Price vs policy: The impact of cost uncertainty on decarbonization pathways

The future costs of many low-carbon power generation technologies are highly uncertain. Capturing these uncertainties for current and emerging technologies can help to understand potential policy impacts and the roles that emerging technologies could play. Energy system studies often use a scenario-based approach, which requires modelers to choose specific values from the range of possibilities, which can bias results and report unlikely scenarios. This paper combines a stochastic capital-cost forecasting methodology, based on Wright’s law of experiential learning, with a range of cost values for emerging technologies. The set of inputs generated is linked with the COPPER power system capacity expansion model to generate a database of 400 model runs, using 100 sampled combinations of cost input parameters and four policy scenarios. The impacts of policy on future emissions, system costs and generation mixes are presented. The incorporation of uncertainty into the model demonstrates the consistent deployment of transmission across all scenarios, in contrast with the inconsistent deployment of emerging technologies. This study finds that neither the carbon tax nor proposed clean electricity regulations achieve power-system decarbonization by 2050 across all scenarios. The results from this study are consistent with the results of national and provincial energy studies in Canada, however some results were outliers compared to the full distribution of potential model outcomes. These findings underscore the critical need to incorporate uncertainty into power system models, particularly when discussing policies and emerging technologies. • Links stochastic cost forecasts with the COPPER capacity expansion model. • Conducts 400 probabilistic simulations under four Canadian policy scenarios. • Finds transmission expansion robust across all cost and policy uncertainties. • Shows CCS and SMR deployment highly sensitive to cost and policy choices. • Reveals current policies insufficient for full power sector decarbonization by 2050.

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Publication Details

Journal
Energy Economics
Published
2025-12-18
DOI
https://doi.org/10.1016/j.eneco.2025.109088
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
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article

Price vs policy: The impact of cost uncertainty on decarbonization pathways

Madeleine McPherson, Nathan de Matos
Energy Economics
Integrated Energy Systems Optimization
article

Price vs policy: The impact of cost uncertainty on decarbonization pathways

Madeleine McPherson, Nathan de Matos
article en

Abstract

The future costs of many low-carbon power generation technologies are highly uncertain. Capturing these uncertainties for current and emerging technologies can help to understand potential policy impacts and the roles that emerging technologies could play. Energy system studies often use a scenario-based approach, which requires modelers to choose specific values from the range of possibilities, which can bias results and report unlikely scenarios. This paper combines a stochastic capital-cost forecasting methodology, based on Wright’s law of experiential learning, with a range of cost values for emerging technologies. The set of inputs generated is linked with the COPPER power system capacity expansion model to generate a database of 400 model runs, using 100 sampled combinations of cost input parameters and four policy scenarios. The impacts of policy on future emissions, system costs and generation mixes are presented. The incorporation of uncertainty into the model demonstrates the consistent deployment of transmission across all scenarios, in contrast with the inconsistent deployment of emerging technologies. This study finds that neither the carbon tax nor proposed clean electricity regulations achieve power-system decarbonization by 2050 across all scenarios. The results from this study are consistent with the results of national and provincial energy studies in Canada, however some results were outliers compared to the full distribution of potential model outcomes. These findings underscore the critical need to incorporate uncertainty into power system models, particularly when discussing policies and emerging technologies. • Links stochastic cost forecasts with the COPPER capacity expansion model. • Conducts 400 probabilistic simulations under four Canadian policy scenarios. • Finds transmission expansion robust across all cost and policy uncertainties. • Shows CCS and SMR deployment highly sensitive to cost and policy choices. • Reveals current policies insufficient for full power sector decarbonization by 2050.

Energy EconomicsVol. 154
University of Victoria (CA)
Openalex Percentile: Top 59%
Integrated Energy Systems Optimization
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