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Carbon dioxide removal technologies, such as bioenergy with carbon capture and direct air capture, are valuable for stringent climate targets. Previous work has examined implications of carbon removal, primarily bioenergy-based technologies using integrated assessment models, but not investigated the effects of a portfolio of removal options on power systems in detail. Here, we explore impacts of carbon removal technologies on electric sector investments, costs, and emissions using a detailed capacity planning and dispatch model with hourly resolution. We show that adding carbon removal to a mix of low-carbon generation technologies lowers the costs of deep decarbonization. Changes to system costs and investments from including carbon removal are larger as policy ambition increases, reducing the dependence on technologies like advanced nuclear and long-duration storage. Bioenergy with carbon capture is selected for net-zero electric sector emissions targets, but direct air capture deployment increases as biomass supply costs rise., Carbon dioxide removal technologies such as bioenergy with carbon capture and direct air can influence power sector planning and operations. Here the authors show how carbon removal options lower costs of deep decarbonization and alter electric sector investments.

The emergence of variable renewable energy and battery storage technologies have fundamentally transformed the electric power sector and generated demand for analysis to understand their roles in future energy systems. Although unique characteristics of these resources are well-recognized and require more sophisticated methodologies to capture effectively, guidance is limited on best practices and research gaps. This paper selectively reviews recent literature and draws upon our collective modeling experience to offer recommendations to analysts and consumers of model outputs on approaches for modeling variable renewable energy and storage in long-term electric sector models. We focus on regional- and national-scale models with technological, temporal, and spatial detail given their prevalence in planning and policy analysis, though insights are applicable in other settings. The review highlights how the research frontier has advanced in representing renewables and energy storage over the past decade; however, given the many considerations involved with appropriately capturing salient economic and operational characteristics of renewables, there is a gap between commonly used models and state-of-the-art methods. Model simplifications can materially impact policy analysis associated with power sector decarbonization and high renewables deployment, and improving model representations of variable renewables can enhance insights for policymakers and other stakeholders. This review can point the way for improved methods for established models and designs for emerging ones.

The Paris Climate Agreement sets out an aggressive goal of limiting global average warming to well below 2 °C. As a first step, virtually all countries have put forth greenhouse gas emission reduction pledges in the form of nationally determined contributions, or NDCs, for the 2030 timeframe. Our analysis looks beyond the NDCs to explore potential post-2030 regional emissions reduction participation and ambition. For each scenario, we examine the implications for global emissions and long-term temperature. We then evaluate the regional consequences for energy systems and ensuing costs. We conclude by reflecting on the additional global abatement costs of tightening temperature goals. Overall, this study provides a multidimensional characterization of the scale of regional effort supporting climate outcomes, details important to decision-makers as they consider mid-century emissions targets, and long-run climate objectives.

Power sector decarbonization is an important pillar of climate mitigation efforts, but perspectives differ about the relative competitiveness of generation technologies and how limited portfolio approaches (e.g., where non-renewable generation options are prohibited) could alter the costs and likelihoods of reaching emissions reduction goals. The existing literature on impacts of technological availability and cost on electric sector planning typically use models that do not have sufficient technological, spatial, and temporal detail to adequately resolve the economic competitiveness of variable renewable energy vis-a-vis dispatchable generators. Using a state-of-the-art energy-economic model, this work examines impacts of technological availability and advanced generation technologies on U.S. electricity market outcomes across a range of regional, market, and policy contexts. We show that decarbonization costs are 11%–76% higher as technological options are removed from consideration (incremental compliance costs for a 95% CO2 reduction below 2005 levels are roughly twice as high when new nuclear, carbon-capture-equipped units, and transmission are not allowed). However, the economic and technical implications of limited portfolios depend on the market and policy contexts (e.g., costs are higher with stringent targets, more extensive end-use electrification, and lower gas prices) and the costs and capabilities of the remaining options. The analysis demonstrates how lower temporal and spatial resolution models likely understate the value of technology by omitting key economic and technical features of high variable renewable pathways. Additionally, the analysis quantifies how technological change can lower costs of emissions reductions by 7%–73% and how low-cost battery storage can provide a hedge against higher costs when technological portfolios are limited.

The spatial and temporal variability of renewable generation has important economic implications for electric sector investments and system operations. This study describes a method for selecting representative hours to preserve key distributional requirements for regional load, wind, and solar time series with a two-orders-of-magnitude reduction in dimensionality. We describe the implementation of this procedure in the US-REGEN model and compare impacts on energy system decisions with more common approaches. The results demonstrate how power sector modeling and capacity planning decisions are sensitive to the representation of intra-annual variation and how our proposed approach outperforms simple heuristic selection procedures with lower resolution. The representative hour approach preserves key properties of the joint underlying hourly distributions, whereas seasonal average approaches over-value wind and solar at higher penetration levels and under-value investment in dispatchable capacity by inaccurately capturing the corresponding residual load duration curves.

Jacobson et al. (1) aim to demonstrate that an all-renewable energy system is technically feasible. Not only are the study’s conclusions based on strong assumptions and key methodological oversights, but its framing also omits the essential notion of trade-offs. A far more relevant question is how renewable energy technologies relate to the broader set of options for meeting long-term societal goals like managing climate change. Even if the goal were to maximize the deployment of renewable energy (and not decarbonization more generally), Jacobson et al. still fail to provide a satisfactory analysis by glossing over fundamental implications of the technical and economic dimensions of intermittency. We briefly highlight two prominent examples, and then …

Results from four integrated assessment models show countries’ efforts to cut emissions fall towards the lower end of the social cost of carbon distribution, suggesting insufficient levels of ambition to meet the Paris Agreement goals. The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years1. An important policy task will be to assess and compare these contributions2,3. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.