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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Biogas Utilization in Refuse Power Plants (BURP 2 )

The BURP 2 project investigated the technical and financial viability of co firing biogas with waste coal for power generation while using carbon capture and sequestration to achieve net negative emissions. A comparative assessment integrating geospatial mapping, technoeconomic analysis, and life cycle analysis was carried out to evaluate retrofitting an existing coal fired facility in West Virginia, versus developing a new greenfield power plant in Kentucky located near a low quality coal resource. The study found that CO 2 capture rates of 90% or higher, in combination with biogas feedstocks such as animal manure, could significantly reduce global warming potential compared to plants using neither biogas nor CO 2 capture systems. Economic feasibility depended heavily on federal tax credits and proximity to fuel sources. In both greenfield and retrofit scenarios, access to biogas played a key role. Because the retrofit site was located close to existing biogas resources, it represented a feasible option, whereas the greenfield site, being far from pipelines or biogas sources, would require prohibitively expensive biogas transport infrastructure. Overall, the research showed that repurposing waste or low-quality coal with renewable biogas and CO 2 capture systems could provide a viable approach for reducing carbon emissions in power production, if biogas resources are easily accessible and available in sufficient quantities.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Synergistic Heat Pumped Thermal Storage and Flexibly Carbon Capture System

As the U.S. grid evolves toward a lower-carbon system, fossil generation assets need to operate in energy markets with high variable renewable energy (VRE) penetration while also decreasing carbon emissions. Current carbon capture and storage (CCS) technologies suffer from high capital cost and an inability to operate flexibly during periods of oscillating demand. The ARPA-E FLECCS Program Phase 1 was created to fund designing and optimizing innovative CCS processes that enable flexibility on a high-VRE grid. To address this need, the Colorado State University (CSU) Team won funding to design a synergized system of thermal energy storage, power generation, and flexible carbon capture to enable breakthrough system performance that achieves an LCOE <$75/MWh with >99% capture rate. This approach will target new or existing natural gas combined cycle power plants. The proposed design utilizes novel hot and cold thermal energy storage (TES) technologies that store low-cost, off-peak electricity as thermal energy to power CCS solvent regeneration and boost plant output during periods of peak demand. The design provides an overall optimized net present value (NPV) by maximizing low carbon power to grid while prices are highest using Storworks Power’s concrete TES technology. The team also capitalizes on decades of ION Clean Energy’s (ION) development in low cost and flexible pioneering solvent technology, which has proven reductions in energy consumption and overall cost of 28% and 38%, respectively, compared with state-of-the-art CCS.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Thermodynamically Stable, Plasmonic Transition Metal Oxide Nanoparticle Solar Selective Absorbers towards 95% Optical-to-Thermal Conversion Efficiency at 750 °C

Generation 3 (Gen) concentrating solar power (CSP) systems requires a high operation temperature ≥750°C to increase the power-cycle efficiency towards ≥50%. However, such a high operation temperature poses a notable challenge to high temperature materials. On the receiver side, a critical challenge is the lack of solar selective absorbers that demonstrate both high optical-to-thermal energy conversion efficiency η therm approaching 95% and long-term thermal stability at >750°C in air. Existing solar absorbers either have limited η therm ≤89% or deteriorate significantly within 500 h at 750°C; some of these also require costly vacuum deposition for stringent thickness control. Therefore, it is highly desirable to simultaneously achieve η therm ~95% AND high thermal stability at 750°C for future generations of CSP receivers. This project has investigated and developed low-cost, highly scalable spray-coated transition metal oxide nanoparticle (NP) pigmented solar selective coatings on various types of Inconel alloy tube sections that are thermodynamically stable at 750-800°C in air, maintaining η therm >94.3%(93.2%) under a solar concentration ratio of C=1000 after 60 simulated day-night cycles at 750ºC (800ºC) (1 cycle=12 h at 750 or 800°C and 12h ramping down to 25°C). We have also coated up to 48 inches long receiver tubes for preliminary solar testing under Norwich Technology’s parabolic trough systems, demonstrating notably improved performance in solar heating compared to benchmark Pyromark 2500 coatings. Two key innovations have been developed in this project: (1) We achieved an unprecedented high thermal efficiency >94% by optimizing the d-band optical absorption spectra of transition metal ions, engineering their valences and stoichiometry; (2) We were able to maintain or even slightly increase the efficiency when operating at 750°C in air by engineering the interdiffusion of transition metal ions between the coating and the Inconel substrate to our advantage. Featuring high-temperature solar spectral selectivity and thermodynamic stability in air, as well as low-cost, highly scalable solution-chemical synthesis and spray coating techniques, this innovation in solar selective absorber technology alone accounts for nearly 40% of the targeted reduction in the levelized cost of electricity (LCOE) from the receiver, thermal energy storage, and operation & maintenance combined by 2030, as proposed by the U.S. Department of Energy. For a 110 MWe CSP power plant, this LCOE reduction from the solar selective coating alone transfers to ~$\$ $1.9 M increase in annual profit based on a sales price of 10¢/kWh (or an annual sale of $50 M/year). The high solar absorptance (~98%) NP pigment materials developed in this project are equally applicable to volumetric receivers either as a coating or as bigger ceramic microspheres after sintering, potentially benefiting Gen3 falling particle CSP technologies. All these contributions facilitate the larger scale deployment of CSP systems with energy storage capability to address the intermittency issue of solar energy towards dispatchable solar electricity, bridging the temporal gap between peak solar electricity production and peak electricity consumption. The collaboration with Norwich Technologies and Brayton Energy in this project will also facilitate the future commercialization of this new solar selective coating technology developed in this SIPS project.

