The existing building stock faces the challenge of low energy efficiency and requires renovation and upgrading to meet society′s goals of carbon reduction and sustainable development. This study presents an optimization framework utilizing genetic algorithms to develop robust retrofit plans that balance the need for improved energy efficiency, cost-effectiveness considerations for householders, and uncertainties regarding climate conditions. A case study of an aged residential building in a hot and humid region of China is used to demonstrate the proposed method. The optimization results show a potential energy demand reduction of 81.5%. However, due to the relatively long time required to realize economic benefits from high investments, short-term optimization tends to favor solutions with high energy demand and low primary costs. To effectively reduce carbon emissions, it is recommended to consider the long-term economic benefits of retrofits and prioritize solutions with high energy efficiency. However, it is important to acknowledge that the expensive nature of retrofit investments may pose barriers to residents. Society should provide adequate support and guidance to facilitate residential renovation efforts.

Energy conservation renovation of existing buildings is a crucial aspect of sustainable energy development. This study examines the annex of a university sports training building in Guangzhou, highlighting the conflict between maintaining landscape visibility and mitigating excessive solar radiation and thermal conditions following renovation without external shading. Specifically, the analysis focuses on scenarios where the building’s primary orientation aligns with the region’s unfavorable solar orientation. To address this challenge, five facade optimization strategies are proposed, four of which incorporate external shading solutions: horizontal shading, vertical baffle shading, inclined baffle shading, and a comprehensive shading system. Performance simulations were conducted using Ladybug and Honeybee tools within the Grasshopper platform to evaluate the multi-objective optimization of the building’s thermal and visual performance under energy conservation constraints. The findings demonstrate that an integrated shading system significantly influences both building energy consumption and thermal performance. Notably, the 46° inclined baffle shading scheme proves particularly effective in the Guangzhou context, successfully reducing solar radiation, improving indoor lighting quality, and lowering energy consumption, while minimizing visual obstruction. These results provide valuable insights for developing energy-efficient renovation strategies for similar buildings in the region.

The Sixth Assessment Report of the IPCC highlights that global surface temperatures have risen by 1.1 °C above pre-industrial levels, with a marked increase in the frequency and intensity of extreme heat events in hot–humid regions. Buildings in these areas urgently require passive design strategies to enhance climate adaptability. Employing Zhupu Ancient Village in Chaoshan region in China as an example, this study analyzes and evaluates the wind-driven ventilation archetype and buoyancy-driven ventilation archetype of the village through integrated meteorological data analysis (ECMWF) and computational fluid dynamics (CFD) simulations. The results indicate that the traditional climate-adaptive archetype facilitates wind speeds exceeding 0.5 m/s in over 80% of outdoor areas, achieving unobstructed airflow and a discernible stack ventilation effect. Through archetype translation, the visitor center design incorporates open alleyway systems and water-evaporative cooling strategies, demonstrating that over 80% of outdoor areas attain wind speeds of 0.5 m/s during summer, thereby achieving enhanced ventilation performance. The research provides a climate-response-archetype translation-performance validation framework and practical case studies for climate-adaptive design of public buildings in hot–humid regions.