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DOE OSTI2025

Photosynthetic Biohybrid System for Enhanced Abiotic N 2 -to-NH 3 Conversion under Ambient Conditions

Photosynthetic biohybrid systems (PBSs) offer an eco-friendly approach to transforming solar energy into value-added products by integrating biological entities with inorganic semiconductors. However, the chemical conversion capacity of most PBSs has inherent limitations, as whole-cell bacteria and isolated enzymes require fine-tuning of environmental conditions. Here, in this study, we report a new PBS developed by introducing free-standing ceria nanoparticles into the purple membrane (PM) of Halobacterium salinarum archaea, which can unidirectionally transfer charge carriers in response to incident photons, even after separation from living archaea at various conditions. Our microscopy, spectroscopy, and synchrotron X-ray scattering analyses confirm that the electrostatic assembly between ceria and PM creates seamless interfacial contact, thereby enhancing the photocatalytic capacity of ceria. Although the conversion of dinitrogen (N 2 ) to ammonia (NH 3 ) is thermodynamically challenging due to the triple bond in N 2 and a series of charge-transfer reactions, our PM–ceria (PMC) hybrid nanoparticle efficiently produces NH 3 by reducing N 2 using solar energy even under atmospheric pressure and room temperature while simultaneously converting glycerol into value-added derivatives. Additionally, our PMC nanoparticle involves neither toxic/precious metals nor bioengineering processes to achieve enhanced photocatalytic N 2 -to-NH 3 conversion. This study sheds light on the new aspect of PBSs by employing PM to potentially resolve the global energy and environmental challenges posed by the conventional Haber–Bosch process.

Jang, Jinhyeong [Argonne National Laboratory (ANL)↗

DOE OSTI2025

Photocatalytic Overall Water Splitting at the Integrated Rh–MoRhO x Cluster Heterostructure on InGaN/GaN Nanowires

The quest for efficient solar-driven water splitting, a promising avenue for clean fuel production, faces challenges due to limited solar energy conversion efficiency. Traditional approaches study the overall water splitting as two spatially separate half reactions on two unrelated sites, hindering full utilization of photogenerated charge and water molecules. To overcome these limitations, an integrated cluster heterostructure catalyst on InGaN/GaN semiconductor nanowires is proposed for the effective utilization of photogenerated charge carriers and water molecules on the same redox localization. By establishing the fast charge extraction kinetics based on InGaN/GaN nanowires, the integration of Rh and MoRhOx clusters on the nanowire surface enables simultaneous and fast hydrogen/oxygen evolution reactions at the cluster heterostructure. Furthermore, the integrated strategy can enhance the charge redistribution across the heterostructure between the two clusters, further optimizing adsorption of reaction intermediates on each cluster for boosted photocatalytic water splitting activity. Consequently, the integrated heterostructure triggers a 40-fold increased hydrogen production efficiency in an artificial leaf system. This study provides valuable insights for the rational design of advanced heterostructured photocatalysts for water splitting and beyond.

GaN nanowire↗

DOE OSTI2024

Toward sustainable electrochemically mediated separations driven by renewable energy

Environmental pollution, water scarcity, resource shortage, and fossil fuel reliance have all represented threats to a sustainable future. Separation processes play a pivotal role in improving sustainability in fields such as industrial processes, resource recycling, wastewater treatment, and water desalination, among others. Electrochemical systems have gained increased attention as effective separation platforms, not only in performance but also as a potentially energy-efficient approach. However, the reliance on non-renewable energy sources, such as fossil fuels, for electricity generation limits the advancement toward a fully sustainable separation process. Integration of separation processes with eco-friendly renewable energy sources can increase overall sustainability and decrease carbon footprint. Here, in this review, we provide an overview of electrochemical separations and recent efforts to integrate them with renewable energy sources such as heat and solar energy. We discuss electrochemical separations, including electrosorption and electrodialysis, and research to transition these processes to thermoelectrochemical (TEC) and photoelectrochemical (PEC) platforms. Finally, we discuss current challenges and future prospects in direct integration of renewable energy sources with separation processes.

electrochemistry↗

DOE OSTI2024

Techno-Economic Analysis and Market Potential of Geological Thermal Energy Storage (GeoTES) Charged With Solar Thermal and Heat Pumps

