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The Development of a Framework for Modelling Greenhouse Gas Mitigation Scenarios in the Electricity Generation Sector

  • Author / Creator
    Moronkeji, Adeoye
  • Low- or zero-emitting alternative sources of energy have become widely sought for reducing greenhouse gas (GHG) emissions globally. Specifically, in the electricity generation sector, governments, utilities, regulators, and institutions have announced and implemented integrated policy measures such as renewable electricity generation targets, incentives, and efficiency standards for climate change mitigation. However, the associated constraints of recoverable resource viability, public acceptability, and high investment costs, along with limited generation output of alternative energy technologies compared to fossil fuel technologies, could make a low-emission electricity generation mix uneconomical to pursue. Therefore, it is necessary to quantitatively evaluate the greenhouse gas mitigation possible and the associated abatement costs from different integrated alternative energy penetration scenarios in an electricity generation mix in order to make informed policy decisions. The Long-range Energy Alternative Planning (LEAP) software was used to model the power generation sector over a study period of 41 years (2010-2050). Alberta, a Western Canadian province, was selected to evaluate the environmental and policy implications of the foregoing. This study assessed the comparative GHG mitigation in terms of dollar per tonne avoided and cumulative GHG emissions that could result from the adoption of different alternative energy penetration scenarios in which fossil fuels are replaced in an electricity generation mix in the medium term (to the year 2030) and long term (to 2050) using LEAP. Pathways for increasing the renewable share of electricity generation and associated GHG mitigation possible were investigated. The business-as-usual (BAU) scenario and 18 alternative scenarios were developed, simulating situations in which high-emission baseload coal-fired power plants would be retired and replaced by gas-fired power plants for baseload generation, and zero- or low-emission alternatives such as biomass hydro, solar, wind, geothermal, and nuclear are introduced into the generation mix to replace at least two-thirds of retired coal capacity by 2030. Over the study period, the results show that a GHG mitigation potential of 44% to 60% below 2014 reported emissions of 48.9 Mt CO2 eq. from the electricity generation sector may be achieved by the year 2030. A 30% renewable capacity target would increase the renewable electricity production share from the current 10% to 22% by 2030. The GHG abatement costs of the alternative scenarios range from −$5/t CO2 eq. to $820/t CO2 eq. compared to the BAU by 2030. By 2050, about 42% to 65% GHG mitigation potential may be achieved with scenario abatement costs of −$13/t CO2 eq. to 214/t CO2 eq. compared to the BAU. The outcomes of this study offer insights into the selection of alternative energy penetration pathways for a lower GHG emission electricity generation mix in Alberta.

  • Subjects / Keywords
  • Graduation date
    2017-11:Fall 2017
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R3TT4G69X
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Master's
  • Department
    • Department of Mechanical Engineering
  • Supervisor / co-supervisor and their department(s)
    • Kumar, Amit Mechanical Engineering)
  • Examining committee members and their departments
    • Li, Yunwei (Ryan) (Electrical and Computer Engineering)
    • Tian, Zhigang (Will) (Mechanical Engineering)
    • Kumar, Amit Mechanical Engineering)