References
Demirezen, G., Fung, A. S., & Deprez, M. Development and optimization of artificial neural network algorithms for the prediction of building specific local temperature for HVAC control. International Journal of Energy Research.
- Developer(s)
- Gulsun Demirezen, Alan Fung
Description
The cloud‐based smart dual fuel switching system (SDFSS) project is a dual‐fuel integrated hybrid heating, ventilation, and air conditioning (HVAC) system in residential homes. The SDFSS was developed to enable optimized, flexible, and cost‐effective switching between the natural gas furnace and electric air source heat pump (ASHP).
- Applications
Optimizing fuel switching for Canadian residential houses; planning simultaneous Reduction of Energy Cost and Greenhouse Gas Emission with Smart Grid Infrastructure
- Key Inputs
location specific ambient temperature, GHG emissions from the consumption of the natural gas, hour of the day, electricity pricing, natural gas pricing, electricity consumption from the hvac equipment, data from the natural gas furnace
- Key Outputs
reduction of cost from the heating, reduction of GHG Emissions
Registered developers
| Name | Organization |
|---|---|
| Gulsun Demirezen | Ryerson University |
