The significance of using local predicted temperature for cooling load simulation in the tropics

摘要

In building energy simulation, researchers commonly use weather data obtained from the software database or (meteorological) MET station. However, this method leads to disparity of urban-rural temperature condition, hence the input weather data do not characterize the on-site condition. This paper highlights the importance of generating and implementing the urbanized weather data, primarily on the ambient temperature. A parametric approach was used to create hundreds urban layouts of the hypothetical office block plan. An annual temperature profile was generated for each scenario using the Screening Tool for Estate Environment Evaluation (STEVE) tool. It was found that the local average temperature (T-avg) and peak afternoon period (T-max) from these scenarios could differ 1-2 degrees C and 1.2-3.5 degrees C respectively as compared to the MET station data. Using Integrated Environmental Solutions (IES) to simulate the thermal load performance, this temperature difference can lead to an approximately 8% difference in the predicted cooling load, 20% in external conduction gain, and 17% in fresh air intake gain. These numbers can be deemed substantial in simulating building performance, especially cooling load due to changes in the external condition. Furthermore, the comparison proves to be significant in term of enhancing the simulation result and representing the studied area. (C) 2016 Elsevier B.V. All rights reserved.