In this project, we developed a techno-economic analysis (TEA) model that can be used to evaluate the viability of a proposed Geological Thermal Energy Storage (GeoTES) design. This MATLAB-based model integrates distinct subsystem models for the reservoir, wells, power cycle, and solar field to capture their distinct characteristics. It applies this approach in simulating GeoTES storage and dispatch operations for durations ranging from hourly to seasonal. Using cases studies based on GeoTES designs provided by industry partners - Premier Resource Management (PRM) and EarthBridge Energy - we validated the TEA model estimations of system performance and costs (such as thermal and electrical power/energy inflow and outflow, capital costs, and levelized costs of energy and storage) for both concentrating solar thermal (CST) and Carnot Battery (CB) pairings with GeoTES (CST-GeoTES and CB-GeoTES). For the CST-GeoTES case, the model was validated against the proposed system designed by PRM. It showed good agreement with PRM's estimations when well and pump costs derived from PRM's estimations were used. When GETEM-based costs were used, there was a slight overprediction due to GETEM's project/site agnostic assumption of these costs. From a sensitivity analysis perspective, the levelized cost of electricity (LCOE) of the CST-GeoTES case was most sensitive to well flow rate and the charging temperature. An optimal design scenario resulted in an LCOE of 0.11 $\$$/kWhe. CST-GeoTES can also provide a source of heat to meet seasonal demands. With 12-hour and 24-hour levelized cost of heat (LCOH) of 0.018 $\$$/kWhth and 0.022 $\$$/kWhth, respectively, CST-GeoTES could be competitive in the California market with an average industrial price of natural gas in California between 0.041-0.047 $\$$/kWhth. The levelized cost of storage (LCOS) for CST-GeoTES depends on the energy storage duration. Although the LCOS is relatively higher for shorter durations (e.g., ~0.50 $\$$/kWhe for 1 hour of storage), it is an order of magnitude lower (0.06 $\$$/kWhe) for longer storage durations and competitive with lithium-ion batteries (beyond 12 hours of storage) and molten-salt thermal energy storage (beyond 32 hours). Energy. Three options were explored and applied to the EarthBridge case study: (1) A Carnot Battery design using R125 working fluid with both hot and cold storage; (2) A Carnot Battery design using R125 working fluid with only hot storage; (3) A Carnot Battery using a commercially available heat pump with carbon dioxide (CO2) working fluid and hot storage only. The CB-GeoTES with cold storage only had a slight (round-trip) efficiency advantage over the system without (43.4% vs. 42.8%). This is because the cold storage is limited by the freezing point of water, so the cold storage is not much colder than the environment. The system using commercially available technologies was the least efficient - partly because different cycles were used in the heat pump (CO2) and heat engine (binary cycle) which leads to some inefficiencies. Using the commercially available design, the levelized cost of energy (LCOS) from the model (0.10 $\$$/kWhe) was higher than that estimated by EarthBridge (0.068 $\$$/kWhe). This is because of the low round-trip (38.7%) efficiency of the commercially available design. Sensitivity analysis reveals that the model is most sensitive to electricity price. Including electricity price in the TEA for CB-GeoTES leads to an increase in LCOS from the base value to 0.25 $\$$/kWhe. To determine storage sites suitable for GeoTES, we gathered and analyzed geological, petrophysical, and geophysical data of oil and gas reservoir and aquifers in California and Texas. We down-selected possible sites based on cut-off values for site characteristics (e.g., reservoir temperature, formation thickness, permeability, porosity, depth, and brine salinity) and preliminary costs. Using this approach, the Carrizo-Wilcox, Yegua-Jackson, and Dockum brackish aquifers in Texas were identified as having the highest suitability. Similarly, in the central California region, the White Wolf, Belridge South Tulare, and Belridge South Reef Ridge were the most suitable. Going further, we assessed the storage potential in the selected sites. To do this we developed distributions of reservoir characteristic data and applied a Monte Carlo-based analysis to account for intrinsic uncertainty in the acquired data. The analysis revealed that the Carrizo-Wilcox aquifer had the highest storage potential with a mean capacity of 554 TWhth (i.e., 63 TWhe). The estimated capacity serves as an upper limit of storage potential given that not all fields in the basin will be developed. We participated in multiple outreach activities including conference presentations, panel session discussions, and the facilitation of a GeoTES workshop at the NREL Golden campus.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Consensus-Based Control and Optimization of Power System Inertia

