SEARCH · Engineering Papers

Results for “energy systems model”

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

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,171 records · Page 65

All sources NASA NTRS DOE OSTI

NASA NTRS2001

Momentum and Energy Assessments with NASA and Other Model and Data Assimilation Systems

Aspects of the angular momentum cycle, energetics, and related diagnostics from a number of models, including some from the Goddard Laboratory for Atmospheres, and from the Atmospheric Model Intercomparison Project (AMIP) are examined. Torques that dynamically excite changes in angular momentum, including strong torques at mountains were studied. The measure of how atmospheric mass from a strong weather signal can notably change the angular momentum is studied. For AMIP, there is a spread in the angular momentum amongst models, while the GLA model does reasonably well compared to the other models in the diagnostics examined, namely angular momentum and water vapor. Trends and interannual variability in water vapor over a lengthy period was examined. The role of the diabatic heating components, especially latent heating, in the energy cycle and the terms converting available potential energy to kinetic energy, among other parts of the energy cycle, are studied. Modes of climate of the atmosphere, especially the Arctic and North Atlantic Oscillations, are analyzed as well.

Salstein, David↗

NASA NTRS1976

Tests of a reduced-scale experimental model of a building solar heating-cooling system

An experimental solar heating and cooling system model has been built and operated, combining elements that are programmable (e.g., heating and cooling load of a building and collected solar energy) with experimental equipment. The experimental system model was based on the loads and components used in the Solar Building Test Facility (SBTF), which includes a 1394 sq m solar collector field at NASA Langley. These tests covered 5 continuous days under summer conditions. For the system model up to 55 percent of the simulated collected solar energy was used for the building load. This amount of solar energy supplied 35 percent of the building cooling load. Heat loss was significant. If tank heat loss were eliminated, which would make it similar to the actual SBTF, 75 percent of the collected solar energy would be used. This amount would supply approximately 50 percent of the building cooling load. A higher fraction of solar energy is possible with a more performance-optimized system.

Namkoong, D.↗

DOE OSTI2023

Multiscale Electricity Modeling for Evaluating Carbon Capture and Sequestration Technologies (Final Report)

Carbon capture and sequestration (CCS) technologies that can operate with a high degree of operating flexibility could provide necessary electric grid flexibility in a system with high shares of variable renewables. This project examines the deployment and dispatch potential of twelve unique flexible CCS (FLECCS) technologies that encompass post-combustion carbon dioxide (CO 2 ) capture designs, concepts using a storage media to enable energy arbitrage, and hybrid processes that integrate CCS with direct air capture (DAC) for flexibility with net zero or negative CO 2 emissions. FLECCS technology potential is explored with a multi-model, multi-scale framework including the Regional Energy Deployment System (ReEDS) electric sector capacity expansion model (CEM) and the PLEXOS production cost model (PCM). Innovative methods were developed to represent FLECCS technology operating modes, performance, and cost in the two models. ReEDS was then used to simulate nine scenarios for each FLECCS technology, three CO 2 emissions price futures reaching $\$$150, $\$$225, and $\$$300/tCO 2 in 2050; and three scenarios for FLECCS technology deployment favorability relative to competing technologies. For each CO 2 price and reference FLECCS favorability, the 2050 infrastructures from ReEDS model are downscaled and implemented in PLEXOS to examine hourly dispatch under detailed operational constraints that are not included in ReEDS. FLECCS technologies exhibited a wide range of deployment potential ranging from none to several hundred gigawatts of capacity, with outcomes highly sensitive to input cost and performance parameters that are inherently highly uncertain. When deployed, FLECCS tended to displace a combination of wind, solar, and natural gas-based technologies rather than supporting increased renewable deployment. As a result, CO 2 emissions reductions facilitated by FLECCS deployment tended to come with higher overall system costs and electricity prices. When economically competitive, FLECCS technologies can contribute significant flexible generation and firm capacity to the grid, but continued technology development and an expanded analytical scope are necessary to fully understand FLECCS deployment potential its impact on the electric power sector. Follow-on analysis incorporating captured CO 2 tax credit value from the Inflation Reduction Act (IRA) and other potential policy scenarios could be particularly valuable, as this policy can substantially change the relative competitiveness of FLECCS technologies.

