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<p>To address low energy efficiency and poor indoor thermal comfort during winter in conventional rural single-standing buildings in Northwest China, this study retrofitted the original boiler-based heating system into a solar water heating system with an intelligent energy allocation strategy. An intelligent scheduling algorithm was developed to optimize system operation and dynamically allocate solar thermal energy. Field tests were conducted to evaluate indoor air quality (IAQ) and thermal environment parameters of the retrofitted building. Results showed that the IAQ fully met the requirements of China’s Indoor Air Quality Standard and the Design Standard for Energy Efficiency of Rural Residential Buildings, reaching Class II (non-polluted). The indoor thermal comfort level was also rated as highly appropriate. Multivariate regression analysis identified the influence of various IAQ factors on indoor comfort in descending order: indoor air relative humidity, indoor air temperature, NO2 concentration, CO2 concentration, CO concentration, SO2 concentration, PM10 concentration, and TVOC concentration. The proposed intelligent energy allocation method effectively enhanced both energy utilization and indoor environmental quality, demonstrating a viable solution for sustainable heating in cold-climate rural buildings.</p>

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Intelligent energy allocation in solar water heating systems for single-standing buildings in cold climates: application to winter heating in rural Northwest China

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月23日

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  • Rongdan Diao,
  • Hao Feng,
  • Congwen Chi,
  • Yajuan Guan,
  • Josep M. Guerrero

摘要

To address low energy efficiency and poor indoor thermal comfort during winter in conventional rural single-standing buildings in Northwest China, this study retrofitted the original boiler-based heating system into a solar water heating system with an intelligent energy allocation strategy. An intelligent scheduling algorithm was developed to optimize system operation and dynamically allocate solar thermal energy. Field tests were conducted to evaluate indoor air quality (IAQ) and thermal environment parameters of the retrofitted building. Results showed that the IAQ fully met the requirements of China’s Indoor Air Quality Standard and the Design Standard for Energy Efficiency of Rural Residential Buildings, reaching Class II (non-polluted). The indoor thermal comfort level was also rated as highly appropriate. Multivariate regression analysis identified the influence of various IAQ factors on indoor comfort in descending order: indoor air relative humidity, indoor air temperature, NO2 concentration, CO2 concentration, CO concentration, SO2 concentration, PM10 concentration, and TVOC concentration. The proposed intelligent energy allocation method effectively enhanced both energy utilization and indoor environmental quality, demonstrating a viable solution for sustainable heating in cold-climate rural buildings.