Dynamic simulation of thermal load and energy efficiency in poultry buildings in the cold zone of China

Understanding the dynamic heating and cooling load of poultry houses enables more precise environmental housing control; however, there is a lack of efficient tools for evaluating and predicting these loads. The objectives of this study were to develop and validate a toolkit to simulate the hourly building load throughout a year, simulate the base room temperature, and investigate the thermal performance of a commercial poultry house in Beijing. Various infiltrating air volumetric flow rates (0.2, 0.6, 1.0, and 2.0 air changes per hour) and total ventilation rates under three mortality levels (5.0%, 10.0%, and 15.0%) were used for the simulation to compare the annual heating and cooling load (AHL and ACL). The correlations between measured and simulated data were 0.99 for indoor air temperature and 0.90 for relative humidity. Based on the simulation results, the base room temperature was -9.2 to 42.2 degrees C throughout the year. The recommended temperature was met only 38.80% of the year, indicating that extra energy must be consumed to maintain a suitable temperature all year. Air inlets (windows and doors) were altered to meet Chinese energy efficiency standards, which decreased the maximum AHL and ACL by approximately 11.10% and 4.81%, respectively. When the tightness of envelope construction was adjusted from "loose" to "medium" and from "loose" to "tight", the maximum AHL decreased by 15.45% and 19.86% and the maximum ACL decreased by 4.45% and 5.72%, respectively. Decreasing the ventilation rate reduced the hourly cooling and heating load from 12.51 to 50.04 KW and 3.75-15.01 KW, respectively, due to different mortality rates when the air temperature difference was 5.0 degrees C and 20.0 degrees C. The proposed simulation toolkit is an effective and accurate tool for evaluating and predicting dynamic building loads for poultry houses. Hourly dynamic thermal simulations throughout the year can accurately determine potential problems in housing systems and lead to appropriate energy-saving strategies.