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DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗
DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees C or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗
DOE OSTI2024

Towards Prospective LCA Using Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) Framework for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 Degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM(Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.

emissions↗
DOE OSTI2019

Techno-Economics of Cogeneration Approaches for Combined Power and Desalination From Concentrated Solar Power

For many decades, integration of concentrated solar power (CSP) and desalination relied solely on the use of conventional steam Rankine cycles with thermally based desalination technologies. However, CSP research focus is shifting toward the use of supercritical CO 2 Brayton cycles due to the significant improvement in thermal efficiencies. Here, we present a techno-economic study that compares the generated power and freshwater produced from a CSP system operated with a Rankine and Brayton cycle. Such a study facilitates co-analysis of the costs of producing both electricity and water among the other trade-off assessments. To minimize the levelized cost of water (LCOW), a desalination facility utilizing multi-effect distillation with thermal vapor compression (MED/TVC) instead of multistage flash distillation (MSF) is most suitable. The techno-economic analysis reveals that in areas where water production is crucial to be optimized, although levelized cost of electricity (LCOE) values are lowest for wet-cooled recompression closed Brayton cycle (RCBR) with MSF (12.1 cents/kWh e ) and MED/TVC (12.4 cents/kWh e ), there is only a 0.35 cents/kWh e increase for dry-cooled RCBR with MED/TVC to a cost of 12.8 cents/kWh e . In conclusion, this suggests that the best candidate for optimizing water production while minimizing both LCOW and LCOE is dry-cooled RCBR with MED/TVC desalination.

14 SOLAR ENERGY↗
DOE OSTI2013

Investigation of Gas Solid Fluidized Bed Dynamics with Non-Spherical Particles

One of the largest challenges for 21st century is to fulfill global energy demand while also reducing detrimental impacts of energy generation and use on the environment. Gasification is a promising technology to meet the requirement of reduced emissions without compromising performance. Coal gasification is not an incinerating process; rather than burning coal completely a partial combustion takes place in the presence of steam and limited amounts of oxygen. In this controlled environment, a chemical reaction takes place to produce a mixture of clean synthetic gas. Gas-solid fluidized bed is one such type of gasification technology. During gasification, the mixing behavior of solid (coal) and gas and their flow patterns can be very complicated to understand. Many attempts have taken place in laboratory scale to understand bed hydrodynamics with spherical particles though in actual applications with coal, the particles are non-spherical. This issue drove the documented attempt presented here to investigate fluidized bed behavior using different ranges of non-spherical particles, as well as spherical. For this investigation, various parameters are controlled that included particle size, bed height, bed diameter and particle shape. Particles ranged from 355 µm to 1180 µm, bed diameter varied from 2 cm to 7 cm, two fluidized beds with diameters of 3.4 cm and 12.4 cm, for the spherical and non-spherical shaped particles that were taken into consideration. Pressure drop was measured with increasing superficial gas velocity. The velocity required in order to start to fluidize the particle is called the minimum fluidization velocity, which is one of the most important parameters to design and optimize within a gas-solid fluidized bed. This minimum fluidization velocity was monitored during investigation while observing variables factors and their effect on this velocity. From our investigation, it has been found that minimum fluidization velocity is independent of bed height for both spherical and non-spherical particles. Further, it decrease with decreasing particle size and decreases with decreasing bed diameter. Shadow sizing, a non-intrusive imaging and diagnostic technology, was also used to visualize flow fields inside fluidized beds for both spherical and non- spherical particles and to detect the particle sizes.

09 BIOMASS FUELS↗
DOE OSTI2016

Status of FeCrAl ODS Irradiations in the High Flux Isotope Reactor

FeCrAl oxide-dispersion strengthened (ODS) alloys are an attractive sub-set alloy class of the more global FeCrAl material class for nuclear applications due to their high-temperature steam oxidation resistance and hypothesized enhanced radiation tolerance. A need currently exists to determine the radiation tolerance of these newly developed alloys. To address this need, a preliminary study was conducted using the High Flux Isotope Reactor (HFIR) to irradiate an early generation FeCrAl ODS alloy, 125YF. Preliminary post-irradiation examination (PIE) on these irradiated specimens have shown good radiation tolerance at elevated temperatures (≥330°C) but possible radiation-induced hardening and embrittlement at irradiations of 200°C to a damage level of 1.9 displacement per atom (dpa). Building on this experience, a new series of irradiations are currently being conceptualized. This irradiation series called the FCAD irradiation program will irradiate the latest generation FeCrAl ODS and FeCr ODS alloys to significantly higher doses. These experiments will provide the necessary information to determine the mechanical performance of irradiated FeCrAl ODS alloys at light water reactor and fast reactor conditions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Integrated Solar Thermochemical Reaction System (Final Report)

