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At least 217 records · Page 12

MADWEC Techno-Economic Analysis: Cooperative Research and Development Final Report

The objective of this project was for the facility to conduct a techno-economic assessment of the Maximal Asymmetric Drag Wave Energy Converter (MADWEC), developed by the University of Massachusetts Dartmouth (UMass Dartmouth), used for powering remote monitoring and AUV charging systems compared to other existing power supply options. The assessment estimates capital expenditures (CapEx), operational expenditures (OpEx), and power performance for 18 scenarios with the purpose of identifying key cost drivers, comparing total system cost, and comparing the power performance of the power supply options in terms of required installed capacity and estimated theoretical annual energy performance. The scenarios include two end-uses: (1) AUV charging and (2) offshore remote monitoring); three power sources: (1) MADWEC), (2) photovoltaic (PV) solar buoy, (3) and traditional battery swapping); and three locations; (1) nearshore, (2) far-offshore, and (3) high-latitude). In addition, other project goals included developing high level installation, operation, and maintenance plans for each scenario.

16 TIDAL AND WAVE POWER↗

Update on Parallel Process Execution in the Next Generation System Analysis Model

As of the end of 2021, 88,880 metric tons of heavy metal (MTHM) (44,741 MTHM in dry storage; 44,139 MTHM in wet storage) of spent nuclear fuel (SNF) were stored at various reactor sites across the United States [1]. The Office of Storage and Transportation in the Department of Energy is planning for the transportation, storage, and eventual disposal of SNF and high-level radioactive waste (HLW). To aid in this effort and inform decision-makers about the backend of the spent fuel cycle, systems analysis tools capable of analyzing the various options with respect to SNF and HLW management are being used as well as continuously improved to meet the evolving needs of the program. System analysts typically use these tools to vary underlying assumptions (shipping rates, allocation priority, available facilities, start dates, etc.) and study the implications of these changes on site clearance schedules, campaign costs, transportation infrastructure acquisition, etc.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Update on Parallel Process Execution in the Next Generation System Analysis Model (NGSAM)

As of the end of 2022, it is estimated that over 90,000 metric tons of heavy metal (MTHM) of spent nuclear fuel (SNF) were stored at various commercial nuclear power reactor sites (both operating and shutdown) across the United States [1]. The Office of Storage and Transportation within the U.S. Department of Energy’s Office of Nuclear Energy is planning for the transportation, storage, and eventual disposal of SNF and high-level radioactive waste (HLW). To aid in this effort and inform decision-makers about the backend of the spent fuel cycle, systems analysis tools capable of analyzing the various options with respect to SNF and HLW management are being used as well as continuously improved to meet the evolving needs of the program. System analysts typically use these tools to vary underlying assumptions (shipping rates, available facilities, start dates, interim storage capacity, etc.) and study the associated system implications such as timing for clearing sites of SNF, various cost elements, transportation infrastructure acquisition needs, etc.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

