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DOE OSTI2024

Navigating Options for Transportation Electrification and Solar Charging: Steps and Lessons Learned in Montana Communities

This document is intended to assist communities who are considering investing in electric transportation. It can assist communities engage stakeholders, prioritize community goals, assess electric transportation options, and navigate complex decisions about deploying zero emission electric transportation in their community. It covers technological, economic and environmental aspects of the transition to electric vehicles (EV), and highlights the specific considerations related to the deployment of renewable energy technologies (e.g., distributed solar) in combination with EV supply equipment (EVSE, e.g., charging stations). There are many important decisions to make and questions for communities to ask themselves as they consider electric vehicle types, charging infrastructure, and electricity generation options. This guide will help communities assess: (1) Which stage in the decision-making process they are in with respect to EV deployment; (2) Questions they can explore to guide their decisions about EV deployment; (3) How to engage key stakeholders on EV deployment options; (4) Tradeoffs and benefits of various electric transportation options and; (5) Synergies of pairing electric vehicle charging and renewable energy generation technologies. The analysis and lessons learned presented in this roadmap are intended to serve as a template and guide for similarly situated communities across the country who want to prepare for and play a role in the electrified transportation future.

14 SOLAR ENERGY↗
DOE OSTI2024

Evaluation of the Turbine Integrated Mortality Reduction (TIMR SM ) Technology as a Smart Curtailment Approach (Final Summary Report)

Wind energy is a crucial technology for achieving net-zero emissions by 2050. However, the growth and deployment of wind energy in North America have led to the deaths of many bat species due to operating wind turbines. Hundreds of thousands of bats are estimated to die at wind turbines annually in North America. Operational minimization, which includes feathering turbine blades and curtailment, has been documented to reduce bat fatality effectively. Curtailment refers to altering turbine operation based on wind speed, time of year, temperature, sensors, and activity models. However, when turbines are curtailed, they do not generate power, resulting in energy loss and revenue for wind energy facilities. The Electric Power Research Institute (EPRI) funded the development of Turbine Integrated Mortality Reduction (TIM SM ) Technology, which curtails turbine operation when bats are detected. The initial TIMR system research showed promising results, with an 85% reduction in overall bat fatalities and a 91% reduction for the little brown bat. However, these results were based on a single site during one fall season, and it was unclear if similar results could be replicated at other wind energy facilities. This research aimed to validate the TIMR system results from the prior field study at a second site in the U.S., estimate the power production and reduction in bat mortality at turbines with installed TIMR systems relative to blanket curtailment and fully operational turbines, test the TIMR system in two calendar years and during the summer and fall periods, and evaluate the operational and commercial characteristics of the TIMR system for potential wind industry adoption. The study was conducted at a 500.9-MW wind energy facility in southeast Adair County, Iowa. Three experimental treatments were involved in this randomized block design study: TIMR, Curtailment at 5.0 m/s, and Normal Operation. In 2021, three treatments were used at 18 turbines, expanding to four treatments across 36 turbines in 2022. The TIMR system worked as designed throughout the entire study; however, because of unexpected wind turbine operational challenges in 2021, there was not sufficient sample size to evaluate the treatment differences. In 2022, there were significant differences in fatality levels between treatment types and normal operating turbines. Curtailment at 5.0 m/s reduced fatalities by 30.8% compared to normal operations, and TIMR decreased fatalities by 48.6% compared to normal operations. Two different methods were used to evaluate the differences in energy loss for each treatment. The TIMR system resulted in 1.3% to 1.6 % annual energy loss in 2021 and 1.0% to 1.2 % in 2022. The Curtailment at 5.0 m/s resulted in 0.6% to 0.8 % annual energy loss in 2021 and 0.5% to 0.6 % in 2022. The project achieved all the stated objectives and demonstrated that TIMR is an effective technology that balances bat fatality reduction with energy generation. The results will support the deployment of TIMR and other acoustic sensor-based technologies. The research provides valuable insights into the impact of different treatments on fatality rates and energy outputs, contributing to the ongoing efforts to mitigate the environmental impact of wind energy.