This report describes progress accomplished in a three-phase project that has advanced the concept for a Solar Thermochemical Advanced Reactor System (STARS) – a system that is designed to convert solar energy into storable/useful chemical energy – from Technology Readiness Level 3 to Technology Readiness Level 6. STARS accomplishes its objective by directing the heat from a dish concentrator onto a chemical reaction system, increasing the energy content of the feedstock, methane, a chemical fuel that is available from multiple sources including natural gas, landfills and anaerobic digesters. The system uses a parabolic dish solar concentrator, previously developed for electrical power generation, and a compact, process-intensive chemical reaction system based on micro- and meso-channel process technology (MMPT). The combined Dish-STARSTM system provides a solar augment to the incoming methane stream, increasing its chemical energy content by 20-30% while decreasing its carbon intensity. When the immediate chemical product, known as syngas, is directly used for power generation the result is electricity with approximately 20% less CO 2 emissions. Alternately, if the syngas is further reacted to produce valuable chemical products, such as hydrogen, the reduction in carbon emissions is retained and reduced carbon intensities can be attained for the chemical products. In a co-production mode, lowcarbon hydrogen or electricity plus various hydrocarbons (for example, methanol, olefins or plastics) can be produced. Over the course of this project, the efficiency of Dish-STARSTM was improved from a previous value of 63% to slightly over 70%, with results and analyses indicating a potential for values greater than 80%; manufacturing investigations identified fabrication methods for the MMPT components, proofed-out additive manufacturing for microchannel heat exchangers, developed equipment cost models and, together with on-sun testing, supported technoeconomic evaluations. If developed into commercial products, project results indicate the potential for the efficient use of concentrated solar energy in nearterm applications for electrical power generation and the production of chemicals, including hydrogen.

14 SOLAR ENERGY↗
DOE OSTI2025

Thermal Systems Modeling for Integration of Industrial Processes with Advanced Nuclear

Applying combined heat and power concepts to advanced nuclear reactors can enable increased nuclear utilization in the future clean economy, as well as provide safe and reliable clean energy to industrial systems. Analyses have been performed to evaluate the integration of nuclear energy with industrial processes for both clean electricity production and providing process heat for direct use to reduce emissions in the production of chemical commodities. The key research question that needs to be answered is: "What are the prospective approaches for integrating nuclear-generated heat energy into non-electric applications that can facilitate combined heat and power operations by advanced nuclear reactor systems?" This presentation will highlight several case studies showing conceptual designs for thermal delivery systems to integrate small modular reactor (SMR) process steam and electricity with industrial processes including oil refining, hydrogen production, and methanol production.