FORCE-DISPATCHES Integration - Initial Demonstration

Integrated energy systems (IES) combine, in mutually beneficial ways, power from variable renewable energy sources and nuclear power plants (NPP) to improve economic viability under uncertain market and weather conditions. The open-source Framework for Optimization of Resources and Economics (FORCE) tool suite, developed at Idaho National Laboratory (INL), has enabled comprehensive modeling and simulation of IES. The capabilities within FORCE include grid portfolio optimization through the Holistic Energy Resource Optimization Network (HERON) and the transient process model analysis library HYBRID, among others. Continuous efforts and investments from the IES programs have been made to expand and improve the versatility of the FORCE toolset in fiscal year 2022. Code-coupling and cross-tool communication have been important methods for improving this versatility. This report focuses on an additional workflow in the HERON tool for capacity and dispatch stochastic optimization through integration with the external tool Design Integration and Synthesis Platform to Advance Tightly Coupled Hybrid Energy Systems (DISPATCHES). DISPATCHES was primarily developed by the National Energy Technology Laboratory, in collaboration with other national laboratories, which included INL, universities, and industry partners. It is coupled to a library of algebraic models for specific plant components, and to a framework for stochastic optimization different from that provided in the current Risk Analysis Virtual Environment (RAVEN)-running-RAVEN algorithm in HERON. HERON currently conducts stochastic optimization via an outer-inner loop: it optimizes over variable capacity on the outer loop, and at each step within the capacity parameter space, conducts an inner optimization over scenarios (of market signals, demand, and/or weather patterns) and hourly dispatch throughout a user-specified number of years. On the other hand, DISPATCHES conducts stochastic optimization via an “all-at-once” strategy in which capacity variables are optimized at the same level as dispatch variables, as all scenarios are considered at once. The latter method works especially well for projects of limited size and project length, as the necessary computational power and memory increases with the number of variables and scenarios. The new capability to use the DISPATCHES workflow in HERON enhances standalone simulations by leveraging FORCE tools—namely, the economic metrics from the Tool for Economic Analysis (TEAL) and reduced-order model (ROM) sampling from RAVEN. The initial demonstration of the DISPATCHES workflow simulates an existing nuclear-case flowsheet within the DISPATCHES repository—this models a NPP with a secondary revenue stream for hydrogen production. Electrical output from the plant is converted to hydrogen via a proton-exchange membrane (PEM) electrolyzer, hydrogen tanks are used for storage, and an additional turbine is added for hydrogen combustion. Continued work regarding this FORCE-DISPATCHES integration will include automatic generation of DISPATCHES models from HERON inputs, offering analysts the option of using either the RAVEN-runsRAVEN or DISPATCHES workflow to solve technoeconomic optimization problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Transmission Alternatives for California North Coast Offshore Wind, Volume 4: Cost-Benefit Analysis Report

The purpose of this report is to compare the costs and benefits of installing offshore wind power plants with capacities up to 500 megawatts (MW) in the Humboldt Wind Energy Area offshore California, focusing on identifying the costs related to transmission upgrades and possible alternatives such as energy storage. We identify several options that result in lower costs than upgrading transmission to provide full deliverability. Our estimates of the levelized cost of energy (LCOE) assuming full deliverability range from $80/MWh for a 144-MW plant to $73/MWh for a 480-MW plant with a 2030 commercial operation date; however, the additional cost of transmission upgrades increases these values to between $86/MWh and $98/MWh. Based on curtailment and revenue estimates developed using a production cost model, the LCOEs for plant capacities of 144 MW and 168 MW with Energy Only deliverability are lower than the combined cost of energy and transmission upgrades for full deliverability. The addition of a 4-hour, 15-MW battery energy storage system increases revenue for both plant sizes, with the 144 MW + storage scenario producing the most revenue relative to LCOE.

17 WIND ENERGY↗

Techno-economic analysis of non-aqueous hybrid redox flow batteries

Renewable energy has become indispensable to improving human life, but its growth is hampered by a lack of cost-effective energy storage systems to solve the intermittency problem. Non-aqueous hybrid redox flow batteries (NAqHRFBs), based on lithium metal anode and organic redox molecules (redoxmers), have been investigated as an attractive energy storage option because of their high cell voltages and energy densities compared to other redox flow battery candidates. However, little is known about the economic potential of NAqHRFBs, as well as the operational and materials impacts. This research establishes a techno-economic model to analyze the capital costs of NAqHRFBs with selected organic redoxmers, including 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO). Sensitivity analyses for current density, area-specific resistance, cell voltage, electrolyte composition, redoxmer price, and equivalent molecular weight indicate the key factors in controlling NAqHRFB capital cost. To make the current NAqHRFB cost-effective, the first priority is to increase the operation current density over 10 times of those used in lab-scale tests, followed by adjusting redoxmer-related characteristics to afford more cost reduction space such as decreasing the unit price by ~20 fold. The results have shed light on potential material development and system engineering directions to make NAqHRFBs viable for renewable energy storage.