17 WIND ENERGY↗
DOE OSTI2023

Maritime Fuel Cell Generator Project: 2018 – 2023

This report summarizes activity in the Maritime Fuel Cell (MarFC) Generator Project from 2018 – 2023. FY 2018 saw the implementation of upgrades and repairs, making the unit more reliable and operator friendly. In FY2019 the team engaged the Scripps Institution of Oceanography (SIO) to use the MarFC to provide zero-emission shore power to the research vessel R/V Robert Gordon Sproul while in port at the Nimitz Marine Facility in San Diego, CA. In FY2020, the MarFC unit was shipped to San Diego, CA. A fueling contract with IGX was established to support MarFC operations at SIO, with renewable hydrogen provided by the California State University Los Angeles (CSULA) hydrogen station. The project team (Sandia, Cummins/Hydrogenics) provided training to SIO staff on the technical details of the MarFC, the safe use of hydrogen in general and the MarFC in particular. The first fueling of the unit at the SIO pier was successfully completed by IGX. The first powering of a vessel with fuel-cell shore power was conducted with the R/V Robert Gordon Sproul. While the mechanical systems (lights, AC, ventilation, hydraulics, pumps and cranes) were powered without incident, problems arose when powering the computer systems. Inspections carried out in FY2021 revealed the MarFC needed routine maintenance. Maintenance was performed and the unit was upgraded. The MarFC was turned on after the year pause, and initial test data on power levels and stability were collected. FY2022 was a year spent repairing, upgrading and testing the MarFC unit. Spikes in power and voltage were observed above 60 kW that could potentially extend below 60 kW with time. Such spikes could cause problems with the Sproul electrical systems. These age-related problems, the extended time for the Sproul spent in dry dock for scheduled upgrades, and the associated need to reschedule the vessel’s high-priority science missions made it no longer possible to deploy the unit at SIO. After due consideration, the decision was made by DOE, MARAD and the project team to cease the deployment, remove the MarFC from SIO, and not pursue further deployment activities. On December 2, 2022, the MarFC unit was removed from the Scripps Nimitz Marine Facility and shipped to Fridley, Michigan. The Cummins/Hydrogenics plan for the unit is to assess the condition of the MarFC subcomponents, and then use it as a training/learning system for technical employees new to hydrogen fuel-cell technology. After summarizing project activity from 2018 – 2023, this report provides a review of lessons learned. This report provides next steps in contemplating a follow-on project that would further advance the use of fuel-cell-based shore power in a marine setting. A comparison is made of the project results to the original objectives. This report ends with an accounting of presentations stemming from the project, and a list of references.

08 HYDROGEN↗
DOE OSTI2022

White Paper on Lithium-Ion Battery Safety for use in Safety Planning at the Waste Isolation Pilot Plant

The Waste Isolation Pilot Plant (WIPP) is an underground facility designed to safely dispose of radioactive waste. The WIPP uses many heavy vehicles to transport materials and equipment underground. Most of these vehicles are powered by traditional internal combustion engines (ICE) with diesel fuel. Recently, electric vehicles (EVs) powered with batteries have been used at the WIPP. EVs have very low operational and maintenance costs, not considering battery replacements, and they have zero emissions during operation. This absence of emissions makes them ideal for underground facilities with limited ventilation. Even if a facility has robust ventilation normally, ventilation systems can break down leading to restrictions in ICE powered operations. Figure 1 shows a rendering of the WIPP.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Rational Design of Electrocatalysts for Maximizing CO2 Electrolysis Performance

This virtual invited talk in the session " Electrocatalysis and Energy”) at the International Conference on Catalysis Science and Chemical Engineering (CatScience 2024) will briefly overview diverse research areas of NETL to advance energy and environmental sustainability along with carbon management to achieve net zero emissions by 2050. Subsequently, the talk will primarily discuss how rational design of novel electrocatalysts would maximize the CO2 conversion in different cell configurations.

Nguyen Phan, Thuy Duong↗
DOE OSTI2024

Rational Design of Electrocatalysts for Maximizing CO2 Electrolysis Performance

This presentation will briefly overview diverse research areas of NETL to advance energy and environmental sustainability along with carbon management to achieve net zero emissions by 2050. Subsequently, the talk will primarily discuss how rational design of novel electrocatalysts would maximize the CO2 conversion in different cell configurations.

Nguyen Phan, Thuy Duong↗
DOE OSTI2024

Overview of NETL’s Low Temperature CO2 Electrolysis Research

This keynote lecture will briefly overview diverse research areas of National Energy Technology Laboratory (NETL) to advance energy and environmental sustainability along with carbon management. Our electrochemistry efforts on carbon conversion directly support the US goal of achieving carbon-free power sector by 2035 and net zero emissions by 2050. Since CO2 electroreduction is highly structure-sensitive, NETL ongoing research has been focused on the rational design and engineering of electrocatalysts to facilitate the CO2 conversion to desirable products with good selectivity, activity, and durability. Different classes and types of electrocatalytic materials will be covered in this talk, from well-defined atomic-scale model catalysts to heterogenous, scalable powder systems at nano- and micro-scale for “real world” performance evaluation. Several spectroscopic, microscopic, and electrochemical characterization techniques along with computational findings will be additionally discussed to gain more insights into the structure-activity relation. The last part of this seminar will provide more detail on how NETL has transitioned from the most common aqueous H-type reactor for lab-scale validation to more realistic full electrolyzer cell in bench-scale prototype. The knowledge, electrocatalytic materials, and device validation achieved from NETL in-house research will be translated to industrial sector for large scale deployment and the anticipated outcome will help advance the development of low temperature CO2 electrolysis technologies.

