With the growth in China’s economic GDP, energy consumption has increased year by year. The energy demand of rural residential buildings is 223 million tons of standard coal equivalent, accounting for 24% of the national energy demand. Therefore, an energy-saving design for rural residences is necessary. This research took the traditional residences in southern Shaanxi as the research object and combined the cooking methods in southern Shaanxi with solar heating, proposing a sunlight heating system with an additional firewall. The system is composed of a firewall system and a sunlight system. The combination of the two systems prolongs the heating time and makes up for the lack of intermittent heating. The firewall principle involves using the heat generated by cooking through the heat storage and heat release capacity of the wall, and using the principle of heat radiation and convection to increase the indoor temperature. Meanwhile, the principle of the additional sunlight room involves using the external facade of the building to establish an additional sunlight room, by absorbing the heat radiation of the sun and using the principle of heat transfer from the wall. The rapid loss of indoor hot air is avoided, the heating time is prolonged, and part of the heat is retained, thereby improving the heating efficiency. A model was established based on the typical residential model in southern Shaanxi, and the presence or absence of solar radiation on the wall was used as the research variable. Using ANSYS software to simulate the analysis, it is concluded that the firewall–sunlight system can extend the heating time and meet the continuous heating demand, and the heating effect is better than that of the firewall heating system alone. When the walls have solar radiation, the annual heat load reduction rate of the buildings under the new system is 20.21%. When the walls do not have solar radiation, the annual heat load reduction rate of the buildings under the new system is 8.56%.

Solar energy is a renewable, green, clean, and universal resource that has great potential in rural areas. Combining solar heating technology with building design to increase indoor thermal comfort in winter is an effective energy-saving and environmentally friendly approach. The factors affecting solar building heating mainly include two aspects; one is the lighting area of the building, and the other is the storage of building materials. By increasing the lighting area and using materials with good heat preservation and storage performance, the indoor temperature in winter can be effectively increased, and the heating time can be prolonged, thus decreasing the energy requirements of the building. In this paper, traditional houses in cold winter areas are selected as the research object, and a roof solar heating storage system is proposed. The method is to transform the opaque roof of the traditional houses into a transparent glass roof, and the thermal insulation and heat storage material HDPE is installed in the attic floorboards. The working principle of this system is to increase the amount of indoor solar radiation to raise the indoor temperature and make use of the thermal insulation performance of heat storage materials to prolong the indoor heating time. Through ANSYS software simulation, the heat transfer process, heat transfer mode, and temperature change of the system are analyzed, and the energy saving of the system is analyzed. The system can effectively raise the indoor temperature and has good energy-saving performance. The indoor temperature is raised by 5.8 °C, and the annual heat load of the building is reduced by 1361.92 kW·h, with a reduction rate of 25.02%.

In China, research on winter heating and energy saving for residential buildings mainly focuses on urban residences rather than rural ones. According to the 2018 China Building Energy Consumption Research Report, rural residential buildings emit about 423 million tons of carbon, accounting for 21% of the country’s total carbon emissions. According to the research on China’s greenhouse gas inventory, the main sources of carbon emissions in rural areas are from cooking and the burning of fuelwood and biomass for heating in winter. In this study, the southern Shaanxi area, which is hot in summer and cold in winter, was selected as the research site, and a fire wall system was planned that combines cooking and heating facilities in residential buildings. The system uses the heat generated by cooking and the heat storage capacity of the wall, as well as the principle of thermal radiation and heat convection, to increase the indoor temperature. The advantage is that the hot air generated is mainly concentrated in the inside of the wall, which reduces the direct contact with the cold outdoor air and avoids excess heat loss. In this study, in addition to considering the influence of the cooking fire wall system on the indoor temperature, the difference in the outer wall with or without solar thermal radiation was also considered. The research results show that the use of a cooking fire wall heating system reduces the annual heat load of the building to 440.8318 KW·h, which is a reduction rate of 7.91%. When there is solar radiation on the outer wall, the annual thermal load of the building is reduced by 1104.723 kW·h, and the reduction rate is 19.84%.

Solar energy has the advantages of being green, renewable, and energy-efficient. The use of solar energy in buildings can result in significant energy savings, and a great deal of practical and theoretical research has been conducted on solar buildings around the world. Southern Shaanxi belongs to a climate zone with hot summers and cold winters (HSCW). The mean room temperature is 4 °C, and it is lower than 2 °C at night, which greatly exceeds the thermal comfort range that the human body can bear. Aiming at a range of challenges including backward heating methods and low heating efficiency in southern Shaanxi, a fully passive thermal storage wall heating system (TSWHS) is proposed for traditional houses in the area. The specific method is to set up a thermal storage wall (TSW) outside the outer walls on the east, west, and south sides of the residential buildings. The wall is provided with an air exchange port, and there is no glass in the outer area of the doors and windows, which does not affect the normal application. The principle is that after the TSW receives solar radiation, the temperature of the internal HDPE (high-density polyethylene) and the air inside the cavity rises, which raises the interior temperature via the heat transfer and the air exchange port inside the TSW. The hot air inside the thermal wall achieves the purpose of heating. Lastly, through a comparison with the original heating system (OHS), it is confirmed that the TSWHS has certain practicability. According to an experimental simulation, the system can increase the indoor temperature by an average of 5.1 °C in winter and save about 1726.43 kWh of energy, accounting for 27.24% of the energy saving.

It was proposed to develop a better multiscale learning dictionary picture de-noising technique. The approach improves the adaptive threshold curvilinear transform, which can divide an image into different scale information and be used to build a curvilinear multiscale learning dictionary. The method finished the dictionary and sparse coefficient updates in the picture through circular iterations and then superimposed the matching curvilinear wave domain image blocks and performed the curvilinear inverse transform to generate the denoised image. The test was carried out by adding additive Gaussian noise to a standard grayscale image, and the results revealed that the peak signal-to-noise ratio of the grayscale image de-noising result of this paper’s method was improved by 56.6% on average, and the structural similarity was improved by 0.44 on average, compared to the conventional de-noising algorithm. It was determined that the enhanced approach preserved the picture’s edge and texture information well, that image quality was greatly improved, and that the algorithm’s execution efficiency was superior to that of the conventional de-noising algorithm.