Search

Abstract The residential building sector consumes a large amount of energy and is recognized as a high potential area where urban energy consumption and carbon emission can be reduced. To reduce the residential energy consumption, relevant policies and measures have been formulated in different places. However, due to the lack of adequate information in the process of policy formulation, the effectiveness of most energy-saving policies for residential buildings seems to be unsatisfactory. Although previous studies have analyzed the energy consumption for a single building or for the whole construction industry at the national level, few of them investigated the life-cycle energy consumption of residential buildings at the city level. Since municipal governments are the key implementers for the reduction of urban energy consumption, a city-level analysis on the energy consumption of residential buildings is highly needed for the policy making. To fill the research gap, this paper develops a life-cycle dynamic simulation model to fully reveal the characteristics of energy consumption of residential buildings at the city level. This easy-to-use model is validated by a case study of Beijing, which demonstrates its applicability and capability to help analyze multiple indicators of residential energy consumption and the dynamic trends of these indicators for municipal governments. Furthermore, the model can be used under the condition of limited input data, and can provide the situation analysis and simulation results of energy consumption of urban residential buildings for facilitating the policy making by municipal governments. Graphical abstract Image 1 Highlights • The proposed model can analyze city-level energy consumption of residential buildings. • The model can be used with relatively limited amounts of input data. • Operation stage accounts for 67% of total residential energy consumption in Beijing. • Heating is the most energy-intensive activity of operation stage in Beijing. • Policy implications for residential energy saving are provided based on the model. [ABSTRACT FROM AUTHOR]

• DeST is an effective and accurate tool to predict dynamic thermal load for poultry buildings. • Annual maximum cooling and heating load decreased 11.10% and 4.81% when thermal performances meet standards requirements. • Tightness was adjusted from "loose" to "tight" could lead maximum hourly heating and cooling load declined 19.90% and 5.72%. • Ventilation rate should be decreased according to the actual stocking density/mortality. • The toolkit can be used to suggest relevant energy saving measures for hen houses. 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 °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 °C and 20.0 °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. [ABSTRACT FROM AUTHOR]