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At least 721 records · Page 40

A Predictive Prescription Framework for Stochastic Unit Commitment Using Boosting Ensemble Learning Algorithms

To take unit commitment (UC) decisions under uncertain load, most existing stochastic optimization (SO) frameworks adopt a generic representation of uncertainty. While load levels that materialize on a particular day are influenced by various covariates (such as the day of the week or temperature), SO frameworks typically disregard such side observations, wasting actionable information that could significantly enhance decision quality. Here, this article proposes a contextual SO (CSO) framework for UC under uncertain load, which can effectively exploit covariate observations in conjunction with a class of machine learning (ML) algorithms to improve the out-of-sample performance of UC decisions. It shows how three ML algorithms, adaptive boosting, gradient boosted trees, and extreme gradient boosting, can be used to this end, constituting the first application of these algorithms in any CSO framework. Using real-world data harvested from the New York ISO grid, we measure the out-of-sample performance of the framework in terms of total operation cost, shed load values, locational marginal prices, and total payments by the loads, against several benchmark methods proposed in the literature. The article has an online companion (Yurdakul et al.), wherein we present additional results and lay out further mathematical formulations used in this work.

42 ENGINEERING↗

TCF - Sustainable Well Cement for Geothermal, Thermal Recovery, and Carbon Storage wells

Primary cementing is the most important operation performed on a subterranean well. Cement, placed in the annulus between the casing and the formations, serves as a hydraulic seal preventing fluids and gas migrations, protecting steel casing from corrosion, and supporting the well structure. Poor cementing jobs can be directly responsible for wells not reaching their full capacity, casing corrosion, compromised well integrity and, in the worst-case scenarios, well collapse. Geothermal, thermal recovery, and carbon storage wells offer environments that are especially difficult for cements to survive while the required lifespan of these wells can be years. In these wells currently used cements cannot provide durable well integrity, and new solutions are necessary. The necessity of stabilizing the electric grid, increasing its flexibility, and providing energy on demand will further expand the market of durable cement solutions for applications in high-temperature underground reservoir thermal energy storage wells (HT RTES). The design challenges of special cement systems for such wells originate from chemistry limitations of currently used well cements, aggressive environments, temperature and repeated shock conditions associated with them, and very weak formations that are not uncommon in these wells. During the last 70 years the most common systems for thermal-well construction have been Ordinary Portland Cement (OPC) (absolute majority of the wells), silica-lime system, and high aluminum cement-containing formulations. The major issues of calcium-silicate hydrates, that form during the hydration of OPC resulting in hardened material, are their poor chemical resistance to acids due to the calcium interactions with acid anions followed by its eventual dissolution, even in mild acids, such as carbonic acid from CO 2 dissolution, and inadequate bonding to the steel causing serious casing corrosion problems (Sugama & Pyatina, 2019). Performance of OPC-based cement may be significantly improved with organic additives; however, those are limited by their temperature stability. An alternative to calcium-silicate cement was developed by BNL and commercialized by Halliburton as ThermaLock TM cement. Calcium-aluminate-phosphate-based chemistry of the material allowed overcoming acid-resistance problems of OPC, especially in CO 2 -rich geothermal environments. In 2012-2015, building upon this experience, BNL developed Thermal Shock Resistant Cement (TSRC) with the support of Geothermal Technology Office (GTO) of DOE. TSRC has high-temperature stable chemistry, superior properties of cement-metal casing bond and corrosion protection (4-times better than currently used OPC-based formulation), significantly outperforms common well-cements in thermal-shock tests, has self-healing properties, and like ThermaLock TM is CO 2 resistant incorporating carbonate ions into stable hydrates (Gill et al., 2012).

15 GEOTHERMAL ENERGY↗

LandCast Mosaic: Reconstructing Global Population Distributions, 1975-2025

LandCast Mosaic (LCM) provides a global, high-resolution gridded population dataset spanning 1975–2025, representing annual, scenario-consistent estimates of daytime, nighttime, and ambient population distributions. LCM builds on the 2025 LandScan Mosaic (LSM) population data by backcasting to earlier years using historical changes in built-surface area derived from the Global Human Settlement Layer (GHSL) and authoritative population counts from international datasets. The workflow scales 2025 building-informed gridded population estimates according to observed changes in built surface, applies linear interpolation for intermediate years, and normalizes estimates to match administrative- and country-level totals. The resulting dataset offers consistent, globally gridded population estimates over fifty years, suitable for temporal analyses of population dynamics, disaster risk modeling, and urban planning applications.