hydrogen↗
DOE OSTI2019

Thermal Energy Storage for Dispatchable Geothermal Power

Dispatchable generation refers to sources of electricity that can be turned on or off, or can adjust their power output accordingly to an order. Geothermal plants are usually used for base-load power rather than dispatchable power. Flexibility is a challenge for a geothermal plant because the heat source does not naturally respond quickly to changes in demand. The current state-of-the-art approach to address this challenge is to maintain the geothermal fluid flows at relatively steady rates while providing a bypass around the generation equipment as needed. Under part load, some of the geothermal fluid is pumped to the surface, bypasses the generation equipment, and is re-injected to the ground without extracting any useful enthalpy. This approach is robust but necessarily incurs high parasitic power draws at part load due to the constant, full-flow pumping power requirements. There are even more challenges and unknowns for steam and flash geothermal plants, which were the focus for this project. As a process improvement to this existing configuration of a dispatchable geothermal plant, we examined the use of a phase-change thermal-energy storage (TES) unit that will provide some “inertia” against temperature fluctuations. The TES phase change material (PCM) could be in the form of eutectic molten nitrate salts, organic sugar alcohols, or the like based on the required temperature. This configuration allowed the power plant to meet the ramp rate requirements while allowing the geothermal resource to drawn down at the duty-cycle-averaged extraction rate rather than the full-rated-output extraction rate. The project team performed an experimental and computational evaluation of a peak shaving technical approach that used thermal storage to switch between two nominal operating points: full rated power and 50% power. In the initial requirements definition phase, the team decided to examine the PCM/TES-enhanced geothermal plant in the context of a 40-MW two-stage flash plant operating in mid-Southern California. Steady-state process simulations were used to understand the equipment sizing and the energetics. Dynamic process simulations were used to understand the response rate of the system to changes in requested power output from the utility. The technical approach was also guided by a techno-economic analysis (TEA) and a high-level analysis of the reservoir. Recognizing that performance of the thermal storage was a key risk element, high-fidelity finite-element simulations of the PCM-TES heat exchanger were performed to better understand its performance and temporal response. These simulations were validated with a subscale PCM-TES experimental apparatus that mimicked the geometry of the full-scale system. The key outcomes of this Phase I project were that: 1) the PCM-TES heat exchanger met the target for gravimetric energy storage density, 2) the dispatchable geothermal plant met its target for response rate, 3) the peak shaving approach reduces the number of production wells and does not disturb the wellfield, and 4) the incentives for properly remunerating dispatchable operation were identified.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Geologic hydrogen: a review of resource potential, subsurface dynamics, exploration, production, transportation, and research opportunities

Hydrogen is a versatile resource with critical roles in decarbonization, industrial manufacturing, and energy integration. However, most hydrogen today is produced from fossil fuels, resulting in high emissions and energy consumption. Although low-carbon hydrogen production methods, such as steam methane reforming with carbon capture and renewable-powered electrolysis, are advancing, their high costs hinder large-scale deployment. Identifying alternative pathways for producing low-cost, low-emission hydrogen is therefore essential. Geologic hydrogen, referring to natural and stimulated hydrogen generated in the Earth's subsurface, has attracted growing attention as a potential source of sustainable, economically viable, and environmentally favorable hydrogen. This paper provides a comprehensive review of geologic hydrogen, covering its resource potential, origins, migration and trapping mechanisms, exploration techniques, production strategies, and pipeline transportation. It also identifies key knowledge gaps and proposes a roadmap for future research. The review indicates that geologic hydrogen has vast resource potential and can leverage existing subsurface technologies and geophysical exploration methods. However, major challenges persist, including uncertain hydrogen generation rates, limited understanding and control of serpentinization processes, costly transportation infrastructure, the lack of validated techno-economic analysis, and potential social and environmental issues. As the field is still in its early stages, progress will require interdisciplinary collaboration spanning geoscience, engineering, economics, environmental science, and policy and regulation.

42 ENGINEERING↗
NASA NTRS1990

Aeroacoustic flowmeter

The flowmeter is based on a measurement of phase difference between two points on the circumference of a pipe separated axially by an integral multiple of sound wavelength. Plane sound waves are generated aeroacoustically by a non-protruding ring cavity energized either directly by the flow or by a subsidiary flow of the same medium. The frequency of the aeroacoustic source varies with temperature and therefore the temperature can be obtained. In the case of steam flow, temperature can be measured independently and therefore from the measured frequency (or speed of sound), the quality of wet steam can be measured. The flowmeter is linear in velocity and no calibrations are required.

Shakkottai, Parthasarathy↗
DOE OSTI2022

GOOML - Real World Applications of Machine Learning in Geothermal Operations

GOOML (Geothermal Operational Optimization with Machine Learning) is a machine-learning based framework that enables geothermal power plant operators to explore optimization opportunities for their assets in an efficient and robust digital environment. Backed by real-world data sources, thermodynamic constraints and steamfield intelligence, the GOOML environment provides new tools to explore how to best operate steamfields as well as test new scenarios and configurations prior to implementation in the field. To prove the effectiveness of GOOML, we have undertaken optimization experiments using reinforcement learning (RL) to generate operational suggestions using a balance of mass-take targets, sustainability considerations and net generation. Our experiments use the GOOML construct to explore different field parameters and perform multiple reinforcement learning experiments. Like a comprehensive laboratory workbench, we can change out components of a steamfield to perform testing under a variety of conditions (restrict mass, increase pressure, reroute steam, etc.). This flexibility allows us to explore conditions that would require significant infrastructure changes in a real-world setting at a fraction of the cost and time in a digital environment. The results highlight the benefits of using digital twins and advanced data analytics for the geothermal industry.

