Abstract
Climatic zoning for building energy efficiency applications has important implications in the global energy policy scenario. However, most of the climatic zoning methods currently used are based on few parameters, leading to an oversimplification and ignoring several aspects that are essential for building energy efficiency. In such a context, reliable methods for climatic zoning validation become a key concern. Nevertheless, little is known about this subject. A recent study introduced a procedure to address this gap, as part of the postdoctoral research project currently developed at UNICAMP. The procedure is based on the principle that two areas should belong to the same climatic zoning if building performances are similar in both areas, considering a set of archetype buildings. The procedure is based on building performance simulation results concerning the building stock that is targeted in the climatic zoning policy or program. Simulation results are used to calculate a new index, the Mean Percentage of Misclassified Areas (MPMA), which assesses the quality of the zoning under analysis. The capabilities of this procedure were demonstrated by the evaluation of four alternatives for the climatic zoning of Nicaragua, obtained using different methodologies and previously reported in the literature. This study demonstrated that the MPMA is useful for highlighting qualities and deficiencies of existing climatic zoning methods, particularly when these methods are used in less conventional applications, such as for policy making targeting naturally ventilated dwellings in tropical climates. However, further research is needed to optimize the effectiveness and robustness of this method when apply to more complex scenarios. In that context, the aim of this study is to provide objective confidence levels of the performance-based validation of climatic zoning while using a wide range of building archetypes in complex scenarios. As the validation process is quite complex, this study is particularly focused on the production of performance data through simulation for all data points in space for all buildings and all Performance Indicators. This procedure couples programming, building energy simulation and high-performance computing. This research is complementary to another study in which geographic information systems (GIS) and programming will be coupled to calculate the MPMA. This stage is under development in the ongoing postdoctoral research at UNICAMP and will be concluded in a first stage BEPE at the University of Strathclyde in Glasgow. In the present study, we explore many aspects regarding the appropriateness of climatic zones in a complex case study. Such as the ranges of performance variations in the zones (acceptable variations within the zoning), zoning resolution (number of zones), definition of zone boundaries under uncertainty and its implications in policy-making. For this purpose, the ASHRAE climatic zones will be studied. Sixteen archetypes covering the main features encountered in real buildings in the U.S. and produced by the U.S. Department of Energy (DOE) will be used in this analysis. The Energy Use Intensity calculated using 1042 EnergyPlus weather files produced by DOE, will be analysed. The lessons learned from this study will provide a solid basis to explore and validate other climatic zoning methodologies, such as the Brazilian case, taking advantage of the scientific knowledge acquired in building energy simulation, geographic information system (GIS), programming and high-performance computing by the proposer.
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