14 SOLAR ENERGY↗
DOE OSTI2022

Techno-Economic Analysis of CSP Incorporating sCO2 Brayton Power Cycles: Trade-Off Between Cost and Performance

Concentrating solar power (CSP) plants, thanks to the implementation of cost-competitive thermal energy storage, represent a dispatchable zero-emission alternative to traditional fossil fuel power plants. Next generation solar towers are expected to adopt high temperature receivers (>700 degrees C) coupled to sCO2-based power blocks, which optimal design is generally pushed towards the maximum cycle efficiency, often neglecting the economic impact with the justification that the main share of the capital cost is represented by the heliostat field. As result, the scientific literature lacks in comprehensive studies on techno-economic evaluation of CSP+sCO2 power plants addressing the important correlation that exists between system cost and performances. This work provides a preliminary techno-economic analysis of a solar power tower comparing four different cycle configurations for the sCO2 power block. Results have been reported on a Pareto front, highlighting the tradeoff between the plant investment cost and the solar-to-electricity plant efficiency. The trends of the optimization variables and cycle results have been reported to give useful insights about proper assumptions for the sCO2 power block design. The recompressed cycle with intercooling resulted as the most promising configuration and it has been further analyzed through a comparison of different solutions on the Pareto front. The cost breakdown of the sCO2 power block has been reported to highlight which components have the greatest impact on the overall plant cost and how they vary along the optimal solutions front. Eventually, the optimization has been repeated introducing a correlation to compute the turbomachinery isentropic efficiencies, to investigate their effect on the techno- economic analysis.

concentrated solar power↗
DOE OSTI2024

Blending low-carbon hydrogen with natural gas: Impact on energy and life cycle emissions in natural gas pipelines

In this article, hydrogen (H 2 ) is considered an alternative energy carrier to reduce greenhouse gas (GHG) emissions related to power and heat generation. A quantitative analysis was conducted to estimate the energy intensity and GHG emissions associated with the transportation of NG/H 2 mixture in high-pressure transmission pipeline, considering blending ratios up to 100% of low-carbon H 2 . The life cycle emissions were obtained by including upstream supply chain emissions, compression and transportation emissions, and end use combustion emissions of the NG/ H 2 blend. This study accounts for global warming potential of fugitive methane and H 2 emissions associated with pipeline transportation of the blend in the life cycle analysis. A significant reduction in the overall life cycle GHG emissions can be achieved when delivering the same volume throughput but at a reduced energy flow to end users. However, to maintain the nominal energy throughput of the pipeline regardless of the H 2 mole fraction, a maximum reduction of about 6% is obtained as the H 2 mole fraction in the blend will be practically limited to approximately 30% H 2 when the pipeline operates at capacity.

