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Powered by dGen Webinar [Slides]

NLR's Powered By Webinar Series featuring NLR's dGen Modeling Tool. The Distributed Generation Market Demand (dGenTM) model simulates customer adoption of distributed energy resources for residential, commercial, and industrial entities in the United States or other countries through 2050. The model enables analysis at multiple geographic levels (national, state, and utility, or below) and offers sophistication in representation of decision-making regarding economic and behavioral considerations. Analysts have used dGen to answer questions about load forecasting and integrated resource planning, policy analysis, locational value of distributed energy resources, and more. dGen is open source, and various energy organizations - including independent system operators, regional transmission organizations, and the California Energy Commission - use the model internally.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Influence of the air-cooled supercritical carbon dioxide recompression cycle design-point on molten salt power tower techno-economic performance

Here, this paper investigates the techno-economic performance of a molten salt power tower integrated with an air-cooled supercritical carbon dioxide recompression cycle. Prior research into the cycle design point showed trade-offs between efficiency, cost, and temperature difference across the heat input, resulting in trade-offs between the design-point generation of the molten salt power tower system and the cost of sensible-heat thermal energy storage. Prior research into cycle off-design showed that colder ambient temperature designs have higher efficiencies on cold days but lower efficiency and capacity degradation on hot days. We present a framework to evaluate how cycle design, cost, and corresponding off-design performance affect the techno-economic performance of the molten salt power tower system. We use a steady-state off-design cycle model assuming fixed shaft speeds, inventory control, and air-cooler fan power control and integrate the cycle model with the molten salt power tower model from the National Renewable Energy Laboratory's System Advisor Model. First, we present a surrogate model that uses a heuristic approach to correct the interpolation when the cycle reaches capacity limitations at ambient temperatures hotter than design. Next, we evaluate how the recompression cycle design-point ambient temperature, air-cooler approach temperature, air-cooler fan power, and recuperator conductance influence cycle and system design metrics. Finally, we complete annual simulations using an hourly "duck curve" pricing schedule and present annual performance metrics to evaluate the cumulative effects of the cycle design parameters and corresponding off-design performance on molten salt power tower techno-economics.

14 SOLAR ENERGY↗

US 2023/0182605 A1 Network constraint energy management system for electric vehicle depot charging and scheduling

Network constraint energy management system for electric vehicle (EV) depot charging and scheduling. In an embodiment, a power schedule is received from an economic dispatch application for a charging depot comprising EV charging station(s) and distributed energy resource(s). The power schedule may be simulated on a distribution network model of the charging depot, according to load flow analysis, to determine whether any grid-code violations occur. In response to the detection of violation(s), a constraint may be generated for each violating node, and the economic dispatch application may be re-executed with the constraint(s) to produce a new power schedule, until no violations are detected. When not all load demand can be satisfied by the power schedule, a charging schedule may be adjusted to ensure that critical energy requirements are satisfied. The final power and charging schedules may be used to schedule and control power generation and charging in the charging depot.

Hafiz, Faeza↗

Data Placement Optimization for ATLAS in a Multi-Tiered Storage System within a Data Center

Scientific experiments and computations, especially in High Energy Physics, are generating and accumulating data at an unprecedented rate. Effectively managing this vast volume of data while ensuring efficient data analysis poses a significant challenge for data centers, which must integrate various storage technologies. This paper proposes addressing this challenge by designing and developing a precise data popularity prediction model utilizing state-of-theart AI/ML techniques. This model is crafted from the analysis of ATLAS data and access patterns. It enables us to migrate infrequently accessed data to more economical storage media, such as tape drives, while storing frequently accessed data on faster yet costlier storage media like HDD or SSD. This strategic approach ensures data is placed optimally into the appropriate storage classes, thereby maximizing storage capacity while minimizing data access latency for end-users. Furthermore, the paper includes a performance evaluation of the prediction model using various key metrics such as F1 score, accuracy, precision and recall. Finally, we present a prototype use case, leveraging real-world file access data to assess the model’s impact on performance.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Noise-aware optimization in nominally identical manufacturing and measuring systems for high-throughput parallel workflows