03 NATURAL GAS↗

DOE OSTI2020

A Model for Evaluating the Configuration and Dispatch of PV Plus Battery Power Plants

An open-source model was developed to optimize energy storage operation for photovoltaic- (PV-) plus-battery systems with AC-coupled and DC-coupled configurations. It includes the ability to use forecast energy prices to optimize battery charge and discharge on a rolling time horizon. The model allows for exploration of different configurations, including capital costs, inverter performance, dispatch flexibility, and capturing otherwise clipped energy for the DC-coupled system. The model can run 20 full years of hourly data in approximately two seconds, allowing comparison of a large number of configurations. We applied the model in a test case demonstrating reduced inverter clipping for DC-coupled systems and yielded slightly higher overall value than AC-coupled systems, with an approximately 2 percent increase in internal rate of return or benefit/cost ratio. Our results show that at current estimated prices for lithium-ion battery systems, large-scale PV-plus-battery plants are economically viable under the right conditions, with the configuration playing a role in system flexibility and performance. This model provides the ability for project developers, industry professionals, and researchers to use readily available software to quickly evaluate and design these systems.

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

DOE OSTI2021

Unprecedented cloud resolution in a GPU-enabled full-physics atmospheric climate simulation on OLCF’s summit supercomputer

Clouds represent a key uncertainty in future climate projection. While explicit cloud resolution remains beyond our computational grasp for global climate, we can incorporate important cloud effects through a computational middle ground called the Multi-scale Modeling Framework (MMF), also known as Super Parameterization. This algorithmic approach embeds high-resolution Cloud Resolving Models (CRMs) to represent moist convective processes within each grid column in a Global Climate Model (GCM). The MMF code requires no parallel data transfers and provides a self-contained target for acceleration. This study investigates the performance of the Energy Exascale Earth System Model-MMF (E3SM-MMF) code on the OLCF Summit supercomputer at an unprecedented scale of simulation. Hundreds of kernels in the roughly 10K lines of code in the E3SM-MMF CRM were ported to GPUs with OpenACC directives. A high-resolution benchmark using 4600 nodes on Summit demonstrates the computational capability of the GPU-enabled E3SM-MMF code in a full physics climate simulation.

58 GEOSCIENCES↗

DOE OSTI2022

Building Initial Dynamic System Models for Digital Twins of the Cryogenic Moderator System at the ORNL Spallation Neutron Source

This work describes the initial development of dynamic system models of the cryogenic moderator system (CMS) of the Spallation Neutron Source (SNS) at ORNL as a part of the ORNL LDRD funded project Building TRANSFORM to Accelerate Digital Twin Applications for Nuclear Systems, LOIS 10563. The goal of the work is to start the dynamic system modeling effort with the end goal of using them for real-time applications as digital twins. The CMS is a cryogenic liquid hydrogen flow loop that provides moderation of the neutrons that are generated by the SNS. For optimal neutron production, the CMS needs to maintain a steady and controlled density of cryogenic hydrogen in the moderator section thus requiring precise temperature and pressure control. Due to the varied time scales and system characteristics, control of the system is complex, and diagnostics are also difficult. Difficulty in accessing the flow loop during operations, limited instrumentation and unknown design details of the equipment combine to make the case for having sophisticated digital twin models of the system. Operationally the CMS also provides a strong use case for digital twins due to the constant need of optimization and for troubleshooting/diagnostics. The large amount of data collected which are freely available for using in building the model and verifying and validating the model also makes it a great candidate for a proof-of-concept for digital twins. The project extends ORNL's capacity of development and implementation of the open-source dynamic system modeling tool TRANSFORM for engineering design and digital twin/real-time applications. Specific system configuration data for the CMS have been gathered and an initial dynamic model was created in the TRANSFORM library using Dymola as the solution platform. Models of increasing complexity are created to demonstrate the need for a multi-layered approach in digital twin modeling depending on the scale and phenomena being focused on. The dynamic modeling is shown to bring the dynamic operational aspects to the design process for systems as well as serve as a digital twin to the hardware and allow for models to be tuned and compared against real time operational data. These aims should help to push forward strategic goals of application of digital twins and increase the impact of ORNL systems modeling capabilities with TRANSFORM/Modelica for various advanced energy systems.

