The Paris Agreement's ambitious goal of limiting global warming necessitates the deployment of negative emission technologies (NETs) or carbon dioxide removal (CDR) technologies. While previous research has explored the implications of CDR, primarily bioenergy-based approaches, using integrated assessment models (IAMs), these studies lacked the detail of more specialized energy systems models. This research addresses this gap by employing the REGEN model, a state-of-the-art power sector investment and operations model, to examine the impacts of a portfolio of CDR technologies (BECCS and DAC) on the US electric sector. The study aims to analyze how the availability and cost of these technologies influence electric sector investments, costs, emissions, and overall decarbonization strategies under various policy scenarios and technological assumptions. The significance lies in providing a detailed analysis of CDR's role in deep decarbonization pathways, considering factors often overlooked in broader energy system models.

Existing literature on CDR primarily utilizes integrated assessment models (IAMs), which lack the technological, temporal, and spatial resolution of more detailed energy systems models. While IAMs have evaluated the value and role of CDR options like BECCS and DAC, they haven't provided the granular insights offered by power sector-specific models. Previous work examining power sector decarbonization often includes BECCS but seldom incorporates a portfolio of CDR technologies. This study aims to fill this gap by using a more detailed model, allowing for a more thorough comparison of the effects of various CDR technologies on the power sector. The analysis considers the impacts on investment, operations, and the optimal mix of low-carbon technologies within a deep decarbonization framework.

The research leverages the Regional Economy, Greenhouse Gas, and Energy (REGEN) model, a state-of-the-art model of power sector investments and operations. This model features hourly resolution, allowing for a detailed representation of variable renewable energy sources, energy storage, and dispatchable low-carbon technologies. The analysis focuses on scenarios for the US electric sector, incorporating technical and economic characteristics of BECCS and DAC obtained from literature, EPRI's Integrated Technology Generation Options report, and expert elicitation. The study considers several dimensions: CO2 policy (cap on national emissions ranging from 70% to 140% reduction relative to 2005 levels); choice sets of low-/zero-/negative-CO2 technologies (reference and renewables-only); wind/solar/storage costs (reference and breakthrough); DAC costs (reference and low-cost); BECCS cost and heat rate (reference and sensitivity analysis); biomass resource availability (reference and sensitivity analysis); and CO2 storage infrastructure and costs (reference and sensitivity analysis). The REGEN model optimizes investments in generation, storage, CDR capacities, hourly dispatch, CO2 transport, storage, transmission, and trade. The single-year static equilibrium model is used to capture the unique features of variable renewable energy and their interaction with other power system components.

The study's key findings demonstrate that incorporating CDR technologies into the electric power sector significantly lowers the cost of deep decarbonization, particularly as the stringency of CO2 reduction targets increases. This cost reduction effect is robust across various sensitivity analyses. The results indicate that BECCS is preferred over DAC for net-zero electric sector CO2 targets, assuming affordable and sustainably managed bioenergy. However, DAC's role increases as biomass supply costs rise. The availability of CDR reduces the dependence on technologies such as advanced nuclear power and long-duration energy storage. The model shows that CDR technologies create net negative emissions, offsetting expensive abatement efforts and enabling zero-CO2 targets to become net-zero. Including both BECCS and DAC yields only slightly lower costs than DAC alone. CDR also influences energy storage deployment, reducing the need for longer-duration storage while increasing the utilization of natural gas-fired units with carbon capture. The spatial distribution of CDR deployment is affected by factors like biomass availability, CO2 storage sites, and technological costs, with BECCS deployment geographically more diverse than DAC. High-utilization operations for both BECCS and DAC are observed. The electricity consumption by DAC is a small portion of overall electricity demand, even under high deployment scenarios. Sensitivity analyses show that even with optimistic cost assumptions for renewables, they don't necessarily constitute the least-cost solution without CDR. Moreover, scenarios with CDR achieve greater CO2 reductions for equivalent expenditures or achieve the same reductions at lower costs.

This study's findings directly address the research question by demonstrating the substantial economic and environmental benefits of integrating CDR technologies into deep decarbonization strategies for the electric power sector. The results highlight the significance of CDR in reducing the costs associated with achieving stringent emission reduction targets. The robustness of these findings across multiple sensitivity analyses reinforces the importance of considering CDR in future decarbonization planning. The findings contribute to the field by providing a detailed, power-sector focused analysis using a state-of-the-art model, offering insights often missing in broader energy system analyses. The study's conclusions support the inclusion of CDR options, especially BECCS and DAC, in future modeling exercises to accurately reflect the complexities of decarbonization pathways.

The study concludes that CDR technologies, notably BECCS and DAC, play a crucial role in lowering the costs of deep decarbonization of the electric power sector, especially under stringent emission reduction targets. The choice of CDR technology is sensitive to cost assumptions and biomass availability, with BECCS favored under typical conditions but DAC becoming more competitive with rising biomass costs. Future research should focus on integrating CDR into broader economy-wide models, encompassing various factors such as policy design, lifecycle emissions of biomass, and geological CO2 storage characterization, to provide even more comprehensive decarbonization pathways.

The analysis is based on a single-year static equilibrium model, which may not fully capture the dynamics of a multi-year transition. The model doesn't explicitly consider operational constraints, ancillary service markets, or sub-hourly details that could influence the results. Demand is fixed across scenarios and could provide additional flexibility in real-world systems. The analysis also focuses primarily on the economic aspects of CDR deployment and doesn't delve deeply into lifecycle environmental impacts or land use changes associated with different CDR technologies.