Device-to-device variability in experimental noise critically impacts reproducibility, especially in automated, high-throughput systems like additive manufacturing farms. While manageable in small labs, such variability can escalate into serious risks at larger scales, such as architectural 3D printing, where noise may cause structural or economic failures. This contribution presents a noise-aware decision-making algorithm that quantifies and models device-specific noise profiles to manage variability adaptively. It uses distributional analysis and pairwise divergence metrics with clustering to choose between single-device and robust multi-device Bayesian optimization strategies. Unlike conventional methods that assume homogeneous devices or enforce generic robustness, the proposed framework explicitly determines whether shared optimization across devices is appropriate based on the degree of inter-device noise heterogeneity. This enables improved performance, reproducibility, and efficiency. An experimental case study involving three nominally identical 3D printers (same brand, model, and close serial numbers) demonstrates reduced redundancy, lower resource usage, and improved reliability, along with improved convergence stability and solution quality through the selection of the appropriate optimization strategy based on the degree of inter-device noise heterogeneity. Overall, this framework establishes a general approach for precision- and resource-aware optimization in scalable, automated experimental platforms, demonstrated here on a representative multi-device 3D printing case study.

Schenk, Christina↗

Advances in engineering algae for biofuel production

While algae demonstrate potential as a sustainable fuel source, low productivities limit the economic realization of algal biofuels. High-throughput strain engineering, omics-informed genome-scale modeling, and microbiome engineering are key technologies for enabling algal biofuels. High-throughput strain engineering efforts generate improved traits, including high biomass productivity and lipid content, in diverse algal species. Genome-scale models, constructed with the aid of omics data, provide insight into metabolic limitations and guide rational algal strain engineering efforts. As outdoor cultivation systems introduce exogenous organisms, microbiome engineering seeks to eliminate harmful organisms and introduce beneficial species. In conclusion, optimizing algal biomass production and lipid content using these technologies may overcome the productivity barrier for the commercialization of algal biofuels.

09 BIOMASS FUELS↗

Sharpening of cold-season storms over the western United States

Winter storms are responsible for billion-dollar economic losses in the western US. As storm structures are not well resolved by global climate models, event-scale storm response to warming has not been well established. Here regional storm-resolving simulations are used to investigate climate change impact on western US winter storms. In mid-century under a high emissions scenario, precipitation volume from the top 20% of winter storms is projected to increase by up to 40% across the region. Increased area coverage and storm intensity explain 69% and 60% of this increase, respectively, while a robust sharpening of future storms with larger increase in storm center precipitation than increase in storm area offsets the increase by 31%. Ignoring the changing area-intensity relationship due to storm sharpening could overestimate the watershed design storms by up to 10% or 7-75mm across the western US. Future storm structural changes have broad infrastructure, hydrological, and ecological implications.

54 ENVIRONMENTAL SCIENCES↗

Hybrid Natural Gas Geothermal Combined Cycle Power Plant Analysis

Low temperature geothermal resources, including those associated with oil and gas production, are an underutilized source of low carbon energy. The present work investigates coupling of low-temperature geothermal resources with concentrating solar and/or natural gas energy sources to increase the number of locations at which power generation from low temperature geothermal resources would be technically and economically viable. Stand-alone and hybrid geothermal power cycles are simulated using SimTech IPSEpro process modeling software. Design point strategies for a hybrid power cycle that may operate with either a single heat source or two simultaneous heat input sources are considered. Additionally, off-design power plant operation is investigated to consider the impacts of the heat source availability and ambient temperature variations. The off-design analysis utilizes a modeling tool that predicts power plant performance at each time step as a function of topping cycle heat input (from gas or solar), bottoming cycle heat input (from geothermal), and ambient temperature. Addition of a steam topping cycle to an organic Rankine cycle geothermal power plant provides opportunities to increase the efficiency and power output relative to a stand-alone geothermal power plant. Additionally, use of the waste heat from gas turbine power generation in a geothermal bottoming cycle provides opportunities to increase the amount of power generation associated with each unit of carbon dioxide emitted. This paper will describe the hybrid plant configuration evaluated, discuss the predicted power cycle performance, and compare with stand-alone natural gas and geothermal power generation cases. The power cycle investigated is expected to be applicable for use with conventional hydrothermal resources as well as with geologic thermal energy storage applications and/or enhanced geothermal systems. The steam topping cycle could use a concentrated solar heat source for fully renewable hybrid plant configuration. A plant initially constructed with a natural gas topping cycle heat source could be converted to a solar heat source part way though the power cycle operational life to achieve life cycle carbon emission reductions.