03 NATURAL GAS↗
DOE OSTI2020

Boosting energy efficiency of Li-rich layered oxide cathodes by tuning oxygen redox kinetics and reversibility

In developing electrode materials for next-generation Li-ion batteries, significant efforts have been given to the energy, power density and cycling stability, with much less (if any) attention paid to the energy efficiency – arguably, the most important practical measure for large-scale applications. This is particularly true for the oxygen-redox active electrodes, such as Li 1.2 Ni 0.13 Co 0.13 Mn 0.54 O 2 , the notorious energy-inefficient cathode that has an extremely high capacity but comes with large voltage hysteresis and voltage decay. Herein, we report the rational design of an energy-efficient Li-rich layered cathode along with high energy, power density and cycling stability enabled by tuning oxygen redox activity. Specifically, the target material Li 1.12 Ni 0.22 Co 0.13 Mn 0.52 O 2 exhibits an ultrahigh energy efficiency at 1 C (90.6%), high capacity (> 200 mAh g -1 ) with 98.9% retention and less than 150 mV decay at the extended 200 cycles. Overall, through direct comparison between the material and Li 1.2 Ni 0.13 Co 0.13 Mn 0.54 O 2 , we show that the compositional change, although slightly, greatly improves the oxygen redox kinetics and reversibility, thereby boosts energy efficiency. The findings offer a strategy to narrow the gap between scientific interest and practical application of oxygen-redox chemistry.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Reduced order modeling of a fluidized bed particle receiver for concentrating solar power with thermal energy storage

Oxide particles can serve as both the heat transfer and thermal energy storage (TES) media for next-generation concentrating solar power (CSP) plants where high-temperature TES enables dispatchable electricity from efficient power cycles with firing temperatures above 600 °C. Transferring heat to flowing particles at such high temperatures in a MW-scale central tower receiver remains a challenge for the CSP community. For indirect receivers with external walls to contain the particles, maintaining wall temperatures below the limits of structural metal alloys requires high heat transfer coefficients between the wall and the moving particle stream. Bubbling fluidization of downward-flowing particles can sustain high bed-wall heat transfer coefficients (> 1000 W m -2 K -1 ). Using experimentally calibrated correlations for bed-wall heat transfer and vertical particle dispersion, this study implements an axially discretized zonal model of a counterflow fluidized bed receiver to explore how bubbling fluidization may enable indirect cavity particle receivers. High bed-wall heat transfer coefficients support solar fluxes on angled cavity walls > 200 kW m -2 at peak aperture fluxes of 980 kW m -2 while maintaining external wall temperatures < 950 °C. Lateral particle dispersion enables hotter particles near the receiver leading edge to mix with cooler particles further from the leading edge to lower maximum external wall temperatures. Parametric studies identify how mass fluxes, particle dispersion, and solar concentrations impact indirect receiver thermal efficiency and uniformity for a CSP plant. These studies provide a basis for the design of indirect fluidized-bed cavity receivers that can maintain particle outlet temperatures for TES above 750 °C.

14 SOLAR ENERGY↗
DOE OSTI2020

Internal Insulation and Corrosion Control of Molten Chloride Storage Tanks

The National Renewable Energy Laboratory (NREL) is leading a multi-national team to validate the potential of a chloride-based molten-salt system that uses a ternary blend of MgCl2/KCl/NaCl to provide higher temperature thermal energy storage capability, thereby allowing for higher efficiency in the power block of next-generation concentrating solar power systems. While higher thermal stability, greater operating temperature, and a more efficient power cycle are possible, the molten chlorides present several unique challenges, including the design of internal liners to prevent the corrosion and thermal stress of alloy tank shells. This work discusses issues and potential solutions related to containment of molten chloride salt, specifically the design of the molten salt storage tanks.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2023

Physics-Informed Deep Learning-Based Proof-of-Concept Study of a Novel Elastohydrodynamic Seal for Supercritical CO 2 Turbomachinery

Supercritical carbon dioxide (sCO 2 ) power cycles show promising potential of higher plant efficiencies and power densities for a wide range of power generation applications such as fossil fuel power plants, nuclear power production, solar power, and geothermal power generation. sCO 2 leakage through the turbomachinery has been one of the main concerns in such applications. To offer a potential solution, we propose an elastohydrodynamic (EHD) seal that can work at elevated pressures and temperatures with low leakage and minimal wear. The EHD seal has a very simple, sleeve-like structure, wrapping on the rotor with minimal initial clearance at micron levels. Here, in this work, a proof-of-concept study for the proposed EHD seal was presented by using the simplified Reynolds equation and Lame’s formula for the fluid flow in the clearance and for seal deformation, respectively. The set of nonlinear equations was solved by using both the conventional Prediction–Correction (PC) method and modern Physics-Informed Neural Network (PINN). It was shown that the physics-informed deep learning method provided good computational efficiency in resolving the steep pressure gradient in the clearance with good accuracy. The results showed that the leakage rates increased quadratically with working pressures and reached a steady-state at high-pressure values of 15~20 MPa, where Q = 300 g/s at 20 MPa for an initial seal clearance of 255 μm. This indicates that the EHD seal could be tailored to become a potential solution to minimize the sCO 2 discharge in power plants.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Integration of Heat Pumps With Solar Thermal Systems for Energy Storage

This chapter considers the combination of solar thermal systems with an energy storage device known as a Carnot Battery which charges thermal storage with a heat pump or electric heater. Integrating these systems can provide a variety of advantages, such as dispatchable renewable power generation and electricity storage services. In this chapter a variety of methods for hybridizing these systems are described, and ideal cycle analysis is used to assess their relative merits.

