UNCERTAINTY ANALYSIS OF COMMERCIAL BUILDING PERFORMANCE IN INDONESIA BY CONSIDERING CHANGES OF CLIMATE DATA

• Main Author: Rafi Azzami, Muhammad
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/79429
• Institution: Institut Teknologi Bandung

Building performance is an important factor in a building. Several countries in the world have set policies about high-performance buildings, including Indonesia. In designing a building that usually has a long life cycle, many challenges must be faced, including the uncertainty of climate data caused by climate change. Climate change has so many impacts on the building sector, which are marked by an increase of cooling energy demand and an increased risk of overheating. There are several strategies that can be implemented for, including the strategy in passive design of a building. The strategy in building passive design has been chosen because of its eco-friendly solution when designing a high performance building. Nevertheless, existing guidelines and standards for building performance commonly use historical climate data, so uncertainty of climate data has not been considered yet. Uncertainties of climate data will lead to calculation errors for building performance, so this has to be an important consideration when designing the building performance. Moreover, the long life cycle of a building requires that the building has to be designed to have a high performance, both in the present and in the future. Therefore, this research objective is to identify the changes of building performances in several scenarios of future climate data for optimized commercial building in Indonesia now.. In this research, modeling and simulation of the building performances of a commercial building are conducted using Rhinoceros 3D software with Grasshopper plug-in. Before that, inputs for modelling and simulation have to be defined. Those inputs are future climate data scenarios, geometry and construction of the building, building profile, building performance metrics resulted, and passive design parameters tested. The simulation results building performance metrics for each passive design which are tested in several future climate data scenarios. Then, the results of the simulation are analyzed to identify the changes in building performance metrics that caused by the uncertainty of climate data. The results show that all of building performance metrics that being considered have change, with the biggest change is 31.8% for the Energy Use Intensity metric. Then, robustness test is conducted for all design variations using minimax regret method. After that, all design variations are ranked based on the value of maximum regret for each design. So, five designs with the best rank in each metric and overall metrics are resulted. After that, correlation test between the passive design input parameter and resulted rank for each metric and overall metrics, resulting the order of passive design parameters that has to be changed first. The correlation test results that Window-to-Wall Ratio is the highest correlated parameter, followed by wall insulation thickness, roof insulation thickness, wall insulation conductivity, and roof insulation conductivity. Finally, the conducted analyses give the range of the recommended passive design value that robust for optimized building now in facing the uncertainty of climate data. The recommendations are: building orientation towards the south; wall material with low thermal mass; wall material thickness of 0.30 m, window type with low emissivity; WWR of 30%, infiltration of 0.33; wall insulation thickness of 0.14 m; roof insulation thickness of 0.04 m; wall insulation conductivity with range 0,11 W/m2·K; and roof insulation conductivity with range 0.28 W/m2·K ?