42 ENGINEERING↗

DOE OSTI2023

Representing the Future Role of Hydropower and Pumped Storage Hydropower (PSH) in Electricity Planning Tools

Existing tools for long-term electric sector planning struggle to represent hydropower's nuanced site-specific technical and operating characteristics, which depend on technical specifications as well as water management practices and regulations. As a result, long-term planning models and tools insufficiently characterize hydropower value and incentives, and they cannot fully represent the role hydropower can play in a future electricity system that could include a high penetration of variable wind and solar generation, battery storage, and other low-carbon technologies. This presentation demonstrates the culmination of a multi-year effort to enhance hydropower representations in electricity planning models at the National Renewable Energy Laboratory (NREL), as part of the U.S. Department of Energy (USDOE) HydroWIRES Initiative. New modeling techniques are demonstrated using the NREL Regional Energy Deployment System (ReEDS), an open-access electric sector capacity expansion model used extensively in a wide range of technology deployment and integration analysis, including the 2016 USDOE Hydropower Vision. ReEDS uses a least-cost optimization approach to understand investment and operation of electricity generation, storage, and transmission technologies under future scenarios of electricity technology innovation, demand, policy, and other sectoral drivers. ReEDS was modified to better represent value and opportunities for both pumped storage hydropower (PSH) and hydropower systems without pumping. We incorporated a new national closed-loop PSH resource and cost assessment to explore new PSH deployment opportunities and added plant-level data to better represent the existing PSH fleet. New upgrade pathways enable opportunities for enhanced hydropower flexibility by adding pumps, upgrading dispatchability, increasing capacity, or increasing energy availability. The model was also modified to better represent the value of long-duration energy storage beyond diurnal time scales, allowing both hydropower and PSH to better balance energy supply and demand variations in high-renewable systems. These new features are demonstrated under reference and high-renewable futures and a range of sensitivity scenarios to understand which hydropower and PSH deployment and upgrade opportunities are the most attractive. These scenarios indicate potential for new closed-loop PSH deployment and for hydropower flexibility improvements to have important impacts on long-term electricity system emissions and economic outcomes. Increasing flexibility of the existing hydropower fleet can reduce the need to invest in new flexible grid technologies and help achieve decarbonization goals. Systems with sufficient energy storage could also be valuable for balancing seasonal differences in renewable energy availability, particularly from solar energy. The methods developed for ReEDS and subsequent scenario results reveal important considerations for future hydropower and grid system planning, and all data and code is freely available in a public code repository for use throughout the hydropower industry.

capacity expansion↗

NASA NTRSDate not supplied

CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_FM1+FM2_Edition2)

The ERBE-like Monthly Geographical Averages (ES-4) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2002-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

NET FLUX↗

DOE OSTI2024

Rancor-HUNTER: A Virtual Plant and Operator Environment for Predicting Human Performance

Advances in simulation capabilities to model physical systems have outpaced the development of simulations for humans using those physical systems. There is an argument that the infinite span of potential human behaviors inherently render human modeling more challenging than physical systems. Despite this challenge, the need for modeling humans interacting with these complex systems is paramount. As technologies have improved, many of the failure modes originating from the physical systems have been solved. This means the overall proportion of human errors has increased, such that it is not uncommon to be the primary driver of system failure in modern complex systems. Moreover, technologies such as automated systems may introduce emerging contexts that can cause new, unanticipated modes of human error. Therefore, it is now more important than ever to develop models of human behavior to realize overall system error reductions and achieve established safety margins. To support new and novel concepts of operations for the anticipated wave of advanced nuclear reactor deployments, human factors and human reliability analysis researchers need to develop advanced simulation-based approaches. This talk presents a simulation environment suitable to both collect data and then perform Monte Carlo simulations to evaluate human performance and develop better models of human behavior. Specifically, the Rancor Microworld Simulator models a complex energy production system in a simplified manner. Rancor includes computer-based procedures, which serve as a framework to automatically classify human behaviors without manual, subjective experimenter coding during scenarios. This method supports a detailed level of analysis at the task level. It is feasible for collecting large sample sizes required to develop quantitative modelling elements that have historically challenged traditional full-scope simulator study approaches. Additionally, the other portion of this experimental platform, the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER), is presented to show how the collected data can be used to evaluate novel scenarios based on the contextual factors, or performance shaping factors, derived from Rancor simulations. Rancor-HUNTER is being used to predict operator performance with new procedures, such as results from control room modernization or new-build situations. Rancor-HUNTER is also proving a useful surrogate platform to model human performance for other complex systems.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

Combined Land Use of Solar Infrastructure and Agriculture for Socioeconomic and Environmental Co-Benefits in the Tropics