Carnot Battery↗
DOE OSTI2022

Economic viability of using thermal energy storage for flexible carbon capture on natural gas power plants

Fossil fuel-based power plants generate 80% of the electricity in the United States and provide a reliable generation source for both base and peak power demands. These plants are expected to adapt to changes in environmental policies that will require carbon management with carbon capture and storage (CCS) representing a possible solution. Current solvent-based CCS has a detrimental impact on a power plant's performance due to large heat loads required for carbon capture solvent regeneration. This parasitic load restricts the power plant's output and operation flexibility. Therefore, this study evaluates the feasibility of using thermal storage technologies for natural gas combined cycle (NGCC) power plants coupled with CCS to minimize the impact of solvent regeneration and enable the plant to operate at peak power output. Thermal storage can minimize the impact of CCS on the power plant by providing the heat load required for solvent regeneration during times of peak demand which will allow the plant to operate unrestricted and at full power. In total, fifteen unique thermal storage configurations were evaluated from three thermal storage categories: Brayton cycle heat pump, vapor compression heat pump, and heat recovery steam generator steam extraction for storage. The viability of these systems was determined by evaluating each configuration on thousands of real-world Locational Marginal Pricing (LMP) profiles from the New York Independent System Operator and California Independent System Operator electricity markets using a techno-economic analysis. Afterwards, results were compared to the performance of a base power plant (NGCC with CCS and no thermal storage) to determine the impact of thermal storage on power plant economics. Overall, six of the thermal storage configurations performed better than base CCS enabled power plant on between 11.5% and 38.7% of the LMP signals evaluated. The best performing configuration was a vapor compression heat pump that used flue gas as the working fluid and had both hot and cold thermal storage units. This configuration performed better than the base CCS power plant on 38.7% of the LMP profiles. The results of this study show thermal storage can mitigate the economic impact of carbon capture solvent regeneration on NGCC power plants. Discussion focuses on the impact of electricity pricing on the optimal thermal storage system, the advantages and disadvantages of the systems evaluated, and identifies limitations with the study.

25 ENERGY STORAGE↗
DOE OSTI2025

New class of tritium breeders for fusion applications: Metal-reinforced composite breeders

Commercial fusion reactors operating on a D-T fuel cycle will require a steady supply of tritium to maintain the burning plasma required for continuous power generation. Since tritium has a short half-life, there is negligible natural abundance which necessitates fusion reactors to produce their own source of tritium. Tritium is most easily produced by surrounding a fusion reactor core with lithium (Li), which reacts under the intense neutron flux leaving the reactor core to form tritium and helium. Due to the hazards and technical challenges associated with surrounding a fusion reactor core with many tons of molten Li, other Li-bearing tritium breeder materials have been pursued. Unfortunately, most of the liquid breeders historically examined are exceedingly corrosive to reactor structural materials while many solid breeders in the form of ceramics are forced to make tradeoffs between Li content and mechanical integrity. In this work, to break the historic limit between Li-density and mechanical integrity of traditional solid breeders, a new class of solid tritium breeders is developed: metal-reinforced composite (MERC) breeders. Specifically, the high Li-density of lithium oxide (Li 2 O) is exploited through the addition of a metal reinforcing phase, producing a composite breeder material exhibiting high splitting tensile strength and quasi-ductility with a Li-density greater than other leading solid breeder candidates, including lithium orthosilicate (Li 4 SiO 4 ) and lithium metatitanate (Li 2 TiO 3 ). Mechanical testing, microstructural characterization, and neutronic simulation results are presented and discussed in light of fusion reactor design considerations.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Real-Time Health Monitoring for Gas Turbine Components Using Online Learning and High-Dimensional Data

