Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Canada’s electricity sector is predominantly low-carbon, but includes coal, natural gas, and diesel fuelled power plants. We use a new linear programming optimization model to identify least-cost pathways to decarbonize Canada’s electricity sector. We co-optimize investments in new generation, storage and transmission capacity, and the hourly dispatch of available assets over the course of a year. Our model includes hourly wind speed data for 2281 locations in Canada, hourly solar irradiation data from 199 Canadian meteorological stations, hourly demand data for each province, and inter- and intra-provincial transmission line data. We model the capacity of hydropower plants to store potential energy and respond to variations in renewable energy output and demand. We find that new transmission connections between provinces and a substantial expansion of wind power in high wind locations such as southern Saskatchewan and Alberta would allow Canada to reduce electricity sector emissions at the lowest cost. We find that hydropower plants and inter-provincial trade can provide important balancing services that allow for greater integration of variable wind power. We test the impact of carbon pricing on Canada’s optimal electricity system and find that prices of $80/tonne CO2e render the majority of Canada’s coal-fired plants uneconomic.