25 ENERGY STORAGE↗

Uncertainty Visualization for Renewable Energy Potential

In this paper, we present the reV (Renewable Energy Potential) Dashboard, an interactive browser-based tool for uncertainty visualization and data exploration built using customized plotly dash components. With continuing development and utilization of computational models to study the power sector there is an increasing need for data-driven visualization tools which allow scientists, researchers, and engineers to interact with their data in real-time. Our principle motivation for developing this interactive uncertainty visualization was to provide domain scientists and modelers a platform which allows them to better understand and communicate scientific findings stemming from intricate information encoded in their data that is otherwise difficult to capture by conventional analysis. The development of customized dashboard components using the React programming paradigm, combined with fully pre-processed data, allows for users to select a variety of data options to update and manipulate the visualization in a straightforward computationally efficient manner.

dashboard↗

Light-Duty Vehicle Choice Modeling and Benefits Analysis (van018)

The U.S. Department of Energy’s Vehicle Technologies and Hydrogen and Fuel Cell Technologies Offices (VTO and HFTO) support research and development of efficient and sustainable transportation technologies that will improve energy efficiency, minimize emissions, and enable America to use less petroleum. The analysis in this poster is based on technical progress goals established in VTO and HFTO in the years immediately prior to and including 2020, and it summarizes the estimated energy and emissions benefits corresponding with achievement of those goals. The goals span research activities on batteries, electric drive technologies (EDT), combustion, lightweight materials, fuel cells, and hydrogen storage. The Automotive Deployment Options Projection Tool (ADOPT) is used to estimate the benefits for light-duty vehicles. ADOPT is a vehicle choice and stock model that estimates vehicle technology improvement impacts on sales, energy, and emissions. It includes all the existing vehicle options for realism, estimates their sales using extensively validated consumer preferences, creates new market-driven vehicle options through time, and rolls up sales to estimate energy and emissions. ADOPT takes in technology progress assumptions and applies these to the modeled vehicles through time. The assumptions are represented by a No Program scenario that reflects the technology improvements assumed to occur without further contributions from VTO or HFTO, and a Program Success scenario under which VTO and HFTO program goals are realized. The benefits are calculated by comparing ADOPT's estimated national-level energy and emissions resulting from the Program Success relative to the No Program scenario. By 2050, the Program Success scenario results in 11% less annual petroleum consumption and 10% less annual carbon emissions than the No Program scenario.

ADVANCED PROPULSION SYSTEMS↗

An Updated Life Cycle Assessment of Utility-Scale Solar Photovoltaic Systems Installed in the United States

Given the high deployment targets for solar photovoltaics (PV) needed to meet U.S. decarbonization goals, and the limited carbon budget remaining to limit global temperature rise, accurate accounting of the energy-use and greenhouse-gas emissions over the life-cycle of PV systems is needed. In the United States, most PV systems are large utility-scale systems which use single-axis trackers and central inverters, which are not commonly examined in existing life-cycle assessment (LCA) literature. In this study, we present a cradle-to-grave LCA of a typical silicon U.S. utility PV (UPV) installation which is consistent with the utility system features documented in the annual NREL PV system cost benchmark reports. We analyze and present results for four main metrics: cumulative energy demand (CED), greenhouse gas (GHG) emissions, energy payback time (EPBT), and carbon payback time (CPBT). We consider six primary manufacturing options: three based on an imported PV module supply chain (comparing low-carbon imports, high-carbon imports, and average imports), and three based on a potential domestic PV module supply chain (comparing low-carbon U.S. regions, high-carbon U.S. regions, and average U.S. regions). These manufacturing options were then paired with installation locations to create six main cases: low-carbon options were installed in Phoenix (Arizona), high-carbon options were installed in Seattle (Washington), and average options were installed in Fredonia (Kansas). These locations were selected to represent a range of irradiance and grid mixes in the United States, in order to illustrate the likely range of EPBTs and CPBTs possible across the United States. For all six cases, a sensitivity analysis for end-of-life (EOL) handling was explored to capture current and future management options: landfilling, partial recycling, and high-quality recycling. For the purposes of this report, the benchmark system was defined to use an average imported supply chain with partial recycling, installed in Fredonia (Kansas). CED results show ratios at or below 0.1 MJ oil-eq /MJgenerated which demonstrates efficient use of primary energy resources (below a 1:1 ratio), and represents a slight improvement over previous results in literature. GHG emissions per kWh range from 10-36 g CO 2 e, which are consistent with or lower than previous results published by NREL and IEA-PVPS. We use a graphical approach for calculating EPBT and CPBT in this report, which improves upon methods typically used in literature by accounting for non-linearity and avoiding data quality issues associated with long-term projections. EPBT was determined to vary from 0.5 to 1.2 years, with a benchmark EPBT of 0.6 years; CPBT was shown to vary from 0.8 to 20 years, with benchmark CPBT of 2.1 years, which is lower than other estimates from recent literature (typically >2 years).

