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At least 199 records · Page 11

Iteration-based Linearized Distribution-level Locational Marginal Price for Three-phase Unbalanced Distribution Systems

Distributed energy resources (DERs) are rocking the utilities’ business landscape. It calls for competitive market environments that incentivize DERs to form maximum operating efficiency. Among proposed pricing schemes, distribution-level locational marginal price (DLMP) is effective in signaling the marginal generation cost differences driven by energy losses and network constraints. It can be derived from a distribution-level optimal power flow (OPF) framework, as it essentially presents the sensitivity of optimized generation cost towards incremental loads. However, due to the high resistance-to-inductance ratio and unbalanced characteristics of distribution networks, computational affordable DLMPs are highly challenged. This article provides a linear-approximated DLMP that can be solved efficiently and generalized to account for reactive power flow, three-phase unbalanced loads and meshed network structure. The successive linear programming technique is introduced to enhance the model accuracy. Case studies on an IEEE 123-Bus system validate its accuracy against a nonlinear benchmark and capability in offering proper incentives.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Electrolytic Renewable Fuel Production Optimal Operation Investigation - H2@Scale: Cooperative Research and Development Final Report, CRADA Number CRD-19-00818

This work explored the optimal design and operation of electrolytic hydrogen production from renewable power. While there are many financial incentives for renewable hydrogen, this work investigated the effects of Low Carbon Fuel Standards (LCFS) on the hydrogen breakeven cost. To this end, this project developed optimized operational strategies for electrolytic hydrogen facilities in the California. Four specific model projects were used as the basis for the analysis. Three model projects will be located in California and one in Texas or the Midwest to be determined during the project. All projects include interconnection to the natural gas grid as a method of transport for the product fuel and the hydrogen cases will also consider alternative modes of transport. The operational optimization will maximize project return through fuel production and grid services based on future scenarios for the value of each. The effort will rely on modeling tools developed by NREL and the UCI for grid modeling as well as the integrated resource planning tool (IRP), RESOLVE, which is the official IRP tool used by the California Public Utility Commission (CPUC). The development of this project can help to inform future hydrogen deployment, policy and regulation makers, research and development decisions, and private and public investment.

08 HYDROGEN↗

Techno-Economic Analysis for Co-Processing Fast Pyrolysis Liquid in Fossil Refineries

Recent work at the National Renewable Energy Laboratory (NREL) and throughout the bioenergy community has highlighted incentives associated with co-processing bio-intermediates in existing refineries to reduce capital costs associated with renewable fuels and chemicals production and reduce overall risk for emerging biomass conversion technologies. This presentation summarizes the techno-economic analysis results from the NREL-Petrobras collaboration that focused on refinery integration of fast pyrolysis oil through co-processing in the fluid catalytic cracking (FCC) process. The NREL-Petrobras work highlights the economic opportunity for refiners to engage in co-processing for low-carbon products and introduces the risks for refiners based on variability in crude and fossil-product markets. The NREL-Petrobras results also serve as a basis to inform policy design that reduces economic risk for refinery co-processing and repurposing opportunities. The final topics in the presentation highlight experimental capabilities and emerging analysis approaches at NREL and partner laboratories that support the development and commercial deployment of refinery utilization strategies.

bio-fuels↗

Multi-State Transportation Electrification Impact Study: Preparing the Grid for Light-, Medium-, and Heavy-Duty Electric Vehicles

