REPORT
No Margin for Error Aligning utility resource planning with a net-zero futureFebruary 24, 2024About the report
Utility resource planning is central to Canada’s ability to achieve its climate and energy commitments. Without proactive and integrated planning, the country risks falling behind its net-zero goals, increasing consumer costs, and missing opportunities to leverage demand-side solutions for a more efficient and resilient energy system.
As Canada works towards a net-zero future by 2050, utility resource planning must adapt to meet evolving energy needs. No Margin for Error: Aligning Utility Resource Planning with a Net-Zero Future examines how Canadian utilities currently plan for the future and identifies key gaps that could hinder progress. The report explores the integration of demand-side resources, the risks associated with reactive planning, and the necessity for more coordinated and transparent decision-making processes.
Utilities can help ensure a cost-effective and sustainable transition to net zero by addressing these gaps.
Authors
James Gaede
Director of Research
Brendan Haley
Sr. Director of Policy Strategy
Key report findings
Limited coordination between electricity and natural gas utilities leads to inefficient planning.
Most utility planning occurs in silos, with little collaboration between the electricity and natural gas sectors. This fragmented approach prevents a holistic view of system-wide needs, making developing comprehensive strategies for net-zero energy transitions harder.
Business-as-usual electricity load forecasts underestimate future demand growth.
Utility electricity demand forecasts tend to be lower than those outlined in national net-zero pathway studies. This underestimation limits electrification potential, leading to inadequate system expansion plans and potential energy shortages in the long term.
Demand-side resources are not treated as equal alternatives to supply-side solutions.
Energy efficiency and demand response programs are often undervalued in utility planning models. Instead of being included as selectable resources within system expansion models, they are pre-determined and subtracted from load forecasts, reducing their potential impact.