Residential buildings are major energy consumers, and efficient energy management is crucial. This study addresses the gap in existing research by proposing a novel residential load factor method tailored to hourly climatic data. This method enhances the accuracy of cooling load calculations throughout the year compared to traditional approaches using peak or seasonal averages. The proposed method integrates with the well‐established residential load factor framework, capturing the dynamic influence of temperature variations on energy use. Furthermore, the accuracy of the residential load factor method was verified by comparing the results with those of the RETScreen Expert software. The research also compares buildings based on energy efficiency measures applied. Comparison is carried out for a building with energy efficiency measures and a building without incorporating energy efficiency measures. The results highlight significant yearly reductions in cooling load (47. 92%), leading to lower energy costs (264. 2) and reduced 6621 kg of CO 2 emissions. This study paves the way for further research, including integrating weather forecasting data and exploring the economic feasibility of energy‐saving measures in various contexts. By improving this method, building designers can make better choices to make residential buildings energy‐efficient and environmentally friendly.
Yazdan et al. (2025) studied this question.