97 MATHEMATICS AND COMPUTING↗

A Novel High Energy Density Sorption-based Thermal Battery for Low-grade Thermal Energy Storage

Thermal energy storage (TES) can alleviate peak demand on the electricity grid by offsetting building thermal loads, increasing the grid’s reliability and resilience. However, low energy density and poor energy performance of existing TES technologies limit their applications. Sorption-based thermal battery (STB) system is thus developed using three-phase sorption technology to harvest low-temperature heat, store it with a much higher energy density than common TES systems and dehumidify air or provide space cooling in buildings. Although STB has been experimentally proved to be feasible, influencing factors on its performance are still unknown by far. Therefore, this paper conducted a parametric analysis on crystallization and crystal dissolution performance of a developed STB test rig. The crystallization results showed that the energy density of the STB increased with reducing the solution flow rate and the cooling water temperature. The dissolution results showed that a higher discharge rate of the STB can be achieved with increasing the flow rate and temperature of inlet diluted solution. The work in this study is helpful to the optimal design and operation of the STB system.

Wang, Lingshi↗

Investigation of Nonflammable Electrolytes for Behind-the-Meter Storage Batteries

Behind-the-Meter Storage (BTMS) is a battery-based, stationary energy storage system that is connected to the residential or industrial customer's side of the electrical grid utility service meter. BTMS systems enable consumers to (A) economically schedule charging and usage of stored energy, (B) store and use energy from on-site generation, especially from inconstant, renewable sources like solar and wind, and (C) avoid overloading the grid during peak hours via supplementation with stored energy. BTMS battery performance requirements and general priorities differentiate from other applications, like EVs, which has prompted the development of batteries with tailored electrode and electrolyte materials. These materials prioritize low cost, avoiding critical materials; longevity, achieving 8000 cycle and 20-year shelf lives; and importantly, high safety. Nonflammable electrolytes show promise to improve safety by mitigating thermal runaway, yet often come with sacrifices to battery performance. In this presentation (1) primary categories of nonflammable electrolytes will be discussed; (2) a rational design of experiment will be presented for efficient performance evaluation of several nonflammables electrolyte in BTMS-relevant battery chemistry, Li4Ti5O12- and LiNi0.90Mn0.10O2; and (3) preliminary results will be presented.

battery↗

Numerical Analysis of Regular Material Point Method and its Application to Multiphase Flows

The material point method (MPM) is gaining wide popularity in engineering research to model and simulate complex multiphase flow dynamics. The method relies on solving the governing equations of motion and transport in a Lagrangian framework using particles also known as material points. The fluid and kinematic properties are stored on the material points while the spatial gradient calculation and temporal integration are performed on a background grid. This Lagrangian framework allows for large deformations, easy integration of constitutive models, and direct import of complex geometries as particles. However, despite their increasing popularity, very few studies have addressed the issues of numerical resolution and stability of MPM techniques. The presence of additional factors such as the number of material points-per-cell, the location of the material points, the CFL-like condition used in time update, and the grid shape functions also increase the complexity of the error analysis when compared to other finite element methods. In this presentation, we analyze the various forms of error incurred in the application of MPM to continuum mechanics and multiphase flows. The effect of the previously mentioned factors on the error dynamics is studied. The application of these principles to canonical and industrial problems is also presented.