Capital-intensive turbomachinery, such as gas turbines and combined cycle plants, are constantly being monitored for performance anomalies, faults, and physical degradation. Although these power-generating assets are equipped with hundreds of sensors, existing monitoring tools can only handle moderate-sized data. As a result, only a handful of aggregate metrics are used to monitor machine health. At the same time, developing advanced tools suitable for large datasets have been restricted by the lack of appropriate data. The objective of this proposal was to demonstrate a Big Data analytics framework for fault detection and diagnosis in gas turbine applications. We develop a predictive analytics framework methodology guided by these experimental data, industrial data from our collaborators, and physics-based models with engineering domain knowledge. Our analytics framework consists of four key components (1) a data curation process that addresses data storage, data quality assessments, and integrity checks, (2) a feature engineering component that utilizes statistical methods and transformation algorithms guided by physics-based models to extract high-fidelity fault features that can be leveraged for fault detection and classifying fault severities, (3) a Machine Learning-based fault detection and diagnostics algorithms for detecting operational and hardware faults in the combustion and the turbines section. We utilize two industry-class gas turbine component test rigs to generate first of its kind data for critical gas turbine faults with varying severity levels. Advanced gas turbine test facilities will be interrogated using state-of-the-art instrumentation techniques to build fault signatures and data trends for key combustor and turbine faults. Data generated from a combustor test rig (Georgia Tech) and a turbine test rig (Penn State) during both normal operation and with seeded faults serve as the basis for the Big Data sets. The test conditions in the two test facilities include common, critical events that occur in the operation. Utilizing the combustor test rig, we examine two common combustor faults: lean blowout and centerbody degradation. For the turbine section we develop analytic models for monitoring cooling faults in the gas turbine

03 NATURAL GAS↗
DOE OSTI2024

Cyber-Physical Simulation of an Innovative Solid Oxide Electrolysis Cell - Gas Turbine (SOEC-GT) Hybrid Energy System

To produce green hydrogen at scale and at low cost, the solid oxide electrolysis cell (SOEC) systems would be tied to renewable power sources (mainly solar and wind), leveraging zero-carbon electricity at low prices and even nearly free during overgeneration scenarios. However, due to the intermittency of renewable power generation, the SOEC system is subjected to rapid load transitions that occur not only in diurnal cycles but also in short timeframes (e.g., sub-minute). This can result in fast degradation and thus greatly reduce the SOEC’s lifetime. Our team at the National Energy Technology Laboratory has demonstrated that the anode air flow can have a crucial role in SOEC thermal management. Typically, a higher air flow rate can help to mitigate the local temperature gradient distortion during rapid load transitions. To move a large amount of air, the gas turbine (GT; i.e., compressor-turbine-generator set) has been regarded as the most mature and efficient technology. In this presentation, we show the configuration and preliminary results of an innovative SOEC-GT hybrid energy system in a cyber-physical simulation (CPS) approach.

Zhang, Biao↗
DOE OSTI2025

Cyber-Physical Reformer Development at NETL

Integrated energy systems are considered one of promising technologies to provide efficient, reliable and resilient power generation. The U.S. Department of Energy, National Energy Technology Laboratory is building an automated reformer-solid oxide fuel cell-gas turbine integrated energy system using a cyber-physical systems (CPS) approach, which exploits the advantage of both numerical model and physical system, as well as gapping the inaccessible technologies. Both the fuel reformer and the fuel cell stack are designed to be CPS components, of which the hardware representations are physically integrated with the gas turbine. A compact design is used with the consideration of future commercialization by placing all components inside of a pressure chamber, which is pressurized by the compressor discharge. (Presented virtually at the MILLENNIUM CLEAN and SUSTAINABLE POWER Workshop 2025)

cyber-physical↗
DOE OSTI2025

Testing piezoelectric sensors in a nuclear reactor environment

Several Department of Energy Office of Nuclear Energy (DOE-NE) programs, such as the Fuel Cycle Research and Development (FCRD), Advanced Reactor Concepts (ARC), Light Water Reactor Sustainability, and Next Generation Nuclear Power Plants (NGNP), are investigating new fuels, materials, and inspection paradigms for advanced and existing reactors. A key objective of such programs is to understand the performance of these fuels and materials during irradiation. In DOE-NE’s FCRD program, ultrasonic based technology was identified as a key approach that should be pursued to obtain the high-fidelity, high-accuracy data required to characterize the behavior and performance of new candidate fuels and structural materials during irradiation testing. The radiation, high temperatures, and pressure can limit the available tools and characterization methods. In this work piezoelectric transducers capable of making these measurements are developed. Specifically, three piezoelectric sensors (Bismuth Titanate, Aluminum Nitride, and Zinc Oxide) are tested in the Massachusetts Institute of Technology Research reactor to a fast neutron fluence of 8.65x1020 nf/cm2. It is demonstrated that Bismuth Titanate is capable of transduction up to 5 x1020 nf/cm2, Zinc Oxide is capable of transduction up to at least 6.27 x1020 nf/cm2 , and Aluminum Nitride is capable of transduction up to at least 8.65x x1020 nf/cm2.

