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In the context of residential energy consumption, the top-down approach and bottom-up approach have been developed to model and predict residential energy demand, and the bottom-up engineering model is a promising choice and an effective tool for urban planners and policymakers. However, unlike the existing building stock databases in some developed countries or regions, China's Pearl River Delta (PRD) region lacks such building databases. Thus, the study established a database of 120 residential districts in the PRD region, and developed typical models through the data of the collection, quantification and classification. In this paper, three typical residential district models have been defined, which was a supplement to previously develop seven typical residential building models. Moreover, four common family patterns in the PRD region were determined by literature research, the corresponding schedules and basic settings were developed subsequently for them. Finally, the simulations of the energy consumption of the three residential districts were conducted, whose energy consumption intensities were 28.43 kWh/m2a, 28.41 kWh/m2a and 28.24 kWh/m2a, respectively. The results of the simulation are similar to the results of the actual energy audit, which is considered that the typical residential buildings are representative yet simple-to-use energy model. [ABSTRACT FROM AUTHOR]

• A series of typical residential building models were defined through statistic method. • The envelope's size, shape, thermal properties and opaque feature were determined. • The indoor space partition and function area distribution were also identified. • The models could serve as a standard platform for building energy simulation research. • The method can be applied to other regions and building types with sufficient data. With the rapid growth of urban population in the Pearl River Delta (PRD) region, the research on residential energy saving has attracted increasing attention. Typical buildings are useful tools for building performance simulation of residential district, which is of great significance for local green building-related research, policy formulation as well as market orientation. In this paper, the spatial information (building size, shape, area and amount of dwelling unit area) and the thermal properties of the envelope (such as window-to-wall ratios, shading coefficient, and the heat transfer coefficient) of about 120 residential districts were collected and statistically analyzed. Meanwhile, 120 residential districts are the actual data in the PRD region since 2010. The analysis method involved K-means, histogram and bubble diagram, box plot - bin mean method and slope method, which aims to remove outlier points and find representative value for each parameter, and define a series of typical residential building models. From the analysis result of 120 residential districts, which involved around 350 types of 1300 residential buildings and over 900 types of dwelling units, 7 typical residential building models were determined to be used in other research. [ABSTRACT FROM AUTHOR]