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Heat Transfer Research
Impact-faktor: 0.404 5-jähriger Impact-Faktor: 0.8 SJR: 0.264 SNIP: 0.504 CiteScore™: 0.88

ISSN Druckformat: 1064-2285
ISSN Online: 2162-6561

Volumes:
Volumen 50, 2019 Volumen 49, 2018 Volumen 48, 2017 Volumen 47, 2016 Volumen 46, 2015 Volumen 45, 2014 Volumen 44, 2013 Volumen 43, 2012 Volumen 42, 2011 Volumen 41, 2010 Volumen 40, 2009 Volumen 39, 2008 Volumen 38, 2007 Volumen 37, 2006 Volumen 36, 2005 Volumen 35, 2004 Volumen 34, 2003 Volumen 33, 2002 Volumen 32, 2001 Volumen 31, 2000 Volumen 30, 1999 Volumen 29, 1998 Volumen 28, 1997

Heat Transfer Research

DOI: 10.1615/HeatTransRes.2018025767
pages 659-670

HEAT LOSS ANALYSIS AND OPTIMIZATION OF HOUSEHOLD SOLAR HEATING SYSTEM

Jieyuan Yang
Western China Energy and Environment Research Center, Lanzhou University of Technology, Lanzhou 730050, China; Key Laboratory of Complementary Energy System of Biomass and Solar Energy, Lanzhou 730050, China
Jinping Li
Western China Energy and Environment Research Center, Lanzhou University of Technology, Lanzhou 730050, China; Key Laboratory of Complementary Energy System of Biomass and Solar Energy, Lanzhou 730050, China
Rong Feng
Shaanxi Key Laboratory of Industrial Automation, Shanxi University of Technology, Hanzhong 723001, China

ABSTRAKT

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.


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