Method for Determining Design Heating Load of Rural Residential Buildings Considering Indoor Temperature Uncertainty  
[PERSON]  
1 School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China; [EMAIL_ADDRESS] (H.M.) 1 [EMAIL_ADDRESS] (H.M.) 12 Tianjin Key Lab of Building Environment and Energy, Tianjin 300072, China 23 Cecep Wind Power Co., Ltd., Beijing 100082, China 3  
[PERSON]  
1 School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China; [EMAIL_ADDRESS]. leave the bedrooms empty. In this case, human activity causes non-continuous occupancy in each room throughout the course of one day. Different from large-scale centralized heating found in urban residential buildings, rural residential buildings often receive small-scale decentralized heating. Because of this, heating equipment in rural residential buildings can be easily turned on and off at any time by people, creating a unique \"part-time, part-space\" heating mode [5; 6]. The two most popular methods for figuring out the design heating load are the load index method and the design parameter method [7]. The load index method is the most user-friendly of them all since it enables designers to determine the design heating load based directly on the building area. Nevertheless, this method finds it difficult to take into consideration the impacts of many elements on the design load outcomes, such as the building envelope's performance. Consequently, the design parameter method, a more refined technique, was released. In this method, the designer must first specify the indoor and outdoor design conditions, then it is possible to perform load simulations to obtain the design heating load value. The design parameter method is commonly employed for urban residential buildings because of the well-established applicable codes, which facilitate the determination of indoor and outdoor design conditions. However, the determination of indoor design conditions for rural residential buildings is more difficult. Due to the \"part-time, part-space\" heating mode, the indoor temperatures in rural residential buildings have a large uncertainty in both temporal and spatial dimensions. There are multiple options for the indoor temperature scenario in each room in rural residential buildings, due to the variety of some factors like the occupancy schedule [8; 9; 10], type of activity [11], and preferred temperature [12; 13; 14], but designers are unable to empirically determine which option can meet the requirements for design reliability. Regretfully, there are inadequate standards governing heating system design in rural residential buildings, making it difficult for designers to obtain reliable information about the design scenarios of indoor temperatures. As a result, the inability to accurately assess indoor design conditions limits the application of the design parameter method in rural residential buildings. When the reliable indoor temperature scenario cannot be entirely established, how can the design heating load of a rural residential building be calculated? A workable answer is offered by the recently created probabilistic design load calculation method (also known as the probabilistic method) [15; 16; 17]. This method permits the load computation to include some uncertain parameters. The following is its basic procedure: initially, the uncertain parameters are quantified using some probabilistic models [18]; the building heating or cooling loads are then simulated under various samples of uncertain parameters; lastly, the probabilistic characteristics of the loads are statistically obtained and the design load values are selected in accordance with certain rules [19]. Using the probabilistic method, [PERSON] et al. [20] determined the design capacity of the air-conditioning system of an office building in Spain, taking into account the uncertainty of the building thermal parameters and internal disturbance parameters. Taking a residential building in Hong Kong as an example, [PERSON] et al.