Title :
Inferential control - An advanced control strategy to save energy in residential heating systems
Author :
Jassar, S. ; Liao, Zhiling ; Sharma, Toshi
Author_Institution :
Humber Inst. of Technol. & Adv. Learning, Toronto, ON, Canada
Abstract :
The paper presents an advanced control strategy for residential heating systems to save energy and improve indoor environment. This strategy, named inferential control method, is based on Recurrent Neuro-Fuzzy Inference System. In current practice, the control of these heating systems is based on the measurement of air temperature at one point within the building. The inferential control strategy allows for the control to be based on an estimate of the overall thermal performance, minimizing the chance of overheating (saving energy) and underheating (improving comfort) in the building. The performance of this control technology has been investigated through simulation study. The results show that the proposed control scheme can effectively maintain the temperature at set-point, and results in energy savings and improved indoor environment.
Keywords :
fuzzy reasoning; neurocontrollers; space heating; advanced control strategy; energy saving; indoor environment improvement; inferential control method; recurrent Neuro-fuzzy inference system; residential heating system control; thermal performance; Buildings; Furnaces; Heating; Temperature sensors; Thermostats; Dynamic Heating System; Forced-Warm Air Heating Systems; Inferential Control; Inferential Sensor; Recurrent Neuro-Fuzzy Inference System; Single Zone Control; Soft Sensing; Zoned Control;
Conference_Titel :
Electrical Power and Energy Conference (EPEC), 2012 IEEE
Conference_Location :
London, ON
Print_ISBN :
978-1-4673-2081-8
Electronic_ISBN :
978-1-4673-2079-5
DOI :
10.1109/EPEC.2012.6474959