Five-year technology selection optimization to achieve specific CO2 emission reduction targets

Abstract Long-term planning for replacement of fossil fuel energy technologies with renewables is of great importance for achieving GHG emission reduction targets. The current study is focused on developing a five-year mathematical model for finding the optimal sizing of renewable energy technologies for achieving certain CO 2 emission reduction targets. A manufacturing industrial facility which uses CHP for electricity generation and natural gas for heating is considered as the base case in this work. Different renewable energy technologies are developed each year to achieve a 4.53% annual CO 2 emission reduction target. The results of this study show that wind power is the most cost-effective technology for reducing emissions in the first and second year with a cost of 44 and 69 CAD per tonne of CO 2 , respectively. Hydrogen, on the other hand, is more cost-effective than wind power in reducing CO 2 emissions from the third year on. The cost of CO 2 emission reduction with hydrogen doesn't change drastically from the first year to the fifth year (107 and 130 CAD per tonne of CO 2 ). Solar power is a more expensive technology than wind power for reducing CO 2 emissions in all years due to lower capacity factor (in Ontario), more intermittency (requiring mores storage capacity), and higher investment cost. A hybrid wind/battery/hydrogen energy system has the lowest emission reduction cost over five years. The emission reduction cost of such hybrid system increases from 44 CAD per tonne of CO 2 in the first year to 156 CAD per tonne of CO 2 in the fifth year. The developed model can be used for long-term planning of energy systems for achieving GHG emission targets in a regions/country which has fossil fuel-based electricity and heat generation infrastructure.