Solar photovoltaics (PV) are on the rise even in areas of low solar insolation. However, in developing countries with limited capital, land scarcity, or with geographically isolated agrarian communities, large solar infrastructures are often impractical. In these cases, implementation of low-density PV over existing crops may be required to integrate renewable energy services into rural communities. Here, using Indonesia as a model system, we investigated the land use, energy, greenhouse gas emissions, economic feasibility, and the environmental co-benefits associated with off-grid solar PV when combined with high value crop cultivation. The life cycle analyses indicate that small-scale dual land-use systems are economically viable in certain configurations and have the potential to provide several co-benefits including rural electrification, retrofitting diesel electricity generation, and electricity for processing agricultural products locally. A hypothetical full-density off-grid solar PV for a model village in Indonesia shows that electricity output (1907.5 GJ yr-1) is much higher than the total residential consumption (678 GJ yr-1), highlighting the opportunity to downscale the PV infrastructure by half to lower capital cost, to co-locate crops, and to support secondary income generating activities. Economic analysis shows that the 30-year net present cost of electricity from the half-density co-located PV system (12,257 million IDR) is significantly lower than that of the flat cost of diesel required to generate equivalent electricity (14,702 million IDR). Our analysis provides insights for smarter energy planning by optimizing the efficiency of land use and limiting conversion of agricultural and forested areas for energy production.

agrivoltaics↗

DOE OSTI2022

Multiscale simulation of integrated energy system and electricity market interactions

Accelerating the deep decarbonization of the world's electric grids requires the coordination of complex energy systems and infrastructures across timescales from seconds to decades. Here, we present a new multiscale simulation framework that integrates process- and grid-centric modeling paradigms to better design, operate, and control integrated energy systems (IESs), which combine multiple technologies, in wholesale energy markets. Traditionally, IESs are analyzed with a process-centric paradigm such as levelized cost of electricity (LCOE) or annualized net revenue, ignoring important interactions with electricity markets. This framework explicitly models the complex interactions between an IES's bidding, scheduling, and control decisions and the energy market's clearing and settlement processes, while incorporating operational uncertainties. Through two case studies, we show the importance of understanding and quantifying complex resource-grid interactions. In case study 1, we demonstrate that optimized bidding from one resource shifts the profit distribution for all energy systems in the market. This result suggests new and more flexible IES technologies can disrupt the economics of all market participants, possibly leading to accelerated retirements of less flexible resources. Interestingly, the optimized bidding has little impact on grid-level aggregate statistics, such as total generation costs and renewable penetration rate. While aggregate modeling strategies may remain valid under some IES adoption scenarios for analysis focused on regional outcomes, direct comparisons of IES technologies at specific locations without considering these interactions may lead to misleading or incorrect conclusions. In case study 2, we consider the design and flexible operation of IESs that hybridize conventional generators with energy storage. Through a sensitivity analysis, we find that as the size of the storage system increases, the total number of start-ups for coal- and natural gas-based IESs reduced by 25% and 33.6%, and the total thermal generator ramping (i.e., mileage) reduced by 86.5% and 62.5%, respectively. This shows the primary benefit of storage may not be reduced operational costs (which do not change significantly) but fewer start-ups and less ramping, which may greatly simplify the design, operation, and control of carbon capture systems. The new modeling and optimization capabilities from this work enable the coupling of rigorous, dynamic process models with grid-level production cost models to quantitatively identify the nuanced interdependencies across these vast timescales that must be addressed to realize clean, safe, and secure energy production. Moreover, the proposed general multiscale simulation framework is applicable to all IES technologies and can be easily extended to consider other energy carriers (e.g., hydrogen, ammonia) and energy infrastructures (e.g., natural gas pipelines).

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

SECURED: Simulator-Enhanced Control and Understanding of Reactor systems for cyber-Event Defense

The study discusses a learning approach for analyzing cyber-events in reactor systems using integrated hardware and personal computer simulator models. Key points include the rise in cyber-attacks and their sophistication in industrial control systems (ICS), the necessity for awareness, understanding, resource allocation, and preparation to combat these threats, and the digital transformation of old and new nuclear plants, increasing their exposure to cyber threats. It highlights the cyber vulnerabilities of advanced reactor systems, which rely on digital instrumentation and control for operations and safety functions, making them susceptible to cyber-attacks. The approach involves demonstrating reactor system plant ICS cyber-attacks under various operational conditions utilizing tools like simulator models and hardware-based kits. A strategic solution approach tailored to critical infrastructure is emphasized, along with community engagement for public and government support, adopting effective learning approaches, and the preparation for anticipated future challenges. The presentation concludes with a call to action to address challenges, leverage opportunities, and advance through lesson learning in cybersecurity for nuclear energy systems.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2025

CFD Validation of a Methanation Reactor With Cooling Jacket Used in an ISRU Propellant Production System