concentrating solar power↗

High Temperature Steam Electrolysis Process Performance and Cost Estimates

Technology readiness levels (TRLs) of electrolysis systems have dramatically increased in recent years as the interest in clean hydrogen production and decarbonization of transportation, industrial and other sectors increases across the globe. This is especially true of high temperature steam electrolysis (HTSE) / solid oxide electrolysis cell (SOEC) systems which show promise of much higher system efficiencies than other more developed electrolysis technologies. This possibility of higher efficiencies of HTSE / SOEC systems has been previously assumed to be theoretically possible but in recent years it has become less theoretical and more realistic as an increasing amount of suppliers complete lab and pilot tests showing very promising results. Research in the areas of manufacturing techniques, material selection, electrode and electrolyte compositions, and balance of plant size and integration continues at a fast pace as an increasing number of suppliers both internationally and domestically become involved. The advantages of HTSE become more pronounced when HTSE is coupled with nuclear power plants (NPPs). This is because thermal energy produced by the nuclear reactor can be used in a series of heat transfer loops and heat exchangers to vaporize HTSE feedwater, which drastically improves the economics of the process. Idaho National Laboratory (INL) has been very involved in the research and modeling of HTSE systems for a number of years, in collaboration with other national laboratories, academia, and industry stakeholders both on the hydrogen production as well as the hydrogen demand side. The modeling completed over the years on a large variety of projects has led to a wealth of knowledge at INL including in the area of the technoeconomic assessment (TEA) of HTSE systems. TEAs include process modeling of the HTSE systems to calculate system energy requirements and equipment sizing, followed by estimation of capital and operating costs to enable calculation of the levelized cost of hydrogen (LCOH). The TEA work performed has produced incremental improvements and tuning of the methods, assumptions, models, and results of the analyses as well as providing some opportunities for validating these results. The purpose of this document is to record the current baseline HTSE analyses led by INL to show the current status of assumptions and costs of these systems. Given the rapid development of this technology, the variety of suppliers entering the space, and the increasing attention government and industry are giving to such systems, this document may be updated on a periodic basis with updated analysis and assumptions. This document compiles various analyses results and approaches completed over a period of years into a single document to be used as a baseline going forward. It represents what the INL HTSE analysis group assumes to be the internal best estimate of the current operation, costs, and landscape of the HTSE industry state of the art capability for current SOEC technology in an Nth-of-a-Kind (NOAK) plant, which in this study is defined as existence of the manufacturing capacity to support previous deployment of N = 100 count of 25 MWe modular HTSE blocks (with modular equipment component cost reductions specified as following a 95% learning curve). That said, This is a public document and as such so no proprietary data was used or included in this report. There may be HTSE suppliers that have performance specifications, and cost estimates, and test data that differ from the analysis presented in this document. This document is meant to be a best conservative estimate of the technology and not an absolute reference.

08 HYDROGEN↗

CRADA Number NFE-17-06866 with Active Energy Systems, Inc. (CRADA Final Report)

Cooperative Research and Development Agreement (CRADA) NFE-17-06866 between Oak Ridge National Laboratory (ORNL) and Active Energy Systems Inc. (AES) focused on studying and modeling a low cost, high efficiency energy storage technology. The successful development of low-cost, high-efficiency energy storage is a significant bottleneck in the implementation of intermittent renewable energy sources such as wind and solar. AES is a startup company developing a heat exchange technology to utilize a low-temperature phase change material (PCM). The work done under this CRADA explored this technology’s ability to augment a heat pump/heat engine device to convert electricity into thermal energy and vice versa, operating to complement the needs of the electric grid. Modeling, design and development of a prototype to prove the technology was successful, but current production economics and market demand make further exploration undesirable.

25 ENERGY STORAGE↗

Advanced Compact Generation Module with Fish Safe Runner Technology

Hydropower is an important contributor of stable, load-leveling renewable energy to our national grid. Increasingly, the development of new hydropower facilities or the retrofit of existing ones hinges not only on minimizing costs but also environmental impact. In this report, the analysis and testing of a modular and scalable low-head hydropower generation design using Natel Energy’s Restoration Hydro Turbine is described. This design leverages many established industry approaches for compactness and efficiency while simultaneously allowing for safe downstream fish passage through the turbines themselves. This unique approach reduces overall hydropower facility costs and enables a simpler inclusive method of project design and operation. To assess this design, mechanical and fluid computational analyses were used to study and optimize key parameters. Passage tests of important migratory species (salmonids, American eel) were conducted through representative turbines. The unique propeller geometry of the fish-safe Restoration Hydro Turbine was subjected to detailed design and testing using advanced manufacturing composite techniques. Comprehensive module cost models were developed and assessed alongside hydraulic efficiency. The results of this project show promising and economical applications for downstream passage offish through Restoration Hydro Turbine modules.

