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Exploring the role of negative emission technologies in regional power system planning toward carbon net zero -- A case study for the province of Saskatchewan, Canada

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  • Xu, Yang
  • Huang, Guohe
  • Liu, Yanyan
  • Chen, Leian

Abstract

Negative emission technologies (NETs) such as bioenergy with carbon capture and storage (BECCS) and direct air capture (DAC) are essential for offsetting difficult-to-reduce greenhouse gas (GHG) emissions, critical for achieving a net-zero carbon future. Therefore, an optimization-driven negative emission technologies (ODNET) model has been first developed in this study for deploying NETs in Saskatchewan's power system using a mixed-integer fractional chance-constrained programming approach with Sustainable Development Goals (SDG) assessment. Results indicate that renewable energy including solar, wind, and Small Modular Reactors (SMRs) will dominate future power generation, with natural gas-fired equipped with CCS supporting the low-carbon transition. Applying BECCS and DAC together not only reduces total system costs by 9 %, but also helps achieve carbon net zero ahead of schedule. DAC is expected to deliver 4.28 Mt of negative emissions, while BECCS could provide over 48 Mt of negative emissions and generate over 40,000 GWh of electricity. Moreover, the power system's low carbon transition will enhance SDG indicators in renewable energy share, fossil fuel reduction, and CO2 emissions mitigation. This study highlights optimized strategies for regional power system planning toward carbon net zero and clarifies NETs' roles and potential applications in future power systems.

Suggested Citation

  • Xu, Yang & Huang, Guohe & Liu, Yanyan & Chen, Leian, 2025. "Exploring the role of negative emission technologies in regional power system planning toward carbon net zero -- A case study for the province of Saskatchewan, Canada," Energy, Elsevier, vol. 326(C).
    • Handle: RePEc:eee:energy:v:326:y:2025:i:c:s0360544225019930
    DOI: 10.1016/j.energy.2025.136351
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    1. Liu, J. & Li, J.W. & Li, X. & Li, Y.P. & Gao, P.P. & Jin, L., 2026. "An optimization model to provide electric power systems’ net zero-carbon emission pathways considering diverse measures under double-side randomness and vagueness," Renewable Energy, Elsevier, vol. 256(PI).

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