T. Reinhardt, Brian↗
DOE OSTI2021

Real-Time Health Monitoring for Gas Turbine Components Using Online Learning and High-Dimensional Data (Final Report)

Capital-intensive turbomachinery, such as gas turbines and combined cycle plants, are constantly being monitored for performance anomalies, faults, and physical degradation. Although these power-generating assets are equipped with hundreds of sensors, existing monitoring tools can only handle moderate-sized data. As a result, only a handful of aggregate metrics are used to monitor machine health. At the same time, developing advanced tools suitable for large datasets have been restricted by the lack of appropriate data. The objective of this proposal was to demonstrate a Big Data analytics framework for fault detection and diagnosis in gas turbine applications. We develop a predictive analytics framework methodology guided by these experimental data, industrial data from our collaborators, and physics-based models with engineering domain knowledge. Our analytics framework consists of four key components: (1) a data curation process that addresses data storage, data quality assessments, and integrity checks, (2) a feature engineering component that utilizes statistical methods and transformation algorithms guided by physics-based models to extract high-fidelity fault features that can be leveraged for fault detection and classifying fault severities, (3) a Machine Learning-based fault detection and diagnostics algorithms for detecting operational and hardware faults in the combustion and the turbines section. We utilize two industry-class gas turbine component test rigs to generate first of its kind data for critical gas turbine faults with varying severity levels. Advanced gas turbine test facilities will be interrogated using state-of-the-art instrumentation techniques to build fault signatures and data trends for key combustor and turbine faults. Data generated from a combustor test rig (Georgia Tech) and a turbine test rig (Penn State) during both normal operation and with seeded faults serve as the basis for the Big Data sets. The test conditions in the two test facilities include common, critical events that occur in the operation. Utilizing the combustor test rig, we examine two common combustor faults: lean blowout and centerbody degradation. For the turbine section we develop analytic models for monitoring cooling faults in the gas turbine.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Energy Storage Analysis

This study presents a comprehensive techno-economic characterization of energy storage and exible low carbon power generation technologies that can shift energy across days, weeks, or months to balance daily, weekly, and seasonal disparities in supply and demand. Energy storage technologies evaluated here include pumped hydropower storage (PHS), adiabatic and diabatic compressed air energy storage (CAES), vanadium redox flow batteries (VRBs), pumped thermal energy storage (P-TES), and renewably produced hydrogen stored in either geologic formations or underground pipes with re-electrification via combustion turbines in combined cycles, stationary proton exchange membrane (PEM) fuel cells, or the novel use of PEM fuel cells designed for heavy-duty vehicles (HDVs) which are expected to have shorter lives but also lower capital costs. We also evaluate flexible low-carbon power generation systems, including ethanol combustion in gas turbines and natural gas combustion with carbon capture and sequestration (CCS). We estimate current costs with literature data, use learning rates to characterize future costs, and develop capacity factors calibrated to an 85% renewables grid to calculate the levelized cost of energy (LCOE) of each technology. Results illustrate that at the 12-hour storage duration, PHS and CAES have the lowest LCOE with current costs, and VRBs become competitive if future costs are achieved. At the 120-hour storage duration, hydrogen systems with geologic storage and natural gas with CCS achieve the lowest LCOE in both current and future capital cost scenarios. In particular, the new configuration of HDV-PEM fuel cells with hydrogen storage in geologic formations evaluated here could lower the LCOE by 22-27% compared to stationary fuel cell systems typically evaluated and might help enable very high (>80%) renewable energy electric power systems. P-TES and hydrogen stored in underground pipes are the least-cost options at the 120-hour storage duration rating that do not require some form of geologic storage. Sensitivity analysis and Monte Carlo analysis illustrate that the general trends seen in this study are valid for a wide range of capacity factors and future cost scenarios. The study also illustrates that coproducing and selling hydrogen to other markets could reduce the LCOE of hydrogen systems by up to 39%.

carbon capture and sequestration↗