14 SOLAR ENERGY↗

SOLAr Critical Infrastructure Energization (SOLACE): Leveraging Distributed Energy Resources to Provide Local Power

This document is a technical report based on a large-scale DOE-funded project conducted between 2019 and 2022. The project, called SOLAr Critical infrastructure Energization (SOLACE), is aimed at leveraging distributed energy resources (DERs) to provide local power to communities, feeders, or other regions. The project included a particular focus on high-value critical loads such as municipal water supply, telecommunication hubs, and disaster shelters. The key developments of the project were: (1) A comprehensive pre-event power system analysis methodology that identifies and characterizes the viable local power options. (2) A DMS-based example control system for activating and operating the local power solution during a time of crisis. (3) Grid-forming inverter technology to enable isolated local power operation and black-starting. (4) Cyber-security considerations for isolated systems when wider-area communication may be offline. This report describes the overall process that identifies and assesses the viable DER-based local power solutions for a given facility, region, or community. The report documents the process, including the key analysis steps, tools required, data requirements, and recommended pass/fail criteria for each step. It also provides a sample implementation of this process through a test case. Finally, it provides details of how a viable pre-event plan can be selected and activated at go-time when an event has occurred.

14 SOLAR ENERGY↗

Systems Analysis and Optimization of Circular PET Packaging Supply Chains in the United States: Environmental and Socioeconomic Impacts

Many actions are underway at global, national, and local levels to address the plastic waste problem and transition toward a circular economy of plastics. Studies evaluating environmental and socioeconomic impacts of such a transition are lacking. Here, the purpose of this study is to conduct a national systems analysis of polyethylene terephthalate (PET) packaging supply chains in the United States. Material flow data was combined with environmental and socioeconomic indicators to evaluate and compare the sustainability of the linear PET packaging supply chain, current (2019) supply chain, and possible future circular supply chain options in the United States. Environmentally optimal circular US PET packaging material flows showed 31% and 38% savings of GHG emissions and energy demand, respectively, with a circularity of 77% when compared with a linear supply chain. Additionally, the environmentally optimal system showed higher employment (29%) and wages (31%) than a linear system, but with a 5% decrease in revenue generation. A socioeconomically optimal circular PET supply chain showed increased employment (by 52%), wages (by 67%), and revenues (by 1%), with a circularity of 59% when compared with the linear system. However, it showed 14% higher GHG emissions than a linear system, indicating a trade-off between environmentally and socioeconomically optimal circular PET packaging systems. Overall, linear-to-circular material flow transition may not necessarily lead to increased revenues and decreased environmental impacts of the entire system, but it does benefit society due to increased employment and wages. Future systems analysis work should focus on improving data quality for environmental and socioeconomic dimensions.

