Energy cost analysis of an intelligent building network adopting heat trading concept in a district heating model.

With the help of advanced technologies, district heating systems were gradually improved to increase fuel use efficiency and reduce environmental impacts. Several control strategies focused on the performance improvement of energy generation or distribution in the network. However, most strategies overlooked zone-scaled thermal comfort related to occupant characteristics, and there was lack of studies combined with heat trading concepts. This research presents energy cost analysis of an intelligent network model and heat trading to mitigate increases of energy use and thermal dissatisfaction in a district model. Advanced thermal control algorithms provide optimized supply air conditions responding to occupant characteristics in different buildings. A distribution model contributes to the reduction of energy consumption, and heat trading effects are analyzed to maximize energy cost savings in a district model. In comparison with a conventional model, an intelligent controller improves thermal comfort by about 16.2% for a clinic, 2.4% for an office, and 7.1% for a residential building, respectively. Also, a distribution model with heat trading concept saves total energy costs by about 24.7%, theoretically. In conclusion, the model has advantages that it properly responds to occupant characteristics to mitigate thermal dissatisfaction, and it has a great potential to reduce total energy costs. [ABSTRACT FROM AUTHOR]