Nguyen Phan, Thuy Duong↗
DOE OSTI2024

Continuous integration data-driven platform of industrial-scale subsurface storage for real-time analytics

This project helped address the growing need for efficient and scalable models to support geological carbon and energy storage, which are crucial for achieving net-zero emissions. Traditionally accurate high-fidelity numerical models have been used to simulate relevant storage processes under a handful of processes, however such models are computationally demanding, making uncertainty quantification impractical. Consequently, we first developed a machine learning framework, based on Graph Neural Operators (GNOs), to improving the accuracy of model predictions for a fixed computational budget. We then developed an Ensemble of Improved Neural Operators (ENO), which uses bagging and Monte Carlo dropout techniques, to further improve prediction accuracy. Lastly, we developed the way to explain progressive transfer learning methods to reduce the amount of training data and computational cost of training (i.e., reduce trainable parameters) when using our models for multiple storage sites. Our numerical investigation, which used real-world case studies, demonstrated that our framework can significantly improve the safety and efficiency of geological storage operations, with potential applications in other domains such as geothermal reservoirs and climate modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Energy Clusters Offshore: A Technology Feasibility Review

Globally, governments, companies, and other organizations have committed to achieving net-zero emissions targets in the coming decades. To achieve decarbonization at the scale and pace required to meet these targets, future energy systems will need renewable energy to serve 100% of the existing direct electricity demand, support additional electrification, and decarbonize the wider economy. An energy cluster offshore (ECO) is a concept that seeks to meet this challenge by integrating and optimizing large-scale renewable electricity generation, storage, and fuel production technologies and pairing them with other complementary uses, such as carbon capture or water desalination. This research project explores the techno-economic feasibility of ECO concepts by taking a holistic view of complex, multidisciplinary hybrid plant designs while considering different configurations and objectives. We will outline the most promising technology combinations and configurations, their functional requirements, and opportunities for optimization.

14 SOLAR ENERGY↗
DOE OSTI2024

Integrate Latimer Controls' Solution into RTAC (CRADA Final Report, CRD-23-24672)

Latimer Controls, Inc. was awarded two vouchers under the Department of Energy's American-Made Solar Prize Round 6 to conduct collaborative research at a national laboratory. The National Renewable Energy Laboratory (NREL) was selected as a partner to assist Latimer Controls in the performance evaluation of its photovoltaic (PV) control software. This collaboration focuses on developing a hardware-in-the-loop (HIL) testbed at NREL, which will be used to test and validate the Latimer PV control technology in a realistic yet de-risked environment. Both Latimer and NREL teams will work together to analyze the collected test data, derive insights, and disseminate the scientific findings. Recent studies underscore the potential of solar energy as a zero-marginal-cost and zero-emission flexibility resource within the bulk power system, particularly when integrated with advanced control systems. To enhance the performance of such systems, Latimer Controls has developed leading-edge technologies, including machine learning (ML) algorithms and hierarchical inverter set-point allocation methods. These innovations are designed to estimate the operational headroom of large PV plants for grid integration and control. However, comprehensive validation under real-world conditions remains necessary. To address this gap, the concurrent CRADA project proposes the real-world application and validation of the Latimer Control solution within a HIL environment. Initially, the Latimer algorithm was developed and tested within MATLAB Simulink, a platform suitable for research-level simulations and iterative development. However, transitioning this technology to a real solar site as an industry-ready solution necessitates implementation in a format compatible with widely used solar power plant controllers. In this additional CRADA work, the MATLAB Simulink-based logic will be translated into Structured Text, a programming language compliant with IEC 61131 standards, which is commonly used for custom logic implementations in industry-leading programmable logic controllers (PLCs), such as the Schweitzer SEL real-time automation controller (RTAC). This transition will facilitate the deployment of the Latimer Control solution in real-world solar power plants, thereby advancing the technology towards commercialization.