The integration of distributed energy resources (DERs), such as solar, wind, and energy storage systems, into power grids through inverter-based resources reduces power system inertia, leading to faster frequency dynamics and potential grid instability. To address this challenge, this paper proposes a distributed, consensus-based approach for the real-time control and optimization of inertia sources (synchronous generators and/or DERs) during system disturbances, enhancing both system stability and economic performance. The distributed control and optimization approach assumes each inertia source exchanges information solely with its neighbor ones, making it easily scalable to large power grid networks. The impacts of the communication connectivity among the inertia sources as well as their generation capacity limits on the distributed approach are investigated. We also demonstrate the approach’s robustness in scenarios involving communication time delays and packet losses, validating its effectiveness through numerical simulations on a 4-bus test system and a two-area 8-bus test system.

Power system inertia↗

DOE OSTI2025

Spectral Properties of Globally Distributed ENA Fluxes across Diverse Regions of the Heliosphere

This study analyzes energetic neutral atom (ENA) spectral properties across distinct regions of globally distributed flux (GDF) sky maps, using Interstellar Boundary Explorer data from a full solar cycle, corrected for time dispersion. By time-shifting the data to the heliosheath using GDF source distances from D. B. Reisenfeld et al., we achieve a more accurate representation of heliosheath GDF energy spectra. We quantify ENA spectral characteristics, heliosheath line-of-sight-integrated proton pressure, and heliosheath proton temperature, comparing these to solar wind properties at 1 au and interplanetary scintillation-derived solar wind data. Our findings show that the spectral index is generally anticorrelated with heliosheath proton temperature and pressure, except in the central tail, where a partial positive correlation is observed. The lowest spectral index values occur when high-latitude heliosheath regions are dominated by fast solar wind from polar coronal holes. The south pole exhibits the flattest energy spectra due to plasma heating from both fast solar wind and a late-2014 pressure pulse. The central tail shows shorter variability (5–6 yr) for spectral index and heliosheath proton temperature, while proton pressure follows the 11 yr solar cycle. Most spectral shapes exhibit a “knee” distribution, peaking during solar maximum, with an “ankle” shape observed only at the south pole during solar cycle transitions. Asymmetry in proton pressure in the lobes is driven by the draping effect of the local interstellar magnetic field. This study provides insights into the energetic properties of GDF across the heliosphere, enhancing our understanding of the heliospheric environment.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Low‐Temperature Synthesis of Stable CaZn 2 P 2 Zintl Phosphide Thin Films as Candidate Top Absorbers

Abstract The development of tandem photovoltaics and photoelectrochemical solar cells requires new absorber materials with bandgaps in the range of ≈1.5–2.3 eV, for use in the top cell paired with a narrower‐gap bottom cell. An outstanding challenge is finding materials with suitable optoelectronic and defect properties, good operational stability, and synthesis conditions that preserve underlying device layers. This study demonstrates the Zintl phosphide compound CaZn 2 P 2 as a compelling candidate semiconductor for these applications. Phase‐pure, ≈500 nm‐thick CaZn 2 P 2 thin films are prepared using a scalable reactive sputter deposition process at growth temperatures as low as 100 °C, which is desirable for device integration. Ultraviolet‐visible spectroscopy shows that CaZn 2 P 2 films exhibit an optical absorptivity of ≈10 4 cm −1 at ≈1.95 eV direct bandgap. Room‐temperature photoluminescence (PL) measurements show near‐band‐edge optical emission, and time‐resolved microwave conductivity (TRMC) measurements indicate a photoexcited carrier lifetime of ≈30 ns. CaZn 2 P 2 is highly stable in both ambient conditions and moisture, as evidenced by PL and TRMC measurements. Experimental data are supported by first‐principles calculations, which indicate the absence of low‐formation‐energy, deep intrinsic defects. Overall, this study shall motivate future work integrating this potential top cell absorber material into tandem solar cells.