PET↗

Sustainable Aviation Fuels from 30,000 feet – Scoping Report

A literature review, first principles analysis, and mapping of the airline-fuel infrastructure were performed to reassess the potential for various means of realizing a sustainable aviation sector. The literature review found a plethora of technical methods to make the airline industry net-zero CO 2 but limited work on the emergent barriers to sustainable aviation implementation such as land use, repurposing of fuel refining assets, and airline cost structures. First principles analyses of the energy, land, and costs of three broad net-zero strategies were performed to determine if sustainable aviation is feasible even in the most optimistic scenarios. Those methods were biomass-derived sustainable aviation fuel (SAF), fuel produced from CO 2 captured from the air and H 2 produced from water electrolysis (air-to-fuel: ATF), and offsetting fossil-derived Jet Fuel with carbon dioxide removal from the atmosphere (direct air capture and storage: DACS). Offsetting CO 2 emissions from using fossil Jet Fuel with DACS was found to consume the least energy, require the smallest quantity of land, and be the cheapest option. Replacing Jet Fuel with SAF was found to be only slightly more expensive than DACS but require substantially more land. ATF was found to be the most expensive and energy intensive option, though it did spare land relative to SAF. We found that calls to utilize waste biomass are well-founded, but wastes alone cannot cover the needs of the global airline industry. This means additional land will need to be allocated for biomass cultivation if SAF becomes the primary pathway to sustainable aviation. While differences were found in the performance of different types of biomass, those differences were small relative to differences with ATF and DACS. An analysis of the pricing structure of the airline industry suggests that some of the cost advantage of DACS may be erased by consumer sentiment which could explain why, to-date, the airline industry is focused primarily on SAF and to a lesser extent ATF. Further work is required to estimate the transportation, capital cost, and financing cost implications of greenfield and brownfield sites for SAF, DACS, and ATF. In the final report, we will analyze the potential to retrofit corn ethanol facilities to operate the ethanol-to-jet fuel process in response to decreasing gasoline demand as the electrification of road transport progresses. We will also construct a prioritization of land use to determine whether each net-zero CO 2 aviation pathway can make claim to the land required by their technology.

09 BIOMASS FUELS↗

Automated qualification data tool for high temperature metallic materials

This report describes a framework for storing, processing, and displaying qualification data for high temperature mechanical properties. The framework automates the process of generating design data from mechanical test results, for example for a data qualification report for the ASME Boiler \& Pressure Vessel Code. The framework has three parts: a data storage model with common formats for several types of typical mechanical property tests, a backend based on the \pycreep Python library for correlating and extrapolating the data to generate design material properties and allowable stresses, and a demonstration user interface for displaying, sorting, and filtering the data and exploring different options for modeling the design mechanical properties. The report discusses the options available for data processing, with illustrations from real test data on Alloy 617, Alloy 709, Alloy 740H, and Laser-Powder Bed Fusion 316H. The framework is complete for ASME type data analysis and will be used to store test data generated by the Department of Energy, Office of Nuclear Energy, Advanced Materials and Manufacturing Technologies sponsored qualification programs. Future work could extend the tool to other types of material properties and/or expand the demo user interface to make it accessible across the AMMT program.

36 MATERIALS SCIENCE↗

Tools to perform data reduction of time-of-flight data taken on BL4A (MagRef)—a Jupyter notebook approach

A collection of modules or tools to produce reflectivity profiles from data acquired with unpolarized and polarized neutron beams using the BL4A (MagRef) instrument at the Spallation Neutron Source. The Jupyter notebook approach offers transparency to the user on what is done with the data, and once the event mode data are stored as NumPy binary files empowers the user to perform the steps from their own laptop without the need for Mantid. The notebook offers two options for background subtraction, applies corrections for the wavelength dependence of the polarizer and flipper efficiencies, accounts for Zeeman energy splitting of the spin-flip channels, Qz-bins the data along contours of constant Qz, propagates errors and writes results in text format suitable for analysis with tools such as GenX.