14 SOLAR ENERGY↗
DOE OSTI2024

Heliostats with Adjustable Shape for High Concentration throughout the Day

Our motivation is to develop more efficient heliostats that can provide commercially viable solar thermal power at temperatures > 800°C. Such high temperatures will enable high-temperature industrial processes, as well as electrical generation after sunset with high efficiency. The importance of this research is that such heliostats have the potential to substantially expand the global use of solar energy, by adding solar thermal power as a major component. Thermal solar currently accounts for only 1% of all solar power (with PV being the rest), with heliostat fields providing just 0.25%. Our goals have been 1) to demonstrate a technical improvement for heliostats that can enable fields of them to more efficiently power receivers and reactors, and 2) to show a path to low-cost mass production. Our solution uses new opto-mechanical technology to correct a fundamental deficiency of present heliostats that limits their concentration, namely that they have fixed shape. Most of today’s heliostat research does not address this, but is directed simply toward cost reduction in an effort to make heliostats commercially viable. We are motivated to explore also improving heliostat efficiency, which can be done by continually changing their shape to maximize the concentration of sunlight throughout the day. This is not a new concept, but it has never been implemented in a practical, cost-effective way that approaches the theoretical limit to concentration while also improving mechanical performance; this is our goal. Our major accomplishments have been: 1) We have realized the planned design, construction, and test of a prototype heliostat that achieves the required shape changes in an 8 m2 single-piece glass mirror. The mirror is attached to a steel support frame that is automatically mechanically twisted by the heliostat drives that orient the mirror to direct sunlight to the tower-mounted receiver. Closed-loop tracking is done using a new beamsplitter camera that exploits the target-oriented mount configuration. Field tests of the heliostat show that the light is reflected through the day to always form a disc image of the sun, as needed to obtain the highest concentration. 2) We have developed the design for a field of 431 heliostats to deliver annual average of 1 MW of thermal power at 3,000 sun concentration, matched to a high-temperature ≥ 1000°C chemical reactor. 3) We have also developed, beyond the original stated goals of the project, a new concept for closed-loop tracking and shape-sensing for all the heliostats in the above field, using just 6 cameras around the concentrated reactor focus. Our research adds to the understanding of solar thermal energy by its demonstration of the technical effectiveness of a higher performing heliostat, and by its concept for a new powerful method for real-time tracking and shape sensing in the field, as described above. We have studied the economic feasibility of fields of our twisting heliostats to provide high- temperature heat at a price competitive with that of burning gas, to satisfy the DOE’s studied zero-emissions scenario, where the gas price has to include the cost of carbon capture. The project has the potential to greatly benefit the public if it helps limit global warming by 1) reducing carbon emission from industrial heating, which is currently a major contributor to the 40-billion-ton annual increase in atmospheric CO 2 . 2) Ultimately, the technology could prove to be the least expensive method to power direct air capture of CO 2 on the very large scale needed to remove the 1 trillion-ton excess of CO 2 already in the atmosphere.

14 SOLAR ENERGY↗
DOE OSTI2025

EV Champion Training Webinar 2: ZEV and EV Charging Planning [Slides]

The Electric Vehicle (EV) Champion Training Series, hosted by the National Renewable Energy Laboratory (NREL), is tailored for fleet managers, facility managers, and other stakeholders involved in the deployment of EVs and charging stations. This series equips participants with the skills and knowledge necessary to become subject matter experts in EV implementation. This is the second training in a four-part series and serves as an intermediate training. This training covers the first four steps in the ZEV Ready Center process, including how to identify and train your zero-emission vehicle (ZEV) team, align headquarters strategy with site-level planning, identify ZEV opportunities, and identify charging needs for your project sites. Participants will gain a solid foundation to support the effective deployment and management of EVs and their infrastructure.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Technical Geothermal Roadmap for Indonesia

The technical geothermal roadmapping exercise described by this report is part of the NZW Collaborative Work Program with the Government of Indonesia. Indonesia currently has the second largest installed geothermal power generation capacity in the world and has abundant undeveloped resources that allow for continued expansion of its geothermal resource development, which can serve to contribute to the country’s goal of achieving net zero emissions for power generation by 2060. The DOE GeoVision study (2019) highlighted the importance of technical improvements as the key for accelerating the development of geothermal resources in the United States by reducing the costs and risks to make geothermal more competitive, and this also applies to Indonesia. The main objective of the roadmap is to identify and discuss key technical challenges and discuss how implementation of geothermal technology advances could reduce the risks, costs, and time associated with geothermal exploration and development activities and expand the potential resource base to include unconventional resource types, thus accelerating geothermal deployment in Indonesia.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Autonomous Fueling System for Heavy-Duty Fuel Cell Electric Trucks

