Hybrid energy system optimization model: Electrification of Ontario's residential space and water heating case study

Abstract

Energy systems are becoming more complex as new energy sources are introduced in support of clean energy goals. These hybrid energy systems can be configured for cogeneration to account for multiple energy uses, including not only electricity but also space heating, water heating, and industrial process heat. Variable renewable energy systems are increasingly being added to hybrid systems to mitigate climate change and reduce greenhouse gas (GHG) emissions. This often creates additional challenges to meet energy demands due to variability associated with renewable generation. In support of energy planning for the new clean economy, the Hybrid Energy System Optimization (HESO) model has been developed to study the feasibility and benefits of nuclear-renewable hybrid energy systems. The model is formulated, as a mixed-integer linear programming (MILP) algorithm, to determine the best energy mix by minimizing annual cost. Because electrification will play a significant role in realizing a clean economy, this study explores the potential economic viability of electrification of residential water and space heating in Ontario. Different energy scenarios have been analyzed to understand the challenges associated with electrification and determine which energy sources will significantly reduce greenhouse gas emissions, while also maintaining competitive energy costs. The results show that electrification of residential water heating can be a viable alternative to natural gas heaters; reducing GHG emissions and energy cost. However, electrification of residential space heating is more challenging due to the large seasonal temperature variations that create significant energy demand fluctuations. Additional nuclear and wind generating capacity, as well as storage systems, are all important elements to support Ontario's transition to a low carbon economy through electrification.