Fitzsimmons, Michael [Oak Ridge Associated Univ., ↗

Technical and Economic Assessment and Gap Analysis of Advanced Nuclear Reactor Integration with a Reference Oil Refinery

Efforts to identify the most-economic methods to decarbonize several sectors of the U.S. economy are underway. Industrial processes such as crude-oil refining rely heavily on energy-dense and easily stored and transported fossil fuels for powering their operations. Refineries use large amounts of energy, primarily derived from fossil sources to separate crude-oil components, break down heavier hydrocarbons into lighter compounds, remove impurities, reform hydrocarbon molecules, and generate steam and electricity for pumps and compressors and other various auxiliary systems. Crude-oil refining operations such as distillation, cracking, desulfurization, reforming, utilities systems and some offsite facilities collectively account for most of the energy consumption. Other operations such as hydrocracking or hydrotreating also require hydrogen for developing hydrogenation reactions which involve substantial heating to keep the reactors at high-temperature and pressure levels. All heat and energy demands are typically provided by natural gas (NG), oil, or other fuels, which makes refinery industry one of the most-difficult sectors to decarbonize. Nuclear power is a viable and energy-dense source of clean electricity, heat, and hydrogen to provide the large, sustainable energy supply that the refining industry demands. The U.S. Department of Energy’s (DOE’s) Integrated Energy Systems (IES) program is working to perform research and development, design, economic siting, and risk analysis. This state-of-the-art work will enable the first on-site demonstrations and commercial deployments of advanced small modular nuclear reactors (SMNRs) integrated with industries such as chemical production, refining, iron and steel making, and more. IES seeks to demonstrate the ability of advanced nuclear reactors to meet the heat and power demands of these industries while reducing carbon emissions in a sustainable and cost-competitive way. The primary objective of this research effort is to analyze industrial-scale SMNR integration intended to decarbonize refining facilities. The foreseen outcome is the provision of reliable, cost-competitive, and sustainable clean energy, alongside a reduction of carbon emissions. Specifically, the focus of this work lies on meeting the reference facilities’ heat and electricity demands with nuclear power while also supplying clean hydrogen via integrated high-temperature steam electrolysis (HTSE). This report presents a comprehensive technical and economic assessment of the integration of advanced nuclear reactors into a reference refinery, leveraging financial incentives from the Inflation Reduction Act (IRA). The evaluation aims to explore the potential economic benefits and challenges associated with incorporating advanced nuclear reactors into refinery operations, particularly in terms of energy efficiency, economic implications and environmental impact. By examining both the technical feasibility and economic viability, this analysis seeks to identify existing gaps and propose solutions for successful nuclear integration implementation. The findings are intended to provide valuable insights for stakeholders considering the adoption of advanced nuclear reactors in the refining sector. A refinery reference-plant was developed, using an open-source refinery model, Petroleum Refinery Lifecycle Inventory Model (PRELIM) and expert assessment, as a base case for comparison with various nuclear integration options. The capacity of 100 kbd/day (KBD) of heavy crude-oil feed was selected to represent a general coking-type refinery with deep conversion capabilities (incorporating heavy-oil upgrading with FCC, coking, and associated hydrotreating process units), using a heavy crude-oil feed, which represents about 70% of U.S. refineries configurations. A summary of all cases considered in this study is shown in Table 1.

13 HYDRO ENERGY↗

Resilience Analytics for Interdependent Power and Water Distribution Systems

The occurrence of large-scale outages in power distribution systems (PDSs) caused, for instance, by extreme weather events has raised concerns on the cascading impact of the power outages on the resilience of other critical infrastructures, including water distribution systems (WDSs), whose healthy operation highly relies on the availability of power from PDSs. Here, this paper proposes an analytics model for quantifying the interdependence between the resilience of power and water distribution systems. The proposed model first performs spatio-temporal outage analysis on the PDS and WDS to determine the PDS power serving capability and the resulting cascading impact on the WDS water serving capability during the occurrence of disruptions. The resilience interdependence is then determined by a proposed set of six metrics calculated using the power and water serving capability profiles, which trace and quantify the cascading impacts of power outages in the operation of WDSs during the degradation and recovery stages. The proposed analytics model is implemented on the IEEE 33-bus power distribution system supplying power for pumping stations of a 15-node test WDS, considering multiple cases of water storage capacity, single and multiple outage scenarios, and availability of distributed generation. The numerical results demonstrate that the proposed metrics track the temporal and spatial interdependence between the resilience of power and water distribution systems, providing a mechanism to identify weak spots, and assess options to enhance the resilience of the critical water infrastructure.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Systems Analysis of Biomass and Coal Co-firing Power Plants with Deep Carbon Capture Toward Net-zero Emissions