A digital model of an OxEon Energy methanation reactor (with a cooling jacket) planned for use in a NASA designed In-Situ Resource Utilization (ISRU) propellant production system was developed by the UTEP Aerospace Center using STAR-CCM+ software, a Siemens Computational Fluid Dynamics (CFD) package. The reactor digital model created includes two primary components: (i) a cooling jacket that maintains the required reactor chamber surface temperature and (ii) a reactor core chamber where the exothermic methanation reactions occur. The StarCCM+ digital model has two objectives: (i) maintain the surface temperature of the reactor below a set value so that the extra heat accumulation does not melt or crack the chamber, and (ii) produce the desired amount of methane (CH4) according to test cases completed by OxEon Energy for NASA JSC. The computational digital model was validated with the test data enabling the cooling jacket scale to be predicted based on the reactor's operating temperature. The StarCCM+ simulation of the digital model shows a good agreement with the cooling jacket performance and the CH4 production. One test case for the cooling jacket maintained the reactor wall temperature around 310 °C was validated and the reactor produced 185 g/hr CH 4 .

ISRU↗

DOE OSTI2025

Electrical and Thermal Load Impacts of Three District Heating and Cooling Designs for an Existing Community in Washington, DC

District energy systems that provide building heating and cooling are a promising option to provide low-cost, energy efficient heating and cooling solutions for communities. As some buildings move to electrified heating designs, there may be significant increases in electric grid demand, particularly in the winter. District energy systems may be able to help reduce these high electrical demands on the electric grid, while also providing decreased overall energy consumption with an increased flexibility in electrical energy usage. To evaluate and compare district options for district-based heating and cooling, an existing neighborhood of Washington, DC consisting of 35 existing buildings was selected as a case study. This study models and compares a fourth generation (4G) district heating and cooling systems that provide hot and chilled water from a central plant directly to each prosumer and a fifth generation (5G) district heating and cooling systems that provide near-ambient water via geothermal boreholes to interface with an energy transfer station with a heat pump at each prosumer. These district systems are compared against a baseline of the non-connected buildings with their self-contained and current HVAC systems. The neighborhood was selected as a good candidate for a district system for its diversity of loads (mix of different commercial and property types) and the availability of building characteristics. URBANopt District Energy Systems (DES) was used to model the buildings and create initial Modelica models for the district systems. Finally, the DES models were tuned and simulated in Dymola, and the outputs were post-processed for verification and to calculate the electrical and thermal grid impact metrics. This is the first documentation of this workflow and its complete analysis. The three designed systems are compared via their grid metrics including: total energy consumption, electrical demand peak loads, daily peak-to-valley ratios, and system ramping. A detailed discussion is provided about how each system impacts and interacts with the electric grid.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

ELM–Wet: Inclusion of a Wet–Landunit With Sub–Grid Representation of Eco–Hydrological Patches and Hydrological Forcing Improves Methane Emission Estimations in the E3SM Land Model (ELM)

Wetlands are the largest emitters of biogenic methane (CH 4 ) and represent the highest source of uncertainty in global CH 4 budgets. Here, we aim to improve the realism of wetland representation in the U.S. Department of Energy's Exascale Earth System Model land surface model, ELM, thereby reducing uncertainty of CH 4 flux predictions. We develop an updated version, ELM-Wet, where we activate a separate landunit for wetlands that handles multiple wetland-specific eco-hydrological patch functional types. We introduce more realistic hydrological forcing through prescribing site-level constraints on surface water elevation, which allows resolving different sustained inundation depth for different patches, and if data exists, prescribing inundation depth. We modified the calculation of aerenchyma transport diffusivity based on observed conductance per leaf area for different vegetation types. We use Bayesian Optimization to parameterize CO 2 and CH 4 fluxes in the developed wet-landunit. Site-level simulations of a coastal non-tidal freshwater wetland in Louisiana were performed with the updated model. Eddy covariance observations of CO 2 and CH 4 fluxes from 2012 to 2013 were used to train the model and data from 2021 were used for validation. Patch-specific chamber flux observations and observations of CH 4 concentration profiles in the soil porewater from 2021 were used for evaluation of the model performance. Our results show that ELM-Wet reduces the model's CH 4 emission root mean squared error by up to 33% and is able to represent inter-daily CO 2 and CH 4 flux variability across the wetland's eco-hydrological patches, including during periods of extreme dry or wet conditions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Leveraging System Dynamics to Predict the Commercialization Success of Emerging Energy Technologies: Lessons from Wind Energy