14 SOLAR ENERGY↗

DOE OSTI2025

Review of High-Throughput Surface Treatments for Microlens Arrays

Microlenses are increasingly being integrated into modern manufactured devices. From printed security devices and screens to solar panels and microscopes, these optical materials offer high control over light focusing. Thus, understanding how to treat the surfaces of these fragile, transparent devices on an integrated manufacturing line is essential. Here, in this study, we review the surface treatments for the following application categories: cleaning, increasing surface energy, decreasing surface energy, and tunable surface modifications. This overview describes methods available for the large-scale manufacturing of microlens arrays and the potential impact of those treatments on common optical surfaces. Objectives and qualitative compatibility parameters are compared, and outlooks are provided for further study to aid in streamlining the method selection and process optimization for microlenses and similar optical components.

lens manufacturing↗

DOE OSTI2025

Thermal Analysis of a Solid Particle Light-Trapping Planar Cavity Receiver Using Computational Fluid Dynamics

Concentrated solar power (CSP) is one of the most effective ways of harnessing solar power to create efficient, durable, and resilient energy systems. This study entails thermal modeling and analysis of a novel central tower receiver configuration. This receiver uses solid particles as the heat transfer fluid (HTF), a promising option for third-generation CSP systems. The configuration considered here is the light-trapping planar cavity receiver (LTPCR) introduced by the National Renewable Energy Laboratory. While heat transfer studies of various LTPCR subsystems have been done, system-level thermal analysis of the LTPCR receiver has not been attempted. This study also presents important sensitivity analyses of the operating parameters of the CSP system, which can help guide the design of future central tower receivers. This study employs Ansys Fluent as a computational fluid dynamics (CFD) tool to model fluid dynamics and heat transfer in the receiver, intending to quantify its thermal performance. The model seamlessly integrates Monte Carlo ray tracing data, which generates absorbed solar flux profiles from the heliostat field design, with the heat transfer characteristics of the fluidized particle bed. This unified model is designed to accurately predict the thermal behavior of the LTPCR. Analysis of preliminary results reveals that the primary loss mechanisms are radiative and natural convective losses, in that order. Based on observations from a baseline case, several strategies are suggested and numerically tested. These solutions include selective cooling of high-temperature regions and manipulation of particle bed parameters. Selective cooling of high-temperature regions reduced the peak temperature by 151 degrees C and decreased thermal losses by 0.9%. Improving the particle-wall heat transfer coefficient (P-W HTC) of the particle bed decreased the thermal losses by 1.7% and decreased the peak temperatures by 57 degrees C. Decreasing the particle inlet temperature (PIT) also reduced thermal losses by 3.5% and decreased peak temperatures by 29 degrees C. Compounding these strategies improved the thermal losses of the receiver from 13.5% in the baseline case to 7.5%. Additionally, the study explores the variation in thermal performance across different locations of the receiver, where a variation of thermal losses from 12.9% to 17.3% is found. This allows a comprehensive evaluation of potential improvements in efficiency and temperature management.

computational fluid dynamics↗

DOE OSTI2025

Comprehensive assessment of deep reinforcement learning approaches for economic dispatch in nuclear-driven microgrids

As the electrical grid integrates more variable renewable energy sources such as wind and solar, the demand for distributed and flexible systems to address this increased variability becomes critical. Nuclear-driven microgrids provide a promising solution by offering stable generation to complement intermittent renewables, ensuring grid reliability and operating efficiency. This paper proposes a recurrent deep reinforcement learning framework for optimal economic dispatch in a nuclear-powered microgrid integrating renewable energy sources, small modular reactors, battery storage systems, and balance-of-plant dynamics. A three-agent control architecture is developed, where demand and renewable energy agents act as forecasters, and a reinforcement learning-based dispatch agent performs real-time energy allocation. A nonlinear programming formulation is first used to generate an optimal baseline for benchmarking. The proposed dispatch controller, based on Proximal Policy Optimization enhanced with Long Short-Term Memory networks, exploits temporal correlations in system dynamics by taking advantage of the time series used as inputs to improve policy robustness under uncertainty. Comparative analysis against established deep reinforcement learning methods, including Proximal Policy Optimization with a feedforward architecture, Soft Actor-Critic, and Twin Delayed Deep Deterministic Policy Gradient, demonstrates superior performance. Numerical results indicate that the proposed controller achieves a 0.39% cost reduction relative to the nonlinear programming benchmark and outperforms other learning-based methods by generating additional revenue of up to 0.35%. All reinforcement learning controllers compute dispatch actions in less than 0.3 s, resulting in a computational speedup of more than three orders of magnitude over the nonlinear programming baseline. The findings of this paper highlight their applicability for real-time operation and control in nuclear-integrated microgrids under volatile operating conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Cybersecurity Standards, Certification, and Best Practices for DERs

