Five-year technology selection optimization to achieve specific CO2 emission reduction targets |
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| Affiliation: | 1. Department of Mechanical and Mechatronics Engineering, University of Waterloo, 200 University Avenue W, Waterloo, ON N2L 3G1, Canada;2. Department of Chemical Engineering, University of Waterloo, 200 University Avenue W, Waterloo, ON N2L 3G1, Canada;3. Department of Electrical and Computer Engineering, Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3, Canada;1. Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology, Chengdu 610054, PR China;2. School of Physical Science and Technology, Southwest Jiaotong University, Chengdu, 610031, People''s Republic of China;3. School of Physics, University of Electronic Science and Technology of China, Chengdu, 610054, People''s Republic of China;1. College of Material, Chemistry and Chemical Engineering, Hangzhou Normal University, Hangzhou, Zhejiang, 311121, PR China;2. School of Materials Science and Engineering, Harbin Institute of Technology, Harbin, Heilongjiang, 150001, PR China;1. Green Center for Systems Biology, University of Texas Southwestern Medical Center, Forest Park, Dallas, TX, 75390, USA;2. Department of Physics and Astronomy, University of Arkansas at Little Rock, Little Rock, AR, 72204, USA;3. Department of Physics, Applied Physics and Astronomy, Rensselaer Polytechnic Institute, Troy, NY, 12180, USA;1. State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei 230027, PR China;2. School of Civil Engineering, Hefei University of Technology, Hefei 230009, PR China;3. Anhui International Joint Research Center on Hydrogen Safety, Hefei, 230009, China;1. Key Laboratory for Green Chemical Technology of Ministry of Education, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China;2. Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300072, China |
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| 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 CO2 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 CO2 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 CO2, respectively. Hydrogen, on the other hand, is more cost-effective than wind power in reducing CO2 emissions from the third year on. The cost of CO2 emission reduction with hydrogen doesn't change drastically from the first year to the fifth year (107 and 130 CAD per tonne of CO2). Solar power is a more expensive technology than wind power for reducing CO2 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 CO2 in the first year to 156 CAD per tonne of CO2 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. |
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| Keywords: | Optimization Wind Solar Hydrogen Battery |
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