4.7 Article

Building heating solutions in China: A spatial techno-economic and environmental analysis

期刊

ENERGY CONVERSION AND MANAGEMENT
卷 179, 期 -, 页码 201-218

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2018.10.062

关键词

Spatial data analysis; District heating; Electric heating; Heat pump; Building heating solution; China

资金

  1. Chinese Scholarship Council (CSC) [201407930004]

向作者/读者索取更多资源

Fast urbanization process and promotion of life standard in China requires a great amount of energy input in building heating sector. North China now faces challenges of upgrading existing fossil fuel based high emission district heating systems into more environmental friendly heating systems. South China is discussing to choose proper building heating solutions for new and existing buildings which lack proper heating facilities. Renewable heating technologies such as ground source heat pump and air source heat pump are candidates to upgrade traditional heating solutions such as fossil fuel boilers and electric heaters. In order to find the most feasible building heating solution for different geolocations of China, this paper proposes a spatial data based techno-economic and environmental analysis methodology to fulfill such research gap. Case studies are carried out in two selected cities by using proposed methodology. Evaluation model shows that, heat pumps is quite competitive in south China compared with electric heaters, whereas in north China heat pumps have to reach several preconditions to be competitive with coal boiler district heating system under current techno-economic and environmental situations. In north China, a heat pump should reach a minimum seasonal coefficient of performance of 2.5-3.7 (for ground source heat pump) or 2.7-3.0 (for air source heat pump) to become CO2 and PM2.5 emission neutral as well as economically competitive compared with coal boiler district heating system. The advantage of proposed methodology is its simplicity in execution and could be repeated to other areas as the data required are available.

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