forecasting↗
DOE OSTI2024

Condition-Based Maintenance of a Circulating Water System of a Canadian Nuclear Power Plant using Machine Learning and Statistical Tools

Canada Deuterium Uranium pressurized-heavy-water reactors (PHWR) are a type of nuclear power plant that generate clean and reliable energy. The scope of this work is to automate data analysis methodologies to inform a condition-based maintenance strategy of a circulating water system (CWS) of a PHWR. The multiunit CWS provides a continuous supply of water to cool steam condensers, even during transient scenarios, thereby improving the thermal efficiency. This work aims to develop a machine learning (ML) based approach to detect anomalies in heterogeneous data of a CWS in a PHWR to help inform a predictive maintenance strategy. The heterogeneous data include textual and numeric time series data for a PHWR. Natural-language-processing (NLP)-based models are used to analyze textual data contained in work orders and operator logs and an event-timeseries correlation detection method is applied to assist anomalies diagnoses for CWS. An ML model Robust Linear Model (RLM) is also used to remove the seasonal variations in the system variable distributions based on distributions of environmental variables. A machine learning model, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), trained on both original data and data without any seasonal variations will then be used to detect if an anomaly exists. Thus, by moving to an automated methodology to detect, classify, and forecast anomalies, the maintenance strategy would be based on component condition instead of a time-based schedule.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Carbon‐negative hydrogen from ethanol via catalytic oxidative reforming

Abstract This study evaluated a commercial technology for producing low‐ or negative‐carbon hydrogen through ethanol catalytic oxidative reforming, focusing on the life cycle greenhouse gas emissions, or carbon intensity (CI). Various scenarios were analyzed: (a) comparing corn ethanol (first‐generation or Gen1 ethanol) and cellulosic ethanol (second‐generation or Gen2 ethanol) as feedstocks; (b) assessing carbon capture and sequestration (CCS) for CO 2 from upstream fermentation; and (c) evaluating oxygen sourcing via air separation units vs. on‐site or off‐site water electrolysis using a proton exchange membrane. Findings indicate that the CI for hydrogen production using Gen2 ethanol from corn stover is lower than that of Gen1 corn ethanol. Additionally, using proton exchange membrane‐generated oxygen results in a lower CI than air separation unit‐generated oxygen, regardless of the sourcing method. Implementing CCS for the hydrogen production plant's evolved CO 2 is essential for achieving a net‐negative CI for hydrogen from Gen1 ethanol. All examined scenarios, including both ethanol generations, oxygen sources, and CCS applications, demonstrated a net‐negative carbon intensity, surpassing the life cycle greenhouse gas emissions threshold of 0.45 kg CO 2 e/kg to enable policy credits as outlined in the Inflation Reduction Act §45V. In comparison, the CI for hydrogen from steam methane reforming stands at 3.4 kg CO 2 e/kg with CCS and 9.4 kg CO 2 e/kg without CCS.

08 HYDROGEN↗
DOE OSTI2017

Pilot-Scale Silicone Process for Low-Cost Carbon Dioxide Capture. Final Scientific/Technical Report

