## 3 Model Development
### Operational Parameters of the Baseline Rural House Model  
Survey and measured data indicate that during the heating season, the 24-h average indoor temperature in unheated rural houses remains at 4.7 \({}^{\circ}\)C. In contrast, in rural houses where heating measures are implemented, the 24-h average indoor temperature was maintained between 16 \({}^{\circ}\)C and 25 \({}^{\circ}\)C during the period from 20 January to 25 January 2022. This method of maintaining temperature is influenced by the farmers' own perception of cold and their economic situation [84]. Based on the current status of rural houses and the autonomous region's building energy-saving design standards, the operational parameters for the baseline rural house model are set as follows: For the severe cold C zone, the heating period is from 15 October to 15 April of the following year, totaling 183 days. Heating equipment operates throughout the day, with the indoor heating temperature set at 20 \({}^{\circ}\)C. The indoor person density is 0.02 people/m\({}^{2}\), with an average metabolic rate of 0.9 met (1 met = 58.15 W/m\({}^{2}\)), winter average clothing thermal resistance of 1.2 clo (1 clo = 0.155 m\({}^{2}\cdot\)K/W), and ventilation rate of 0.5 h\({}^{-1}\). Indoor lighting power is 5 W/m\({}^{2}\), and equipment power density is 3.8 W/m\({}^{2}\), with operating times from 8:00 to 9:00 and 20:00 to 24:00. For the heating period energy consumption simulation, meteorological data in EPW format from the CSWD database of the China Meteorological Administration is used. In this study, the building energy consumption model was established using Rhino-Grasshopper, with Ladybug Tools employed as the building performance simulation tool for heating energy consumption simulations. Grasshopper integrates plugins such as EnergyPlus and OpenStudio, and energy consumption calculations are performed using Ladybug and Honeybee to invoke EnergyPlus [82]. Its accuracy has been widely  
Figure 3: Solar radiation as a function of panel tilt/orientation. validated [85; 86; 87]. The benchmark rural dwelling energy consumption model created using Rhino-Grasshopper's visualization is shown in the Figure 4, with heating energy consumption simulated using Ladybug Tools. The results indicate that as temperatures drop, the demand for heating increases, primarily from November to March of the following year. The total heating energy consumption simulation value is 35,920.08 kWh, as shown in Figure 5b's heating energy consumption chart; the average winter heating coal usage of 7.2 tons is calculated based on the measured average daily coal consumption during winter for the benchmark rural dwelling, as shown in Figure 5a for daily coal consumption, using Type III bituminous coal. At this time, the thermal efficiency of the heating system is 88%, resulting in a heating energy consumption of 39,312 kWh during the heating period, with an error rate of 8.6% compared to the simulation value. Therefore, the results of the energy consumption simulation calculations are considered quite accurate and reliable. Rural residences often have smaller capacity photovoltaic systems installed on their roofs, mainly for household electricity use. These systems typically utilize photovoltaic panels, and in some cases, photovoltaic tiles may replace traditional tiles on sloped roofs. This study opts for monocrystalline silicon photovoltaic panels for simulation, installing panels produced by a certain manufacturer at the optimal annual tilt angle of 35\({}^{\circ}\). Table 2 provides detailed parameters of the photovoltaic modules used in the simulation, which employs the Hay diffuse anisotropic model to analyze inclined radiation.