Distributed energy resources (DERs) are becoming increasingly important to the electric grid, including solar energy systems. However, DERs also introduce new cybersecurity risks, including those posed by cloud computing. Standards harmonization is essential for ensuring that DERs are secure and can be safely integrated into the grid. This panel will discuss cyber standards harmonization for solar security. The panel will feature experts from the S2G Program, National Labs and Industry who will discuss the following topics: the cybersecurity risks and future benefits posed by ubiquitous solar energy systems, the development and implementation of cloud-based security solutions for DERs, including solar energy systems, the challenges and opportunities for harmonizing DER cybersecurity standards, and Cyber Informed Engineering and the solar security implementations The panel will also discuss the following specific initiatives: the S2G Program's DER Cybersecurity Framework, UL's DER Cybersecurity Certification Program, and IEEE 1547 Updates. The panel will conclude with a discussion of the future of standards harmonization for DER cybersecurity.

14 SOLAR ENERGY↗

DOE OSTI2024

Assessment and Coordination of DER Cybersecurity Standards

14 SOLAR ENERGY↗

DOE OSTI2025

Agrivoltaic Grazing Systems for a Sustainable Future: A Multi‐Disciplinary Review & Gap Analysis

Solar photovoltaics (PV) is the fastest growing source of electricity in the world, however, its expansion has raised concerns about the displacement of agriculture and the degradation of rangeland ecosystems. This has prompted research and development of multi-land-use systems that co-prioritize energy production alongside agriculture, commonly referred to as agrivoltaics. Currently, agrivoltaic grazing (also called solar grazing) is one of the most common forms of these systems. However, peer-reviewed research on these systems is limited. This review synthesizes research on agrivoltaic grazing systems, drawing upon literature addressing agrivoltaics broadly and considering relevant literature in adjacent fields of study. Based on this review, we identify six key gaps and priority directions for future research. These include foundational fieldwork to characterize the layered ecological impacts of solar PV and grazing and understand PV-livestock integration from both an animal welfare and a PV infrastructure perspective. This will facilitate the development of biogeochemical and economic models that improve our predictive capacity and ability to compare system designs. We also identify gaps in understanding the human aspects of these systems and emphasize the importance of utilizing collaborative research methods and increasing research on the social dimensions of agrivoltaic grazing systems.

14 SOLAR ENERGY↗

DOE OSTI2024

Machine Learning-Assisted Stability Boundary Determination of Multiport Autonomous Reconfigurable Solar Power Plants

The multiport autonomous reconfigurable solar (MARS) power plant is a promising solution to integrate renewable resources and energy storage systems into the alternating current (ac) power grid and an high-voltage direct current (HVdc) link. In the MARS system, various input power sources are connected to the individual submodules (SMs) through direct current (dc)–dc converters. However, the presence of external power sources can result in unbalanced capacitor voltages of SMs, thereby violating stability constraints under multiple/diverse operating conditions. This article aims to address the gap by accurately determining the stability boundary of the MARS system. As such, a novel machine learning (ML)-assisted energy balancing control (EBC) criterion is proposed. Further, in conjunction with a refined EBC, this approach ensures balanced capacitor voltages across various types of SMs, significantly enhancing the overall system efficiency. The proposed EBC criterion effectively controls EBC activation and deactivation, achieving remarkable accuracy. Both power systems computer aided design (PSCAD)/electromagnetic transients including direct current (EMTDC) simulations and control hardware-in-the-loop (cHIL) tests are conducted to validate the feasibility and efficiency of the proposed method. By combining the EBC and ML-assisted EBC criterion, efficient energy management is achieved for systems featuring multiple input power sources, such as MARS. This approach enables the system to fully exploit its potential across an expanded operational range while upholding high-efficiency standards.

