Abstract
Purpose. The purpose of this study was to develop and validate a comprehensive evaluation model to identify optimal energy-saving renovation strategies aimed at reducing operational carbon emissions in hotel buildings in China, considering varying hotel grades, construction periods, and climatic zones.
Theoretical Framework. The study integrates theoretical insights from Energy Conservation Theory, Socio-technical Systems Theory, and Building Energy Simulation Models. This comprehensive framework provides an understanding of how technological, climatic, and operational factors collectively influence energy efficiency outcomes.
Methodology. Utilizing a quantitative approach, the study employed the International Performance Measurement and Verification Protocol (IPMVP) Option D methodology alongside EnergyPlus simulations to estimate energy performance under China's latest national energy-saving standards (GB55015-2021). Real-world data from approximately 300 hotels across different climatic zones and categories from 2016 to 2023 were collected and augmented using advanced statistical methods (Gaussian Copula) to enhance sample robustness. Stepwise regression analysis was then conducted to assess the impacts of various renovation measures on operational carbon emissions.
Findings. The analysis revealed substantial variability in the effectiveness of renovation measures across different contexts. For instance, exhaust-air heat recovery and envelope insulation demonstrated significant carbon reduction in severe-cold climates, whereas demand-controlled kitchen ventilation often resulted in increased emissions due to operational mismanagement. Retrofit measures such as window films showed conflicting outcomes dependent on climate and hotel class, highlighting that retrofit efficacy is highly context-specific rather than universally applicable.
Conclusions and Recommendations. The study concludes that energy-saving renovation strategies must be tailored to specific climatic, operational, and management contexts to achieve meaningful reductions in operational carbon emissions. Practitioners should employ dynamic, climate-specific simulations, rigorous commissioning, and integrated behavioral governance systems. Future research is recommended to utilize longitudinal datasets for stronger causal inference, incorporate occupant behavior metrics, and develop techno-economic models to further refine the decision-making framework for hotel energy retrofits. This research significantly contributes to the theoretical understanding of context-dependent retrofit efficacy and provides actionable guidance for sustainable hotel operations and policy formulation.