%0 Journal Article %A Yang, Jieyuan %A Li, Jinping %A Feng, Rong %D 2019 %I Begell House %K solar heating, heat loss, linear regression analysis, energy supply system %N 7 %P 659-670 %R 10.1615/HeatTransRes.2018025767 %T HEAT LOSS ANALYSIS AND OPTIMIZATION OF HOUSEHOLD SOLAR HEATING SYSTEM %U https://www.dl.begellhouse.com/journals/46784ef93dddff27,57a487e415a472cc,12c1e9017fcf50c8.html %V 50 %X Renewable energy sources have the leverage of unlimited availability and environmental friendliness, therefore, they are the optimal alternation for fossil fuel. Among all renewable energy sources, solar energy is the most signifi cant due to the safety and sustainability. Based on this fact, utilization of solar thermal energy has increased sharply mainly for heating and cooling applications. In order to analyze and optimize the heat loss associated with the household solar heating system, an experimental model was built and tested in Minqing County, Gansu Province, China. In this work, the multiple linear regression method is considered to address the outcomes. The relationship between the environmental factors (such as wind speed, ambient temperature, and the temperature of the heating water tank) and the indoor temperature is identifi ed. The experimental results indicate that the convection heat loss of the tank accounted for more than 86% of the heat loss at night. Changes in the supply mode for the night time heating can save about 685.38 kg of standard coal, 0.47 tons of CO2, 11.31 kg of SO2, and 10.69 kg of NOx emissions, which are equivalent to an annual value of more than 1028.07 yuan. A shift to the use of renewable energy has clear economic, energy-saving, and environmental benefits. %8 2019-02-26