Enhancing public building energy efficiency using the response surface method: An optimal design approach

摘要

Today, energy problems are becoming increasingly serious. The direct energy consumption of buildings accounts for 20% of the total energy consumption in a country. There are difficulties in continuing the mode of high energy consumption in the traditional construction industry. Therefore, the future of construction is in the development of green buildings. In the life cycle of a building, the consumption during the construction phase accounts for only approximately 20% of the total energy consumption. Most of the consumption occurs during buildings operations, such as lighting, heating, air conditioning and the running of various electrical appliances. Therefore, this paper focuses on the energy consumed during the building operation period with the aim of optimizing relevant design parameters to reduce total energy consumption. The West Twelfth Teaching Building (WTTB) of Huazhong University of Science & Technology (HUST) is used as a prototype, and Design Builder is used to establish a model of energy consumption and validate the reliability of the model based on the data obtained from the investigation. Based on this model, the study takes the perspective of energy conservation to analyze ten factors that may affect the energy consumption of the building: the heat transfer coefficient of the roof, the amount of fresh air, the heat transfer coefficient of interior walls, the heat transfer coefficient of the floors, the interior temperature, the energy efficiency ratio of the air conditioner, the thickness of the outer wall insulation, the ratio of windows to walls, the natural ventilation starting temperature and the solar heat gain coefficient of the outer windows. Those factors are then ranked according to their energy-saving potential through partial factorial design tests. The six factors with the most potential for energy savings are selected and divided into 2 groups to conduct a response surface optimization analysis of three factors at three levels. The best level of each factor and the optimal combination of all factors are obtained to reduce building energy consumption to the greatest possible extent and to provide a reference for teaching buildings and similar public buildings (PBs) in achieving the goal of "green building."