LAUSR

The rapid development of rural tourism and higher requirements for the indoor environments of rural tourism buildings (RTBs) have led to rapid growth in the energy consumption of RTBs. The aim of this work was to apply a new method to optimize the indoor thermal environments and energy performances of RTBs and promote scientific passive design strategies for RTBs in southeastern coastal areas of China. First, a field survey was carried out to understand the statuses of buildings and the energy consumption of RTBs. Through a building typology analysis, two types of RTBs (renovated from existing buildings and newly built) were chosen as the dominant types in the villages. Second, a comprehensive parametric study was conducted to examine the impact of energy consumption and the indoor thermal environment using a global sensitivity analysis. The passive design parameters with large sensitivity impacts were selected using the Sobol sampling method and by calculating the comprehensive contribution rates of the parameters. Then, the NSGA-II algorithm was used to simultaneously minimize the two objectives and generate the Pareto front solution sets of the two RTB types. Finally, by applying an entropy-based TOPSIS decision-making method, the optimal schemes (the best energy-saving solution, the best comfort solution, and the best compromise solution) for the two RTB types were further obtained from the feasible Pareto-optimal solutions, and the suggested values for the design parameters are presented. This study proposes a new multi-objective optimization approach combining the NSGA-II algorithm and an entropy-based TOPSIS decision-making method, and the findings are valuable, as they can help designers to improve the designs of rural tourism buildings.