Achieving a net-zero emission economy in the United States requires integrating diverse low-carbon and negative-emission technologies into the existing fossil fuel-dominant power fleet. Potential technologies from the low-carbon portfolio include renewable power, fossil power with carbon capture and storage (CCS), bioenergy with CCS (BECCS), and direct air capture (DAC). Renewable power is a clean energy source but has to pair with costly battery storage to provide dispatchable electricity. Fossil power with CCS offers dispatchable electricity yet still relies on DAC to offset residual emissions, even when deploying deep CCS with more than 90% CO2 capture. Coal-biomass co-firing with CCS, a subset of BECCS, is a reliable energy production technology that can be retrofitted from existing electricity generation units (EGUs). Power plant retrofit maximizes the use of the current U.S. coal power fleet without the need for large-scale deployment of new renewable power, battery storage, or DAC. Retrofitting coal-biomass co-firing with deep CCS in EGUs is a promising option, but not a universal solution. Biomass co-firing at a power plant introduces economic challenges and indirectly poses pressure on land and water resources. Meanwhile, retrofitting deep CCS affects plant efficiency and raises electricity generation costs. Overall, the technical feasibility and economic viability of plant retrofits vary across EGUs, as they are contingent upon the regional availability of biomass, unit-specific characteristics, site-specific fuel supply costs, and adjacent CO2 storage potential. Government incentives like 45Q can improve the retrofit viability, though the impact requires further quantification. A comprehensive analysis at the unit level is essential to address the question regarding the fate of the U.S. coal-fired electricity generation fleet toward the net-zero emission goal. This study conducts a systematic techno-economic-environmental assessment of EGUs to identify the viability of biomass co-firing and deep CCS retrofits in the U.S. coal-fired power fleet. Specifically, it characterizes the techno-economic performance of deep carbon capture, estimates life cycle greenhouse gas (GHG) emissions, and conducts a fleet-level assessment on retrofit viability. The key objectives are (1) to estimate the unit-specific performance and retrofitted cost under various biomass co-firing levels and CO2 capture rates; (2) to determine the possibility of reaching net-zero emission at the fleet level; (3) to quantify the cumulative capacities that are suitable for plant retrofits under current and future biomass supply scenarios; and (4) to improve the understanding of policy impacts on such retrofits to help the power sector’s transition to a net-zero economy. Techno-economic Model of Deep Carbon Capture. This study develops the performance and economic models for Monoethanolamine-based post-combustion CO2 capture at 95–99% capture rates. The process is simulated in Aspen Plus, analyzing the performance of carbon capture technology by varying the plant sizes, solvent lean loading, CO2 concentrations, and flue gas inlet temperature. Based on the key inputs and output parameters of CO2 capture, a reduced-order performance model of deep carbon capture is formulated. In addition, an engineering-economic model integrating the performance metrics is developed to estimate the capital as well as operation and maintenance (O&M) costs. Capital cost estimations follow the framework of the Integrated Environmental Control Model (IECM) and incorporate data regressions from three technical reports by IECM, the National Energy Technology Laboratory (NETL), and the National Renewable Energy Laboratory. The O&M cost estimation utilizes the actual inventory consumption rate and labor requirements. Both performance and cost models are embedded into IECM v13.0-beta, a fossil-fuel power plant modeling tool. Life Cycle Assessment of Power Plants. This study estimates the GHG emissions of power plants through life cycle assessment (LCA). The LCA scope includes fuel supply, combustion-based power generation, and CO2 transport and storage. The fuel-based life cycle module is designed following the framework of the NETL Unit Process Library and CO2U LCA Guidance Toolkit. The module is then incorporated into IECM v13.0-beta. The process-based LCA is applied to estimate the GHG emissions of coal and biomass supply, coal- and coal-biomass co-firing power plant operation, as