Recent U.S. Environmental Protection Agency (EPA) notices of proposed rulemakings for GHG emissions standards for light-, medium-, and heavy-duty on-road vehicles would accelerate ongoing advancements already happening in the industry because of private investment, consumer demand, state-level policies, and federal incentives. As the EPA finalizes these regulations, questions persist regarding the cost of the requisite charging infrastructure and associated upgrades to the nation's electric grid. With support from the U.S. Department of Energy, U.S. Joint Office of Energy and Transportation, and the EPA, a multidisciplinary team conducted a Multi-State Transportation Electrification Impact Study that quantitatively assesses the incremental investment necessary to enable the levels of vehicle electrification expected to be induced by pending EPA regulations and to estimate the potential value of deferred investments in electric distribution infrastructure stemming from proactive vehicle-grid integration planning and deployment. This study finds the simulated incremental capital cost of charging infrastructure (including grid upgrades) to be at least 2.5 times smaller than the lifetime net benefits of vehicle electrification (including fuel savings but excluding the value of avoided emissions). Additionally, the incremental distribution grid upgrade cost of the EPA Action-Unmanaged scenario was found to be approximately 3% of existing utility distribution system investments (on an annual basis). Finally, the potential for managed charging to defer distribution grid upgrades was found to be significant with costs found to decrease from $2.3 billion to an incremental cost of $1 billion across five states in the Action-Managed scenario (relative to the No Action-Unmanaged scenario).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Transportation Electrification Impact Study (TEIS)

Recent U.S. Environmental Protection Agency (EPA) notices of proposed rulemakings for GHG emissions standards for light-, medium-, and heavy-duty on-road vehicles would accelerate ongoing advancements already happening in the industry because of private investment, consumer demand, state-level policies, and federal incentives. As the EPA finalizes these regulations, questions persist regarding the cost of the requisite charging infrastructure and associated upgrades to the nation's electric grid. With support from the U.S. Department of Energy, U.S. Joint Office of Energy and Transportation, and the EPA, a multidisciplinary team conducted a Multi-State Transportation Electrification Impact Study that quantitatively assesses the incremental investment necessary to enable the levels of vehicle electrification expected to be induced by pending EPA regulations and to estimate the potential value of deferred investments in electric distribution infrastructure stemming from proactive vehicle-grid integration planning and deployment. This study finds the simulated incremental capital cost of charging infrastructure (including grid upgrades) to be at least 2.5 times smaller than the lifetime net benefits of vehicle electrification (including fuel savings but excluding the value of avoided emissions). Additionally, the incremental distribution grid upgrade cost of the EPA Action-Unmanaged scenario was found to be approximately 3% of existing utility distribution system investments (on an annual basis). Finally, the potential for managed charging to defer distribution grid upgrades was found to be significant with costs found to decrease from $2.3 billion to an incremental cost of $1 billion across five states in the Action-Managed scenario (relative to the No Action-Unmanaged scenario).

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗

Community-Scale Energy Efficiency Assessment for Zero Net Energy Using the URBANopt Simulation Platform: Preprint

This project explored an innovative modeling approach for assessing the energy efficiency potential of the existing low-income Oceano neighborhood, in unincorporated San Luis Obispo County, and its effects on renewable generation requirements for achieving zero net energy (ZNE). One particular challenge faced was ascertaining the technical energy savings potential across a large neighborhood in a timely manner. The project overcame this challenge through the use of the URBANopt simulation platform, developed at the National Renewable Energy Laboratory. URBANopt manages the automated model creation, simulation, and result aggregation for different design scenarios of existing or candidate buildings in a large neighborhood. Customized energy efficiency packages considered for the residential and commercial sector in the neighborhood included lighting, HVAC, plug load, water heating, envelope, and energy education measures. As a result of the analysis for the Oceano community, energy efficiency measures that are available through incentive programs may provide a 7.4% reduction in the required distributed energy resource (DER) size, corresponding to a 25,000 ft2 decrease in PV array area, to achieve ZNE. Through this work, a computational tool was developed and is being leveraged by the County of San Luis Obispo (CoSLO). The tool has enabled the CoSLO staff to perform similar analysis of the technical potential for energy efficiency, and an understanding of the DER asset requirements and potential savings in other communities within the county.

building energy modeling↗

Pathways of clean energy heating electrification programs for reducing carbon emissions in Northwest China