GE Global Research has developed, over the last 8 years, a platform of cost effective CO 2 capture technologies based on a non-aqueous aminosilicone solvent (GAP-1m). As demonstrated in a previous funded DOE project (DE-FE0007502), the GAP-1m solvent has increased CO 2 working capacity, lower volatility and corrosivity than the benchmark aqueous amine technology. The current report describes the cooperative program between GE Global Research (GE GRC), and the National Carbon Capture Center (NCCC) to design, construct, and operate a pilot-scale process using GAP-1m solvent to demonstrate its performance at 0.5 MWe. (i) Performance of the GAP-1m solvent was demonstrated in a 0.5 MWe pilot with real flue gas for over 900 hrs. of operation using two alternative desorption designs: a Continuous Stirred Tank Reactor (CSTR), and a Steam Stripper Column (SSC). The CSTR is a one-stage separation unit with reduced space requirements, and capital cost. The alternative is a multi-stage separation column, with improved desorption efficiency. Testing the two desorber options allowed us to identify the most cost effective, and space efficient desorber solution. (ii) CSTR Campaign: The CSTR desorber unit was designed, fabricated and integrated with the pilot solvent test unit (PSTU), replacing the PSTU Steam Stripper Column at NCCC. Solvent management and waste water special procedures were implemented to accommodate operation of the non-aqueous solvent in the PSTU. Performance of the GAP-1m solvent with the CSTR was demonstrated for over 500 hrs. while varying temperature of the desorption (230 – 265 oF), solvent circulation rate (GAP-1m : CO 2 (molar) = 1.5 – 4), and flue gas flow rates (0.2 – 0.5 MWe). Solvent carry-over in the CO 2 product was minimized by maintaining water content below 5 wt.%, and desorption pressure at 7 psig. CO 2 capture efficiency achieved was 95% at 0.25 MWe (GAP-1m : CO 2 = 4 (molar), 230 oF desorption), and 65% at 0.5 MWe (GAP-1m : CO 2 (molar) = 1.5, 248 oF). Solvent loss was dominated by thermal degradation of the rich solvent. (iii) Steam Stripper Column Campaign: Higher expected cost of the solvent vs. aqueous amines makes solvent management a top priority to maintain the low cost for the process. During the testing of the GAP-1m solvent with the CSTR, thermal degradation of the rich solvent was found to be the main mechanism in solvent loss. Small amounts of water in the working solution were found to be an effective way to enable steam stripping, thereby lowering desorption temperature, and hence reducing thermal degradation. Steam stripping also increased working capacity by 30% due to a more efficient desorption. The concept was first tested in a glass stripping column (lab scale, GE GRC), optimized in a continuous bench scale system (2 kWe, GE GRC), and demonstrated in a 0.5 MWe PSTU at NCCC. No special system modifications were required to the PSTU to accommodate the testing of the non-aqueous GAP-1 solvent with the regenerator column. SSC was found to be more robust towards solvent entrainment (H 2 O < 35 wt.%). 90 – 95% CO 2 capture efficiency was achieved under stoichiometric conditions at 0.5 MWe (235 oF desorption, 2 psig and 19 wt. % H 2 O). Both CO 2 capture efficiency and specific duty reached optimum conditions at 18 wt.% H 2 O. Low amine degradation (< 0.05 wt.%/day) was recorded over 350 hrs. of operation. Controlled water addition to GAP-1m solvent decreased the desorption temperature, thermal degradation, and improved the CO 2 working capacity due to more efficient absorption and desorption processes. Under these conditions, the GAP-1m solvent exhibited a 25% increased working capacity, and 10% reduction in specific steam duty vs. MEA, at 10 oF lower desorption temperature. (iv) Techno-economic Analysis: The pilot-scale PSTU engineering data were used to update the capture system process models, and the techno-economic analysis was performed for a 550 MW coal fired power plant. The 1st year CO 2 removal cost for the aminosilicone-based carbon-capture process was evaluated at $48/ton CO 2 using the steam stripper column. This is a 20% reduction compared to MEA, primarily due to lower overall capital cost. CO 2 cost using the CSTR desorber is dominated by the economics of the solvent make-up. The steam stripper desorber is the preferred unit operation due to a more efficient desorption, and reduced solvent make-up rate. Further reduction in CO 2 capture cost is expected by lowering the manufacturing cost of the solvent, implementing flowsheet optimization and/or implementing the next generation aminosilicone solvent with improved stability and increased CO 2 working capacity.

0.5 MW Pilot↗
DOE OSTI2021

Case Study: Hybrid Carbon Conversion Using Low-Carbon Energy Sources in Coal-Producing States