well as CO2 pipeline transport and geographical sequestration. An uncertainty analysis is conducted to quantify the variability and uncertainty associated with the LCA using the Latin Hypercube Sampling (LHS) method. Fleet-level Assessment. This study evaluates the technical and economic feasibility of selected coal-fired EGUs, examines the role of tax credits in retrofit viability, and assesses the competitiveness of retrofitted units against other low-carbon options. Unit screening identifies EGUs for the study, focusing on new, efficient baseload units with air pollution controls. The power plant databases are then established to organize unit-specific information on performance and operating conditions from the relevant public databases. Biomass for co-firing retrofits is selected based on home and neighboring county availability, ensuring sustained operation with at least a 5% co-firing level. The CO2 storage site is determined by state-level storage potential, with ArcGIS Pro and NETL CO2 Saline Storage Cost Model used to identify the optimal balance between the nearest transport distances and affordable storage costs. The latest IECM v13.0-beta is then employed to configure and evaluate the eligible EGUs with or without the deployment of deep CCS and biomass co-firing. A supply curve is established to illustrate the cumulative installed capacity suitable for retrofits at different cost levels. A sensitivity analysis on tax credits for carbon sequestration is performed. Finally, a unit-level cost comparison is conducted among retrofitted plants, renewable power with battery storage, and abated fossil fuels with DAC. Expected Results. This study evaluates the technical, economic, and environmental metrics of each EGU across an array of CO2 capture rates and biomass co-firing level scenarios. Unit-level comparisons will identify critical factors influencing technical performance. The supply curves with and without tax incentives will provide insights into the impact of tax credits on biomass co-firing and CCS deployment. The cost comparisons with renewables and DAC-retrofit will assess the competitiveness of the retrofitted units. Life cycle emissions from each unit will be assessed to identify the scenarios under which net-zero emissions can be achieved. These analyses are expected to determine the total coal-fired capacity suitable for serving as a low-carbon energy source with or without tax incentives. The study results are novel in identifying optimal unit-specific strategies for producing carbon-neutral power, whether through retrofitting EGUs with deep CCS, biomass co-firing, DAC, or installing renewable power with battery. The findings will provide insight into nationwide efforts to ensure reliable, affordable, and low-carbon electricity. It also will inform investment decisions and policies in the deployment of deep carbon capture and negative emission technologies for a net-zero energy future.

Biomass Co-firing↗

Assessing the levelized cost of energy in South Korea

This study evaluates the levelized cost of energy (LCOE) for various energy technologies in the Republic of Korea (Korea) from 2023 to 2050, highlighting cost trajectories and potential crossovers among competing technologies. The analysis projects that, based on our set of assumptions, utility-scale photovoltaic systems achieve lower LCOEs than nuclear by 2030, while fixed offshore wind is expected to become cost-competitive with coal-fired generation around the same time. Floating offshore wind is projected to reach cost parity with coal in the late 2030s. Co-firing with natural gas and green hydrogen is identified as the highest-cost generation option due to high natural gas and green fuel costs and declining capacity utilization. This study further examines the potential for hybrid systems that integrate renewable energy with energy storage to serve as flexible, cost-effective, zero-emission alternatives to green hydrogen-based generation. Spatial LCOE assessments indicate that near-shore offshore wind sites may achieve lower costs despite modest capacity factors, contingent on site-specific factors such as grid integration and social acceptance. The findings indicate that renewable energy technologies are expected to experience continued cost declines, with solar photovoltaic becoming the most competitive energy source in Korea by 2030–2035. Incorporating social costs accelerates this shift from conventional alternatives.

Green hydrogen↗