14 SOLAR ENERGY↗

DOE OSTI2026

An Open Source Perovskite Solar Cell Curve Tracer

When developing systems for perovskite solar cells (PSCs), it is important to have a testing platform that closely resembles your deployed systems. While developing a 1 U CubeSat, the Big Red Sat-1 at the University of Nebraska-Lincoln, we found a lack of passive curve tracing instrumentation, which we needed for our mission. To that end, we developed a benchtop passive curve tracer that leverages the Ossila Solar Simulator as an AM1.5 light source. This device utilizes a ladder of switched resistors and a precision voltage and current measurement to achieve the curve tracing. It also integrates a common-anode multiplexer to switch through multipixel PSCs. Finally, the solar cell holder is separate from the main measurement system, so various substrates sizes and pixel counts can be supported. This system is tested using various PSCs. It has been open sourced to enable reuse in future systems that may benefit from the lower power consumption and flight heritage.

14 SOLAR ENERGY↗

DOE OSTI2026

A Monolithic Artificial Leaf for Solar Methanol Production from CO 2 and H 2 O

Methanol, an important liquid fuel and chemical feedstock, has yet to be produced using solar energy, H 2 O, and CO 2 as sole inputs in a standalone device. Here, this study directly addresses this longstanding challenge through presenting the first demonstration of unbiased solar methanol production from CO 2 and H 2 O with a monolithic artificial leaf design, surpassing the previous best energy efficiency in solar alcohol production by at least 1 order of magnitude. We first develop a new generation of photocathodes based on Si micropillar arrays and a cobalt tetraaminophthalocyanine molecular catalyst. By integrating a C 60 interlayer that facilitates unidirectional electron transfer through the semiconductor/catalyst interface, we realize a photovoltage of 500 mV, one of the highest recorded for single-junction Si-based photoelectrodes in aqueous CO 2 reduction, as well as unprecedented methanol formation with a Faradaic efficiency of 30% and a partial current density of 6.3 mA cm –2 . We further integrate the photocathode with a multijunction perovskite photovoltaic minimodule to afford a standalone solar fuel system, which demonstrates a light-to-methanol conversion efficiency of 0.8%, 32 times higher than the present record in light-to-alcohol conversion with an artificial leaf.

alcohols↗

DOE OSTI2024

Integrated protonic ceramic electrochemical cell for sustainable energy economy using water-energy nexus framework

