## 5 Conclusions  
To meet the demand for heating system design in rural residential buildings, this study proposed a probabilistic design heating load calculation method that takes into account the indoor temperature uncertainty. The results of this new method are demonstrated using a rural residential building in Harbin as an example. The specific conclusions are as follows:  
1. A refined method for determining the design heating load of rural residential buildings was proposed. In this method, an indoor temperature stochastic model was established for the usage characteristics of rural residential buildings to generate multiple possible scenarios for the indoor temperature, to ensure the reasonableness of the design load determination.
2. Using a rural residential building in Harbin as an example, the results of the application of the new method in this study were analyzed, and guiding principles for design load selection were found. Specifically, within the confidence level of 90% to 100%, design load values corresponding to lower confidence levels were recommended to reduce the design capacity; within the confidence degree of 80% to 90%, design load values corresponding to higher confidence levels were recommended to enhance the design reliability.
3. The advantages of this new method were analyzed by using the traditional method as a control. The results showed that while the traditional method might not be able to meet the reliability requirements of heating system design for rural residential buildings, the new method can guide the designer to reduce or increase the design capacity based on reliability and economic needs.  
In the new method, whether the design heating load result is reasonable or not depends on whether the stochastic model of indoor temperature can accurately reflect the uncertainty of indoor temperature. In this study, the parameters of this stochastic model were determined by referring to the existing literature. Due to the difference in the level of economic development, the indoor temperature regulation habits of rural buildings in different regions will also be different. Therefore, the model parameters set in this study are not necessarily applicable to rural buildings in all regions. In future work, we will improve  
Figure 8: Comparison of the design heating loads of the new method with the traditional method. (Note: The purple line indicates the results of the new method in this study, and the red line indicates the results of the traditional method).  
the problem of model parameter determination through a lot of field investigation to apply this research method to cases in diverse countries and regions.  
Conceptualization, Z.T.; Investigation, H.M. ([PERSON]) and X.W.; Methodology, H.M. ([PERSON]), X.W. and H.M. ([PERSON]); Project administration, Z.T. and Y.L.; Software, H.M. ([PERSON]) and X.W.; Supervision, Z.T.; Writing--original draft, H.M. ([PERSON]) and X.W. All authors have read and agreed to the published version of the manuscript.  
This study was supported financially by the National Natural Science Foundation of China (Grant No. 51978449).  
Not applicable.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors.  
Author [PERSON] was employed by Cecep Wind Power Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.