We report clean energy heating electrification programs provide a promising way to reduce carbon emissions from fossil fuel combustion and consumption. This work studies the cost competitiveness of clean energy heating technologies under three dynamic mechanisms: investment costs, subsidy policies, and operating costs with real data. It provides key insights into the cost competitiveness of the different heating technologies deployed in different areas, as well as their sensitivity to the three dynamic mechanisms. The results show that currently, the distinct heating programs are more cost-efficient in the urban area with existing heating networks. The average payback period of all district clean energy heating programs in the urban area is 14.9 years, while that of the individual clean heating programs is 24.7 years. The individual heating programs are becoming increasingly cost-competitive with the incentive mechanisms, especially the electricity pricing mechanisms. Moreover, individual heating technologies present remarkable advantages on flexibility and sustainability in the long run. According to the technology diffusion model proposed in this paper, the individual clean heating programs will occupy more than 50% of the market share in 2050 under the comprehensive effect of CAPEX, government subsidies, and OPEX. The real-world results and analysis render references to shape the pathway of clean energy heating electrification in Northwest China and other regions with a similar situation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Insights from FEED studies for retrofitting existing fossil power plants with carbon capture technology

Recent United States Department of Energy (DOE) sponsored front-end engineering design (FEED) studies for retrofitting existing fossil-fueled power plants with state-of-the-art carbon capture technology contain previously overlooked real-world design considerations for near-term deployment of carbon capture. Insights from examining seven recently published FEED study reports are summarized in this paper. This includes a discussion of the design, performance, and cost implications associated with (1) location-specific considerations such as water availability, land availability, and accessibility; (2) host-plant-specific factors such as flue gas specifications, allowable degree of integration between the capture system and host plant, and operational mode; and (3) miscellaneous factors such as market conditions, permitting requirements, and business case incentives. In conclusion, this manuscript highlights (1) water availability as a key design and cost driver, with host plant steam extraction increasing capture system cooling water availability, (2) modularization and constructability impacts on the number of capture trains, (3) the impacts of host plant operational mode and capacity factor on the business case for installing capture, and (4) the merit of continued research, development, and demonstration efforts addressing steam extraction, host plant tie-in at the stack, solvent reclamation and air emissions control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evaluating Impacts of the Inflation Reduction Act and Bipartisan Infrastructure Law on the U.S. Power System

The Inflation Reduction Act of 2022 (IRA) and the Infrastructure Investment and Jobs Act of 2021, commonly referred to as the 'Bipartisan Infrastructure Law (BIL),' collectively represent the largest commitment of the U.S. Federal Government to invest in the modernization and decarbonization of the U.S. energy system. The Congressional Budget Office (CBO) estimates that total support for the broad range of climate and clean energy programs, tax credits, and other incentives authorized through the two laws will exceed $430 billion from 2022 through 2031 (CRS 2022; CBO 2021, 2022). While the climate and clean energy provisions are numerous and have the potential to impact all aspects of the U.S. energy system from fuel and electricity production to final consumption in industry, transportation, and buildings, the provisions relevant to the electricity sector - in particular the suite of tax credits for clean generation, storage, and carbon dioxide ( CO 2 ) capture and storage - are expected to be some of the most consequential in terms of emissions reduction and clean energy deployment (Larsen et al. 2022; Jenkins, Mayfield, et al. 2022; Mahajan et al. 2022; Zhao et al. 2022). In this report, we detail the methods and results of a study estimating the potential impacts of key provisions of IRA and BIL on the contiguous U.S. power sector from present day through 2030. The analysis employs an advanced power system planning model, the Regional Energy Deployment System (ReEDS), to evaluate how major provisions from both laws impact investment in and operation of utility-scale generation, storage, and transmission, and, in turn, how those changes impact power system costs, emissions, and climate and health damages. While not exhaustive in capturing every provision, the analysis estimates the possible scale of power-sector impacts that could result from the modeled provisions in IRA and BIL. The study is structured around two scenarios to evaluate the potential impacts of both laws on the power sector: 1) No New Policy: A counter-factual scenario that reflects all Federal and state policies enacted as of September 2022, with exception to IRA and BIL, and assumes load growth consistent with the Energy Information Administration's Annual Energy Outlook 2022 (AEO22) Reference case (EIA 2022a); 2) IRA-BIL: A scenario reflecting all Federal and state policies enacted as of September 2022, including key IRA and BIL provisions, most notably the investment and production tax credits for zero-carbon emitting electricity generation and storage (ITC and PTC), the tax credit for CO 2 capture and storage (45Q), and the tax credit for existing nuclear plants (described further in Section 2.3). To account for the impacts of IRA and BIL on electrification, assumes increased load growth consistent with a scaled version of the Medium Electrification scenario from the Electrification Futures Study (Mai et al. 2018). These scenarios are simulated across seven sets of assumptions with varying projected future electricity market conditions, including technology costs and performance, natural gas prices, and the degree of availability, feasibility, and cost of development of renewable resources, electricity transmission, and CO 2 pipeline, injection, and storage infrastructure. In addition, we simulate two sensitivities on the 'policy' treatment in which we vary key assumptions pertaining to the realized value of the clean electricity ITC and PTC: 1) the cost of monetization of tax credits, and 2) the level of bonus crediting realized by project developers. We demonstrate that IRA and BIL have the collective potential to drive substantial growth in clean electricity by 2030, while reducing costs for consumers, mitigating climate change, and decreasing the human health impacts of power sector emissions. However, we also demonstrate that if expected cost improvements of clean technologies are not realized and/or constraints on deployment driven by factors such as supply-chain challenges, regulatory hurdles, and the social acceptability of energy infrastructure development limit the rate of clean energy and associated infrastructure deployment (such as transmission), then the share of clean generation achieved and the associated emissions benefits realized may be substantively reduced.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

