGH COMPUTATIONAL DESIGN AND SIMULATION

Optimizing the energy performance of buildings is crucial for achieving sustainability, reducing energy consumption, and mitigating the impact on the environment. Traditional design approaches often rely on simplified calculations and rules of thumb, which may result in suboptimal energy performance. This abstract presents a comprehensive framework for optimizing building energy performance through computational design and simulation. The proposed framework integrates advanced computational tools, such as parametric modelling, simulation software, and optimization algorithms, to enable a data-driven and iterative design process. It involves creating a parametric model of the building that captures its geometry, materials, and systems, allowing for rapid exploration of different design options. Simulation software is then utilized to assess the energy performance of each design variant under various operating conditions and climate scenarios. To optimize the building energy performance, optimization algorithms are employed to search for the optimal design parameters that minimize energy consumption while meeting specific performance criteria. These algorithms consider multiple design variables, such as building orientation, envelope insulation, glazing properties, HVAC system configuration, and renewable energy integration. The optimization process aims to find the most energy-efficient design that balances the trade-offs between energy consumption, occupant comfort, and economic feasibility. The use of computational design and simulation offers several advantages. It enables designers and architects to evaluate numerous design alternatives quickly, considering a wide range of parameters and constraints. The integration of simulation tools provides accurate predictions of energy performance, allowing for informed decision-making during the design phase. The optimization process optimizes the building's energy performance, resulting in improved energy efficiency, reduced operational costs, and enhanced occupant comfort. Case studies are presented to illustrate the effectiveness of the proposed framework. These studies involve optimizing different building types, such as residential, commercial, and institutional buildings, considering various climatic conditions and energy goals. The results demonstrate significant energy savings achieved through the optimization process, highlighting the potential for computational design and simulation in enhancing building energy performance. The application of this framework has important implications for the design and construction industry. By integrating computational tools, architects and engineers can optimize building energy performance from the early design stages, leading to more sustainable and energy-efficient buildings. The framework supports informed decision-making, facilitates collaboration among project and contributes to achieving energy reduction targets and environmental sustainability goals. A comprehensive framework for optimizing building energy performance through computational design and simulation. By leveraging advanced tools and optimization algorithms, the proposed approach enables the exploration of design alternatives, accurate prediction of energy performance, and identification of optimal design solutions. The results demonstrate the potential for significant energy savings and improved sustainability in the built environment