13 HYDRO ENERGY↗

From tensors to qubits

We discuss recent progress in Tensor Lattice Field Theory and economical, symmetry preserving, truncations suitable for quantum computations or simulations. We focus on spin and gauge models with continuous Abelian symmetries such as the Abelian Higgs model and emphasize noise-robust implementations of Gauss's law. We discuss recent progress concerning the comparison between field digitizations and character expansions, symmetry breaking in tensor language, wave-packet preparation and possible new implementations of Abelian models using Rydberg atoms.

Meurice, Yannick↗

High Temperature Steam Electrolysis Process Performance and Cost Estimates - DOE Hydrogen Program AMR Presentation

Technology readiness levels (TRLs) of electrolysis systems have dramatically increased in recent years as the interest in clean hydrogen production and decarbonization of transportation, industrial and other sectors increases across the globe. This is especially true of high temperature steam electrolysis (HTSE) / solid oxide electrolysis cell (SOEC) systems which show promise of much higher system efficiencies than other more developed electrolysis technologies. This possibility of higher efficiencies of HTSE / SOEC systems has been previously assumed to be theoretically possible but in recent years it has become less theoretical and more realistic as an increasing amount of suppliers complete lab and pilot tests showing very promising results. Research in the areas of manufacturing techniques, material selection, electrode and electrolyte compositions, and balance of plant size and integration continues at a fast pace as an increasing number of suppliers both internationally and domestically become involved. The advantages of HTSE become more pronounced when HTSE is coupled with nuclear power plants (NPPs). This is because thermal energy produced by the nuclear reactor can be used in a series of heat transfer loops and heat exchangers to vaporize HTSE feedwater, which drastically improves the economics of the process. Idaho National Laboratory (INL) has been very involved in the research and modeling of HTSE systems for a number of years, in collaboration with other national laboratories, academia, and industry stakeholders both on the hydrogen production as well as the hydrogen demand side. The modeling completed over the years on a large variety of projects has led to a wealth of knowledge at INL including in the area of the technoeconomic assessment (TEA) of HTSE systems. TEAs include process modeling of the HTSE systems to calculate system energy requirements and equipment sizing, followed by estimation of capital and operating costs to enable calculation of the levelized cost of hydrogen (LCOH). The TEA work performed has produced incremental improvements and tuning of the methods, assumptions, models, and results of the analyses as well as providing some opportunities for validating these results. The purpose of this document is to record the current baseline HTSE analyses led by INL to show the current status of assumptions and costs of these systems. Given the rapid development of this technology, the variety of suppliers entering the space, and the increasing attention government and industry are giving to such systems, this document may be updated on a periodic basis with updated analysis and assumptions. This document compiles various analyses results and approaches completed over a period of years into a single document to be used as a baseline going forward. It represents what the INL HTSE analysis group assumes to be the internal best estimate of the current operation, costs, and landscape of the HTSE industry state of the art capability for current SOEC technology in an Nth-of-a-Kind (NOAK) plant, which in this study is defined as existence of the manufacturing capacity to support previous deployment of N = 100 count of 25 MWe modular HTSE blocks (with modular equipment component cost reductions specified as following a 95% learning curve). That said, this is a public document and as such so no proprietary data was used or included in this report. There may be HTSE suppliers that have performance specifications, and cost estimates, and test data that differ from the analysis presented in this document. This document is meant to be a best conservative estimate of the technology and not an absolute reference.

08 HYDROGEN↗

Regional Hybrid Energy Systems Technoeconomic Analysis

This presentation summarizes the final outputs from a multi-year HFTO-funded project that evaluated the potential for hybridized nuclear power plants to economically produce hydrogen. The focus of this presentation is on the interactions between the electricity system modeling and hydrogen system optimization and the resulting figures of merit. This project partnered with Idaho National Laboratory, Argonne National Laboratory, Electric Power Research Institute, and Xcel Energy.

ENERGY PLANNING, POLICY, AND ECONOMY,HYDROGEN↗

Climate-Water-Electricity Interactions in the U.S. Under Alternative Decarbonized Futures

The U.S. electric sector is rapidly evolving, with widespread renewable energy deployment, building and transport electrification, and nuanced decarbonization policies. Climate change influences the supply and demand for electricity by altering water resources for cooling and hydropower, thermal plant efficiencies, and heating and cooling demand. This research combines global climate model data, asset-level water and streamflow modeling, and electric sector capacity expansion modeling to study climate-water-electricity interactions across myriad future climate and electricity scenarios that consider electrification and decarbonization using renewable, hydrogen, carbon capture, and nuclear technologies. Multi-model integration leads to insights into power-water sector interactions and their impacts on grid economics and environmental outcomes.