2024 Buildings Technology Baseline: Dataset Documentation

The Buildings Technology Baseline is a curated and regularly updated dataset of current and projected performance, retail, and installed price data for all major building energy technologies needed to enable cost/benefit analyses. Building technology analyses require an up-to-date understanding of installation costs and cost-effectiveness of key building energy efficiency technologies. The dataset was assembled by Guidehouse during fiscal year 2024. Data was gathered from the 2024 National Residential Efficiency Measures Database (NREMDB), the 2023 Energy Information Administration Updated Buildings Sector Appliance and Equipment Costs and Efficiencies ("EIA Building Data Report"), DOE Lighting Market Model, the 2023 RSMeans database, and the 2020 Grid-Interactive Efficient Building Technology Cost, Performance, and Lifetime Characteristics ("GEB Data Report"), Lawrence Berkeley National Laboratory, various literature, as well as new data from online retailers, stakeholder interviews, and contractor databases in 2023 and 2024. The dataset has been reviewed by subject matter experts at NREL and DOE. The 2024 dataset release is intended to be a starting point for interested users to provide feedback. This database is not intended to provide specific cost estimates for a specific project. The cost estimates do not include any rebates or tax incentives that may be available for the measures. Rather, it is meant to help determine which measures may be more cost-effective. The National Renewable Energy Laboratory (NREL) makes every effort to ensure accuracy of the data; however, NREL does not assume any legal liability or responsibility for the accuracy or completeness of the information.

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↗

Systems Packages for Washington State Building Performance Standard Incentive Program: Phase 1 Analysis

Starting in 2026 Washington State building performance standards will come into effect that require commercial buildings larger than 50,000 sf to meet site energy use intensity targets. To support a state incentive program designed to encourage building owners to start complying early, we characterized the building stock energy use of 11 building types, analyzed 43 energy upgrade measures, and developed seven packages of energy upgrade measures using the ComStock energy analysis tool. Each energy upgrade package included from 4 to 17 energy measures consisting of lighting, HVAC, and envelope upgrades. Package savings were calculated for four priority building types using a sample of 35,000 buildings characterized by four building area bins, three climate zones, and two county types (urban and rural). Of the 28 package and building type combinations analyzed, 17 (61%) met or exceeded program energy savings targets and two packages met targets for all four building types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Bridging Control and Deployment: A Cross-Layer Analysis of Scalable Building Cluster Control

