Modelling and Assessment of Cloud Based Smart Dual Fuel Switching System (SDFSS) of Residential Hybrid HVAC System for Simultaneous Reduction of Energy Cost and Greenhouse Gas Emission Under Smart Grid

The objective of this research is to develop models to assess potential benefits of cloud-based Smart Dual Fuel Switching System (SDFSS) of the residential hybrid HVAC system of electric air source heat pump (ASHP) and natural gas furnace/boiler (NGFB) for simultaneous reduction of energy cost and greenhouse gas (GHG) emission. It will entail detailed modelling, simulation, and optimization of three different well studied residential houses in four regions of Ontario to assess the potentials of such smart cloud-based supervisory control under different Time-of-Use (TOU) electricity prices and federal carbon tax schemes in terms of maximizing energy cost saving and GHG emission reduction while providing a flexible and ubiquitous mechanism for utilities (both electric and natural gas) to better manage their infrastructure for distributed renewable energy generation and load management under the smart grid framework. The aim of this project is to answer the following research question: “How effective are the SDFSSs in different cold climate cities, and how does it perform in future high-carbon pricing scheme from a GHG emission and economic perspective?”

Faculty Supervisor:

Alan Fung


Gulsun Demirezen


Sustainable Buildings Canada


Engineering - mechanical


Professional, scientific and technical services


Ryerson University



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