Reliance on fossil fuels will continue for the next decades even though there are global pushes away from it to mitigate the overarching climate challenge, most especially by its highest consumers and availability. While there is a hastening global shift away from fossil fuel, integrating its assets into this technology helps limit the risk and future losses of stranded assets and reduce the cost of investment in the new technologies. Moreover, the generation of electricity from intermittent renewable sources like solar and wind has witnessed a significant surge in recent years, leading to a pressing demand for practical energy storage systems. Electrical energy storage is anticipated to play a pivotal role in the future global energy system, facilitating load-leveling operations to support the greater integration of renewable and distributed generation. Reversible electrochemical cells (RECs) offer a promising option for addressing the fossil fuel assets integration and energy storage challenges through the interconversion between electrical and chemical energy and concurrent utilizing carbon emission. In their electrolysis mode, the RECs convert electricity into durable, storable, and portable valuable chemical fuels such as syngas and methane. Conversely, the produced chemical fuels can be used as reactants in the fuel cell mode to generate electricity on demand with minimal (hydrocarbons) or zero when H2 or NH3 is used emissions. However, a challenging goal for this type of technology remains to achieve optimal operation and high roundtrip efficiencies, which has hindered the deployment of previous electrochemical cells. This dissertation demonstrates how reversible protonic ceramic electrochemical cells (RePCECs) can be integrated with fossil fuel power plants and renewable energy sources as a potential energy storage system. In this work, integrated RePCEC systems are designed and examined using computational modeling at scales to determine appropriate system configurations and operating conditions that achieve high roundtrip efficiencies. Cell level design of the PCEC is the first approach, several cells are assembled for the stack level model that is integrated into combined cycle powerplant and solar photovoltaic for the system level model. After critical literature review, this answered the operational and integration research questions proposed to address these challenges. The designed systems perform two functions, utilizing captured CO2 and storing renewable energy through co-electrolysis of steam and CO2. The co-electrolysis reaction involves endothermic water electrolysis and exothermic methanation reaction. To enhance high roundtrip efficiency, there is a need for thermal balance and management in the electrolysis mode. This involves operating the RePCEC stack under conditions that favor methane production to balance out heat needed by water electrolysis, it crucial for the RePCEC system operation. Methanation is enhanced by low temperatures. Leveraging on fabricated BCZYYb-electrolyte RePCEC, the cell model designed revealed that the optimum temperature for methane production is 450℃ at atmospheric pressure. Thus, to achieve optimum system performance, operating in the temperature range 450-525℃ is recommended at the given configuration, combining between the optimum temperature for methane production and temperature for the optimum stack roundtrip efficiency. Configuration with carbon capture system and purge stream is the optimum configuration from the seven conceptualized and evaluated. The modeling outcomes include a thermodynamic examination of integrated RePCEC systems, calibration of cell and stack level models, and steady-state simulation and integration into a 600MW combined cycle power plant retrofitted with two two-stage membrane-based carbon capture system and a wastewater treatment and recovery unit. At 100% powerplant loading, the stack and system roundtrip efficiencies are 72% and 51.37% respectively. Adding a purge stream for produced hydrogen at the system downstream improves the efficiencies to 74 and 55.48% respectively. At atmospheric pressure and 525℃, the system model suggests that a stack roundtrip of 82% is achievable, and overall system efficiency increases by reducing the energy consumption by the balance of plant components for steam generation and storage. Economic analysis of the process gives levelized cost of methane as $2.24/MMBtu lower than the conventional production route that range between $3.46/MMBtu and $9.85/MMBtu. The lifecycle analysis shows that the global warming potential for the production of methane and hydrogen from the RePCEC system is 3.83 kg CO2 eq which is lower than 9.35 kg CO2 eq emission during steam methane reforming for hydrogen production. This answered both the environmental and economic concerns in the raised research question. The proposed RePCEC configuration and analysis carried out in this dissertation to address the surge in renewable energy and challenges with PCEC technology hold significant potential in achieving large-scale energy storage while simultaneously reducing carbon emissions. These advancements, coupled with suitable governmental policies and incentive programs, have the potential to economically disrupt the natural gas industries by using RePCEC systems for methane production, thereby making them more favorable for eventual implementation and commercialization.

25 ENERGY STORAGE↗

DOE OSTI2024

From Silos to Synergy: Identifying a Roadmap for Cross-Sector Research to Accelerate the Clean Energy Transition

The U.S. Department of Energy's blueprints for the transportation, buildings, and electricity sectors call for substantial reductions in greenhouse gas (GHG) emissions by 2050. These plans focus on zero-emission vehicles, investments in transit, energy-efficient buildings, and the widespread adoption and deployment of renewable energy technologies like solar photovoltaics (PV), energy storage and energy-efficient appliances. However, these sectors are often studied and modeled in isolation, overlooking how household decisions to adopt clean technologies in one sector influence others. This study, led by an interdisciplinary team at the National Renewable Energy Laboratory (NREL), explores opportunities for cross-sector collaboration to drive more effective and equitable decarbonization. Through discussions with 22 NREL researchers across transportation, building, solar, and grid sectors, the study highlights the need for integrated tools and models that capture interactions between these sectors. Key insights include the need for data standardization and interoperability to enable cross-sector analysis and decision-making. Strengthening utility partnerships is also critical to align energy policies with decarbonization goals and manage the increased demand for renewable energy. The study also emphasizes the importance of equity in the clean energy transition, calling for targeted incentives and support to ensure that low-income and underserved communities benefit from clean technologies like electric vehicles and energy-efficient appliances. To support these efforts, innovative funding mechanisms must be expanded to facilitate interdisciplinary research, such as city-specific decarbonization plans and federal projects like DOE"s Standard Scenarios. By encouraging collaboration and integrating cross-sector insights, this study aims to provide a roadmap to accelerate the clean energy transition and ensure it is both sustainable and inclusive.

14 SOLAR ENERGY↗