The United States urgently needs to tackle the climate crisis while enhancing energy security and resiliency. The complexity of the U.S. energy system, with its interconnected elements, makes predicting future states challenging, especially with the introduction of novel energy systems like wind, solar, clean hydrogen, and advanced nuclear technologies. Modern systems engineering methods and tools can provide deeper insights into these dynamics and future behaviors. This research aims to develop a comprehensive model that captures the main elements and behaviors of new energy technologies within the existing energy system. We hypothesized that the market uptake of novel energy systems is influenced by multiple diverse factors, such as technological learning, availability of resources, and economic incentives; examined the history of electricity generation using land-based wind technologies; and developed a system dynamics model to investigate the relationships between capacity growth and influencing factors, both internal and external. The developed model yielded outcomes that confirmed the hypothesized dynamics of wind energy system diffusion through a quantitative comparison of installed capacity and highlighted the significant influence of resource availability, federal incentives (production tax credits), and technological learning on capacity growth and cost reduction. This research aims to support informed decision-making for investments in novel energy systems and aid in developing effective policies for technology deployment.

17 WIND ENERGY↗

DOE OSTI2020

Evaluation of Hybrid FPOG Applications in Regulated and Deregulated Markets Using HERON

Recent changes in the U.S. energy market, such as low natural gas prices and increased electricity production for variable renewable energy (VRE) sources, have led to an economic crisis for existing light-water reactor (LWR) nuclear power plants (NPP). Many owners and operators of LWRs have elected to decommission these plants rather than continue using them as consistent sources of clean baseload power. This has led to exploration of various possibilities to increase the economic viability of these units, including market restructuring to monetize benefits LWRs already provide to the grid through ancillary markets, load following and economic dispatch, and possible integration of secondary systems directly to the NPP for production of additional products through technologies such as hydrogen electrolysis or water desalination. Previous studies have considered the technologies associated with these Integrated Energy Systems (IES) activities, and the analysis of markets for these secondary products. To analyze the economic viability of various system configurations including IES, especially given the uncertainty surrounding load demand, electricity prices, and the availability of VRE resources, the stochastic technoeconomic analysis package HERON (Heuristic Energy Resource Optimization Network) was released earlier this year as an extension of the risk analysis framework RAVEN (Risk Analysis Virtual Environment). HERON focuses foremost on making the complex uncertainty quantification analysis tools approachable for energy systems analysts, also providing general dispatch optimization algorithms for those workflows. HERON continues to be improved and tested as a significant part of the IES viability analyses performed in this work. HERON is not a capacity expansion model. To consider market and grid energy system development in a variety of scenarios, HERON is best used in coupling with modelling tools such as US-REGEN, which sacrifice some of the uncertainty analysis and resolution of HERON's modelling for the ability to efficiently predict the change in the grid energy system's profile due to economic drivers over decades. HERON can then use this information to explore the economic viability of introducing changes to the predicted outcomes, such as the introduction of an IES. In this work, experts at EPRI using US-REGEN provide six projection scenarios for use in HERON stochastic technoeconomic analysis (STEA) in considering the options available for increasing LWR economic viability through introduction of a hydrogen-centric IES using a high-temperature steam electrolysis plant (HTSE), hydrogen storage, and a constant-rate contracted hydrogen consumer. The results obtained are differential in nature; they do not report expected profits for any configuration, but rather report on the possible increase in the NPV of a configuration with respect to a baseline no-IES configuration. Due to the uncertainty captured in the variable net load of the systems, there is likewise uncertainty in the mean values reported. We consider this viability both in terms of a regulated market, where the energy producers and IES are owned and operated by single entity, as well as a deregulated market, where the IES chooses its bid for electricity generation and is then dispatched by the grid system operator. Results indicate that for deregulated markets, the inclusion of the IES is often statistically beneficial. This is especially true in policies that are not favorable towards nuclear, as nuclear is less often dispatched and is forced to deal with frequent idle capacity. In the nominal case as well as the case of carbon tax policies, inclusion of the IES clearly benefited the economic performance of the NPP. In the regulated case, however, there was a trend towards minimizing the IES, likely due to the optimal sizing performed by US-REGEN of the NPP within the system as well as the lack of penalty for idle capacity at the NPP in the regulated market analyses.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRSDate not supplied

CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_Terra-FM1_Edition1-CV)

The ERBE-like Monthly Geographical Averages (ES-4) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2006-09-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

GEOGRAPHIC SCENE TYPE↗