The motivation for this project stemmed from the challenges associated with rapidly refueling heavy-duty hydrogen fuel cell electric trucks (FCETs). Current manual refueling processes for fast refueling involve large, heavy equipment (e.g., hoses three times heavier than standard) and pose ergonomic risks and potential for equipment damage. The goal was to develop and test an autonomous fueling system to improve ergonomics, enhance safety, increase equipment durability through design improvements, and potentially speed up the fueling process. This project aimed to add to the understanding of autonomous systems in the context of heavy-duty hydrogen refueling, evaluating the technical effectiveness of potential concepts. A successfully developed system would benefit the public by facilitating the adoption of zero-emission heavy-duty transport, reducing reliance on manual labor for a physically demanding task, and potentially improving the safety and efficiency of hydrogen refueling infrastructure. The major accomplishment during the project's active period was the completion of the system-level architecture task. This involved establishing a detailed list of system requirements covering interfaces, environmental conditions, regulatory compliance, industry standards, safety, security, performance capabilities, and optional features. Five key use cases for the autonomous system were also identified. However, due to internal restructuring at Nikola, the necessary resources could not be allocated to continue the project. Consequently, Nikola opted to discontinue the project. The award was mutually terminated by Nikola and the DOE.

08 HYDROGEN↗
DOE OSTI2025

Potential Risks Associated with Short-Term Hydrogen Storage in Methane Reservoirs

Hydrogen (H2) has been identified as a flexible energy carrier with zero emissions. It is possible to utilize H2 by storing Hyblend, or H2 blended with CH4, in existing natural gas infrastructure. However, the compatibility of adapting the current CH4 storage strategies to include H2 injection has not been fully demonstrated. It is essential that we understand the impact of H2 gas on the naturally occurring microbial community of subsurface storage reservoirs before deploying large-scale H2-CH4 storage. We designed a series of experiments that allowed us to identify potential challenges of HyBlend Storage in existing methane reservoirs (Figure 1). First, we characterized two field fluid samples from a methane reservoir located in Western United States. Next, we used these samples to complete a series of short-term reactor experiments at reservoir conditions for a natural gas (100% CH4) and HyBlend (80% CH4/20% H2) storage environment.

geomicrobiology↗
DOE OSTI2025

Renewable Hydrogen to Vehicle (RH2V) – Operation Verification and Risk Mitigation Studies: Original Agreement (Modification 0) (CRADA Final Report)

Toyota has announced plans for commercial fuel cell vehicle deployment in 2015. To fully realize the benefits of fuel cell vehicles (zero emission with no performance loss in terms of vehicle range and capability), hydrogen produced efficiently from renewable sources is necessary. Most of the hydrogen fueling stations today utilize hydrogen reformed from natural gas (produced onsite or delivered). This enables more stations to be deployed cost-effectively within a network. Producing and using cost-effective renewable hydrogen in fuel cell vehicles will enable realization of the full potential. A viable option of green hydrogen that reliably delivers on the full suite of benefits for Toyota fuel cell vehicle drivers is needed. NREL is in a unique position to analyze and optimize renewable hydrogen production scenarios using the Energy Systems Integration Facility (ESIF), a facility that is specifically designed to evaluate renewable energy integration technologies. As the U.S. Department of Energy's (DOE) primary national laboratory for renewable energy and energy efficiency research and development, NREL has extensive knowledge of photovoltaic systems as well as alternative renewable technologies for efficient and reliable production of green hydrogen.

08 HYDROGEN↗
DOE OSTI2025

Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.

14 SOLAR ENERGY↗
DOE OSTI2025

CalTestBed - Twelve Benefit Co - Understanding Degradation of Water Management Properties in Gas Diffusion Layers (CRADA Final Report)

The research between Lawrence Berkeley National Lab and Twelve Benefit Co. enhanced Twelve’s understanding of how chemical changes to the gas diffusion layer lead to failure of their CO 2 electrolyzers. During the CRADA period, LBNL team tested Twelve’s gas diffusion layer samples (GDL), some with microporous layer (MPL) and some without MPL using the water-air capillary pressure setup. LBNL team also tested microporous layer samples using the fuel cell test stands and compared those results with commercial GDL and MPL. Understanding the hydrophobicity of the material, along with electrochemical performance is the key to determining Twelve’s ability to scale their platform. Further improvements to Twelve’s CO 2 electrolyzer can enhance the net zero emissions with their technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