Building cluster control has emerged as a promising approach for enabling flexible and coordinated operation of distributed building systems, yet its transition from pilot demonstrations to routine grid-interactive operation remains limited. This paper argues that this gap cannot be explained by control algorithms alone. Instead, it arises from interacting barriers in communication infrastructure, data and semantic interoperability, uncertainty management, stakeholder participation, market design, and policy support. Accordingly, the paper reviews both technical and non-technical barriers to building cluster control. Technical challenges include heterogeneous devices and protocols, communication latency and reliability, distributed decision-making, and uncertainty propagation across aggregated loads. Non-technical barriers include user participation, stakeholder coordination, incentive allocation, and data governance. Existing solution approaches are synthesized, including semantic interoperability frameworks, edge and hierarchical communication architectures, distributed and transactive control strategies, uncertainty-aware optimization, policy mechanisms, and market reforms. Based on this analysis, two research directions are identified: testing infrastructures that can evaluate control performance under realistic multi-building conditions, and abstraction methods that allow building clusters to interact with other energy sectors through standardized flexibility representations. Overall, the paper provides a structured review of how building cluster control can move from isolated demonstrations toward reproducible, market-compatible, and grid-relevant implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An Agent-Based Modeling Approach for Spatiotemporal Optimization of Electric Vehicle Fast-Charging Station Demand

With increasing electric vehicle (EV) adoption, managing public fast-charging demand effectively is crucial to avoid grid strain. This study investigates the potential of using dynamic pricing schemes to address this challenge. Presented in this study is a scalable agent-based simulation framework, which is applied to a case study in Richmond, Virginia, that assumes a 50% EV adoption rate in 2040. Two pricing schemes are compared: (1) a dynamic-pricing scheme based on station utilization and (2) a dynamic-pricing scheme based on peak power at the station. These schemes are compared to two baseline scenarios: (1) unscheduled first-come, first-served and (2) scheduled with constant price. The study’s results suggest that dynamic pricing has the potential to influence EV charging behavior, inducing both spatial and temporal shifts, but does so at the cost of inducing inconvenience to EV drivers. The results suggest the peak-power dynamic pricing scheme has the potential to mitigate peak demand pressures on the grid with minimal inconvenience, offering a promising approach for sustainable EV charging infrastructure expansion.

33 - ADVANCED PROPULSION SYSTEMS↗

Initial Engineering and Design for CO 2 Capture from Ethanol Facilities

The Energy & Environmental Research Center, in partnership with the U.S. Department of Energy (DOE) and North Dakota ethanol producer Red Trail Energy, LLC (RTE) and with technical support from Trimeric Corporation and the KLJ engineering firm, completed an initial engineering design (IED) for a hybrid capture system to estimate associated costs for retrofitting the operational RTE ethanol plant. The project goal supports the DOE objective to achieve negative emissions using commercially available technologies to attain Technology Readiness Level 6+ from a facility emitting >100,000 tonnes of carbon dioxide (CO 2 ) annually. The RTE CCS (carbon capture and storage) Project is currently operating a CO 2 capture facility, adjacent to the RTE ethanol facility in western North Dakota, and injecting the CO 2 more than a mile below RTE property for permanent storage. This novel hybrid capture system would process about 310,000 tonnes of CO 2 annually for the RTE host site and includes CO 2 capture and compression from bioprocessing as well as capturing CO 2 produced from natural gas boilers. The bioprocessing capture process, based on past RTE studies investigating ammonia liquefaction technology with CO 2 produced from natural gas boilers captured utilizing chemical absorption with amine, was shown to be technically feasible for the RTE site. Activities conducted to support the project goal included 1) designing a hybrid capture system using CO 2 emissions from both bioprocessing and heat production at the host site facility; 2) conducting a pre-front-end engineering and design analysis of the hybrid capture system to include environmental health and safety, a constructability report, identification of permits, and corporate approvals; and 3) performing a techno-economic assessment in accordance with DOE’s methodology, as demonstrated by the bituminous baseline study. In addition, a life cycle assessment (LCA) was completed for the RTE site to estimate the carbon life cycle for ethanol-CCS implementation using the designed hybrid capture system to determine potential for net-negative carbon emissions. Results of the IED showed the hybrid system to be technically viable, with a moderate estimated cost of $55/tonne CO 2 captured for the hybrid system. The cradle-to-gate LCA showed preliminary net-negative carbon emissions potential anticipated from implementing a hybrid CCS system at a commercial scale. Recommended next steps toward potential implementation include hybrid capture system demonstration testing for detailed engineering and LCA model comparisons with low-carbon fuel incentive programs for financial support.