The demand for more carbon efficient power sources and a decrease in natural gas prices has decreased the desire for coal power. This decrease in demand has led to massive job losses in coal mining regions over the past decade. The purpose of this project is to develop a hybrid energy system utilizing both a coal power plant and advanced reactor, which is competitive with natural gas by improving on profitability and decreasing carbon emissions. This report details the problem with a summary of the impact on the coal industry and the availability of renewable energy sources in the Appalachian region. Because of the geography of the region, variable renewable energy sources are not available without significant size and siting restrictions. However, biomass in the form of wood waste is abundant and can be used as a carbon neutral energy source. Combining biomass and coal processing, in addition to thermal power plants, can increase system profits and efficiency by providing peaking power and conversion opportunities for secondary markets. The electric load is based on publicly available demand data from Appalachian Power, which services the western Virginia and southern West Virginia in the Appalachian region. The demand information is combined by service, normalized, and scaled to an average demand of 1000 kW, which will be the basis for sizing the hybrid energy system. A traditional screening curve analysis for a coal plant and advanced reactor shows that the least cost design varies significantly based on the assumed discount rate and capital recovery period. An optimization program to size the design in TEAL based on the load curve gives 10 optimal designs, all with a negative resulting net present value (NPV) and a coal plant capacity of less than 15%. Including profits from selling captured carbon at a flat rate results in a positive NPV; however, the coal capacity factor only increases to about 40%. There are limitations with this optimization as well since the price of CO2 is likely to decrease as more is sold to the conversion market. The suggested design will combine coal power, an advanced reactor, and coal and biomass coprocessing to produce a variety of products that can be sold to the conversion market while increasing system efficiency. The analysis of conversion pathways for coal and biomass reveals that multiple options will need to be included in the analysis to produce the optimal system design. Three systems will be optimized and compared to determine the best design based on the figures of merit of total NPV and cost of carbon avoided. The first system will include a coal power plant and an advanced reactor that will sell electricity to the grid to meet demand and sell captured carbon to the conversion market. The second system adds a high-temperature steam electrolysis plant, which will utilize electricity during times of low demand to produce hydrogen and sell it to the conversion market. The third system adds biomass and coal processing with options for hydrocarbon oils, syngas to be produced for the conversion market, and electricity generation to power components within the system or provide peaking power. This analysis will be based on a new approach that combines traditional screening curve methods with a dispatch algorithm that optimizes the system based on the opportunity cost of different production options. The resulting optimization algorithm should provide results with less processing time than HERON’s decision tree method. The results from this analysis will determine an optimal design and reinforce the benefits of coal power when used in a hybrid energy system. The initial results show that the addition of a secondary market for carbon sales could result in a positive NPV and increases the capacity factor of the coal plant as compared to a design with only sales to the electricity market. The addition of more markets and additional coal consumption from biomass coprocessing could increase NPV further, replace carbon in other markets through the sale of biomass-derived hydrocarbons, and demonstrate the value of coal power technology.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Methods identifying cost reduction potential for water electrolysis systems

The electrochemical reduction of water to form hydrogen is an emerging alternative for energy storage, where hydrogen can be used as a transportation fuel, combusted to generate electricity, utilized in a fuel cell, or used as a feedstock for chemical synthesis. Techno-economic analysis (TEA) is a valuable tool for understanding how to inform research directions that could make hydrogen from electrolysis cost competitive with that produced by conventional means like steam methane reforming. The current state of knowledge on TEA of electrolysis systems suggests cost reductions are likely to result from advances in system design and materials, scale-up of manufacturing processes, and learning by doing effects as electrolysis deployment increases. Future directions and opportunities for TEA of electrolysis systems include dispatchable operation in wholesale power markets, optimization of capital cost and system durability, and analysis of pathways for hydrogen to support economy-wide decarbonization.

08 HYDROGEN↗
DOE OSTI2021

Reformer-electrolyzer-purifier (REP) assembly for hydrogen production, systems incorporating same and method of producing hydrogen

A high temperature electrolyzer assembly comprising at least one electrolyzer fuel cell including an anode and a cathode separated by an electrolyte matrix, and a power supply for applying a reverse voltage to the at least one electrolyzer fuel cell, wherein a gas feed comprising steam and one or more of CO2 and hydrocarbon fuel is fed to the anode of the at least one electrolyzer fuel cell, and wherein, when the power supply applies the reverse voltage to the at least one electrolyzer fuel cell, hydrogen-containing gas is generated by an electrolysis reaction in the anode of the at least one electrolyzer fuel cell and carbon dioxide is separated from the hydrogen-containing gas so that the at least one electrolyzer fuel cell outputs the hydrogen-containing gas and separately outputs an oxidant gas comprising carbon dioxide and oxygen.

Jahnke, Fred C.↗