Multi-Objective Performance Assessment and Pareto Screening of Energy Use, Photovoltaic Generation and Life-Cycle Cost for New Rural Housing Across Five Chinese Cities

Improving building energy efficiency is essential for carbon neutrality. China’s rural housing consumes a substantial share of energy, yet cross-regional comparisons of energy and economic performance under consistent conditions remain limited. This study evaluates new rural housing performance in Guangzhou, Hefei, Beijing, Harbin, and Aksu, which span four climatic zones. Six building parameters were combined using a mixed-level orthogonal design to generate design alternatives, which were simulated in BEopt to obtain energy use intensity (EUI), photovoltaic generation (PVG), and relative life-cycle cost (LCC). Pearson correlation and multiple linear regression quantified variable-performance associations, while Pareto screening identified non-dominated alternatives. Furring exterior-wall insulation R-value was negatively correlated with EUI in five cities (p < 0.001). PV array azimuth, which co-varies with building orientation, and PV tilt were associated with PVG, whereas the variables most associated with LCC and the size of the Pareto sets varied by city. Across 24 non-dominated solutions, mean EUI decreased by 31.1%, PVG increased by 8.6%, and LCC decreased by 9.5% relative to the baseline. The largest individual improvements were a 49.7% EUI reduction in Beijing, 28.6% PVG increase in competition-based Aksu, and 20.2% LCC reduction in Harbin. These results support regionally adaptive and multi-objective design of new rural housing.