01 COAL, LIGNITE, AND PEAT↗

Decarbonization Scenarios in the United States: Comparing Biofuels Growth in Two Models - GCAM and BSM

Scenarios for deep decarbonization rely on biomass for biofuels, biopower, and bioproducts, often including negative emissions via carbon capture and storage or utilization. Despite the prominence of biomass in many deep decarbonization pathways, critical questions remain about biomass allocation, effects of transportation electrification, the pace of growth, and implications for agriculture and land use. We address these questions through a unique comparison of carbon pricing effects on the growth of biomass utilization and its effects on land use in the United States by comparing results from a multisectoral integrated assessment model, the Global Change Analysis Model [GCAM], with results from a biomass-to-biofuels system dynamics model, the Biomass Scenario Model [BSM]. We contribute to model comparison efforts by analyzing the biomass deployment needed for a scenario consistent with a "Middle of the Road" Shared Socioeconomic Pathway [SSP2] and a representative concentration pathway of 2.6 W/m2. The GCAM scenarios solve for global equilibrium conditions that are consistent with this pathway, including demands for biomass across all economic sectors and representing bioenergy with carbon capture and storage as a technology option. The BSM scenarios assess those biomass and biofuel results for the United States and identify challenges associated with that pace and amount of expansion. In the scenario analysis, we harmonize key factors such as carbon price trajectory, domestic ethanol fuel demand, ethanol blending, and arable land availability, and vary them in both models. In GCAM, we vary the carbon price, transportation electrification, ethanol blending constraints, and arable land availability inputs and the value of the carbon in land; in BSM, in addition to directly inputting certain GCAM results, we vary the maximum rate of biorefinery construction, flexibility of feedstock types across conversion processes, and policy incentives such as tax credits and renewable identification number payments. The selected carbon price trajectory results in a rapid increase in biofuel production in the United States, reaching about 9.4 EJ/year in 2060 in the highest scenario analyzed in GCAM. Results differ between the two models in timing and ultimate quantity of biomass and biofuel production. GCAM biofuel quantities generally exceed BSM amounts because CCS is applied to biofuel pathways in GCAM, and because of differences in capacity expansion and related dynamics of land allocation, biomass production, and price dynamics. These dynamics include rapid biorefinery capacity expansion in high demand cases. To satisfy this biomass demand, GCAM rapidly equilibrates land allocation, but the BSM limits the rate at which this re-allocation can occur. A further contrast with the equilibrium approach in GCAM is that the BSM represents a delay between planting and harvesting woody biomass resources. As a result of these model contrasts, feedstock costs in BSM increase more than in GCAM, and the absence of CCS in the BSM also reduces the relative economic attractiveness of biofuels production. The bottlenecks, lags, and price increases also lead to potential for volatility in feedstock price and land allocation to biomass in the BSM. GCAM has more biomass production than BSM in all scenarios, partly because of the broader, economy-wide coverage of GCAM, in contrast to BSM's exclusive focus on biofuels. In both models, trends like those of biofuels production were observed for biomass production: minimal growth without a carbon price and policy incentives, and increases with a carbon price, particularly with carbon capture and storage, because the inputs assume that biopower and biofuels decrease greenhouse gas emissions. In high policy scenarios, biomass demand is high, and the consequent high biomass prices due to the land re-allocation bottleneck in the BSM limit biofuel production even if the biorefinery capacity is expanded. However, because biomass prices do not increase as much in the low policy scenario, growth is slower and the land-reallocation bottleneck no longer dominates, such that the effect of increased capacity can be seen. Across both the models, a change in assumptions from less to more land availability increases biofuel production in both GCAM and BSM, as the upward pressure on feedstock price and volatility are both reduced.