climate change↗

Techno-Economic Analysis and Life Cycle Assessment of the Production of Biodegradable Polyaliphatic–Polyaromatic Polyesters

Poly(butylene-adipate terephthalate) (PBAT) is a polyaliphatic–polyaromatic polyester that is biodegradable and has found application in several markets, making it a widely produced biodegradable polymer worldwide. However, the production of PBAT is carbon-intensive, as it relies on the use of petroleum-based monomers. There is, thus, significant interest in identifying polyesters that are biodegradable and less carbon-intensive (e.g., use of biomass- derived monomers). In this work, we develop a detailed process model (and an associated database) for the production of polyaliphatic–polyaromatic polyesters including petroleum-based PBAT and biomass-derived alternatives including poly(pentylene- adipate terephthalate) and poly(pentylene-adipate furandicarboxy- late). Techno-economic analysis (TEA) reveals that the production costs of these polyesters strongly depend on monomer costs (accounting for over 90% of the total production cost) and identifies market conditions under which biomass-based polyesters can be cost-competitive to petroleum-based PBAT. Life cycle assessment (LCA) shows that biomass-derived polyesters can reduce the global warming impact of PBAT by half. Altogether, the proposed TEA/LCA model aims to provide guidance into polyesters that are most promising and help assess their overall economic and environmental performance.

42 ENGINEERING↗

Economic and biophysical limits to seaweed farming for climate change mitigation

Net-zero greenhouse gas (GHG) emissions targets are driving interest in opportunities for biomass-based negative emissions and bioenergy, including from marine sources such as seaweed. Yet the biophysical and economic limits to farming seaweed at scales relevant to the global carbon budget have not been assessed in detail. We use coupled seaweed growth and technoeconomic models to estimate the costs of global seaweed production and related climate benefits, systematically testing the relative importance of model parameters. Under our most optimistic assumptions, sinking farmed seaweed to the deep sea to sequester a gigaton of CO 2 per year costs as little as US$\$$480 per tCO 2 on average, while using farmed seaweed for products that avoid a gigaton of CO 2 -equivalent GHG emissions annually could return a profit of $\$$50 per tCO 2 -eq. However, these costs depend on low farming costs, high seaweed yields, and assumptions that almost all carbon in seaweed is removed from the atmosphere (that is, competition between phytoplankton and seaweed is negligible) and that seaweed products can displace products with substantial embodied non-CO 2 GHG emissions. Moreover, the gigaton-scale climate benefits we model would require farming very large areas (>90,000 km 2 )—a >30-fold increase in the area currently farmed. Our results therefore suggest that seaweed-based climate benefits may be feasible, but targeted research and demonstrations are needed to further reduce economic and biophysical uncertainties.

60 APPLIED LIFE SCIENCES↗

Code Benchmark of the HTTF Pressurized Conduction Cooldown Test Using SAM

The High Temperature Test Facility (HTTF) at Oregon State University is an integral system test facility to simulate postulated reactor transients of prismatic high-temperature gas-cooled reactors(HTGRs). A series of test campaigns was launched, providing abundant test data that could be used to benchmark reactor system analysis codes like the System Analysis Module (SAM). In this study, a SAM model of the facility is developed based on the two-dimensional (2D) ring model approach. All components including the ceramic matrix, graphite heaters, helium coolant channels, core barrel, upcomer, pressure vessel, and reactor cavity cooling system are modeled as concentric cylindrical rings. The model is used to simulate one of the benchmark problems-Pressurized Conduction Cooldown (PCC)-within the scope of the Organisation for Economic Co-operation and Development Nuclear Energy Agency International HTTF Benchmark. The simulations consist of two parts. In the first part, operating and boundary conditions as well as thermophysical properties of materials are specified for the benchmark problem. In this work, results from the first part will be used in code-to-code comparison. In the second part, the SAM model is used to simulate Test PG-27, which is the first PCC test carried out in the HTTF, with only two of the ten heater banks activated. The results in the second part are used for code-to-data comparison. Because the helium coolant flow rate is not measured in this facility, it is estimated using the input power and inlet/outlet coolant temperatures. Additionally, radial heat flow in the ceramic blocks is complicated by hundreds of cylindrical coolant channels and heater rods embedded in them. As such, it is necessary to deduce an effective thermal conductivity for the ceramic to analyze the core thermal behavior. SAM predictions of the helium coolant and ceramic temperatures are compared with test data measured in three equivalent sectors. Overall, the SAM results agree reasonably well with test data within the variation of data among the three sectors, which demonstrates SAM's capability in capturing transient effects in HTGR using the simplified 2D ring model.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