biofuels↗

Techno-economic and environmental assessment of solar-based electrical vehicles charging stations integrated with hydrogen production

With the growing interest in adopting both commercial and residential electric vehicles (EVs) utilizing green renewable energy, the techno-economic assessment of EV charging stations with solar energy is a critical aspect of the transition to sustainable transportation. However, battery storage capacity for variable solar energy production is becoming increasingly less cost-effective due to the higher Lithium price. Complementing solar energy production and battery storage, the potential of combining green hydrogen fuel energy integration with solar energy for EV charging stations can provide a sustainable alternative to reach carbon-free transportation. This research aims to assess the technical and economic viability of grid-connected Photovoltaic (PV)-based EV charging stations across Kentucky based on existing EV load profiles. The study considers different PV system sizes, locations, orientations, and the impact of net metering policies and electricity tariffs on the profitability of the PV systems. Further, using excess PV energy, Lithium-Ion batteries will be charged, which will be assessed considering the techno-economic and environmental impacts of green EV charging stations. To further enhance green renewable energy production, we also investigated the feasibility of on-grid PV-based EV charging stations with Lithium-Ion batteries charged during low tariff periods. In comparison with these scenarios, we studied the potential benefits of integrating green hydrogen energy production using excess solar energy with and without governmental incentives. Furthermore, we assess the environmental impact of these green EV charging stations across Kentucky. Our study indicates that EV stations across Kentucky have similar techno-economic feasibility with insignificant deviation in the levelized cost of electricity, payback period, and PV energy fraction with/without Li-Ion batteries. However, with green hydrogen production, the marginal H 2 production cost indicates the first scenario (on-grid PV energy charging) is the most significant, roughly 10 USD/Kg, which is similar to 1.5 times higher than the second (charging during low-tariff periods) and the third scenarios (power grid to satisfy the demand deficit - approximately 6.5 USD/Kg). From the environmental perspective, the second scenario would be a good option for either hybrid EV/H 2 or EV charging stations in Kentucky, factoring in the hydrogen production cost and the carbon footprint.

08 HYDROGEN↗

Evaluation of Performance Variables to Accelerate the Deployment of Sustainable Aviation Fuels at a Regional Scale

An increase in jet fuel consumption and its associated emissions across the world have led to the need for alternative technologies to produce sustainable aviation fuels (SAF). One option to produce SAFs is to utilize waste or biomass-based feedstocks that has the potential to reduce greenhouse gas emissions by 50% or more compared to conventional jet fuel. However, there is a lack of understanding of how the synergistic effects of key performance variables could hinder or help the deployment of aviation fuels on a regional scale. Here, we assess the implications of key variables-including type and quantity of waste/biomass feedstock availability near the airport, cost of SAF production, life cycle greenhouse gas (GHG) emissions, policies, and fuel/infrastructure logistics-on the deployment of SAF at Chicago's O'Hare International Airport. We consider three ASTM International-approved SAF technologies (Hydroprocessed Esters and Fatty Acids, Fischer-Tropsch, and Alcohol to Jet) that can be blended up to 50% with petroleum-based jet fuel. Results from our analysis show that woody biomass-based Fischer-Tropsch technology has the lowest fuel production costs ($2.31-$2.81/gallon gasoline equivalent) of all pathways, and it reduces life cycle GHG emissions by 86% compared to conventional jet fuel despite the higher availability of crop residues compared to either woody biomass or fats, oils, and greases. Also, infrastructure is available at O'Hare International Airport to blend SAF with Jet A fuel through three terminals directly connected to the airport via pipelines. Our sensitivity analysis shows renewable fuel incentives and feedstock price to be key performance variables affecting the production cost and deployment of SAF.

alcohol-to-jet↗