high pressure reverse osmosis↗

Semantic Interoperability to Enable Smart, Grid-Interactive Efficient Buildings

Achieving a widespread transition to grid-interactive, efficient buildings (GEBs) depends critically on there being sufficient interoperability among connected building systems. While many critical elements already exist at the technical interoperability level (TCP/IP, BACnet, etc.), a lack of interoperability in the semantic level hinders streamlined integration of interdependent applications. Semantics refers to expressing information about “things” in a way that can be consistently understood by applications. Key components of formalized semantics include identifying what a “thing” is (its “type”), defining general information about that “thing” (its characteristics or properties), and defining the appropriate relationships of that “thing” to other “things” (its function or role in a larger system). Although this might seem initially trivial, the success of smart building applications is highly dependent on maintaining consistent self-descriptive notions of the “things”. Without semantic interoperability, it is technically difficult, labor-intensive, and cost-prohibitive to enable three key objectives of GEBs: optimizing performance, automatically identifying and diagnosing faults, and delivering grid services. Industry, academia, and standards bodies have invested effort in developing information models to facilitate semantic interoperability, however, they have not been widely adopted across the U.S. commercial building portfolio. This paper will present a pathway to drive semantic interoperability through a three-pronged approach to be led by the DOE Building Technologies Office in partnership with NIST and multiple national laboratories comprising: 1) industry engagement and coordination across existing efforts; 2) a semantic interoperability standard that empowers building owners to identify and require interoperable attributes when procuring equipment and applications; 3) tools to assist in implementation and a test framework to verify compliance of products with semantic interoperability specifications. This approach is designed to accelerate the timeline for adoption of semantic interoperability specifications. The intent is to reduce soft costs associated with implementing advanced controls, fault detection and diagnostics, and other smart building technologies and use cases as a necessary step in achieving an energy efficient smart grid future.

Bergmann, Harry↗

Semantic Interoperability to Enable Smart, Grid-Interactive Efficient Buildings

Achieving a widespread transition to grid-interactive, efficient buildings (GEBs) depends critically on there being sufficient interoperability among connected building systems. While many critical elements already exist at the technical interoperability level (TCP/IP, BACnet, etc.), a lack of interoperability in the semantic level hinders streamlined integration of interdependent applications. Semantics refers to expressing information about “things” in a way that can be consistently understood by applications. Key components of formalized semantics include identifying what a “thing” is (its “type”), defining general information about that “thing” (its characteristics or properties), and defining the appropriate relationships of that “thing” to other “things” (its function or role in a larger system). Although this might seem initially trivial, the success of smart building applications is highly dependent on maintaining consistent self-descriptive notions of the “things”. Without semantic interoperability, it is technically difficult, labor-intensive, and cost-prohibitive to enable three key objectives of GEBs: optimizing performance, automatically identifying and diagnosing faults, and delivering grid services. Industry, academia, and standards bodies have invested effort in developing information models to facilitate semantic interoperability, however, they have not been widely adopted across the U.S. commercial building portfolio. This paper will present a pathway to drive semantic interoperability through a three-pronged approach to be led by the DOE Building Technologies Office in partnership with NIST and multiple national laboratories comprising: 1) industry engagement and coordination across existing efforts; 2) a semantic interoperability standard that empowers building owners to identify and require interoperable attributes when procuring equipment and applications; 3) tools to assist in implementation and a test framework to verify compliance of products with semantic interoperability specifications. This approach is designed to accelerate the timeline for adoption of semantic interoperability specifications. The intent is to reduce soft costs associated with implementing advanced controls, fault detection and diagnostics, and other smart building technologies and use cases as a necessary step in achieving an energy efficient smart grid future.

30 DIRECT ENERGY CONVERSION↗

SAM Finite Volume Method Development Status Update: GCR Application, Restart, and MultiApp

The System Analysis Module (SAM) is being developed as a modern system analysis code for advanced non-light-water-reactor safety analysis under the U.S. DOE NEAMS program. Previous feasibility studies have demonstrated that a staggered-grid finite volume method (SG-FVM), implemented under the MOOSE framework, can deliver more than an order of magnitude speedup over the existing continuous Galerkin finite element method (CG-FEM) solver for liquid-cooled, incompressible but thermally expandable flow systems. This work extends the previous effort to compressible, gas-cooled reactor applications, where pressure couples directly into the mass equation adding additional nonlinearity into the equation system. New code capabilities are implemented for pebble bed high-temperature gas-cooled reactor (PB-HTGR) analysis, including a pebble bed CoreChannel component, built-in pebble bed effective thermal conductivity model and channel-to-channel crossflow model. The capabilities are tested, benchmarked, and demonstrated for problems with increased level of model and physical complexities, including the HTTU effective thermal conductivity test, the SANA passive cooling test, and a demonstration case using the GPBR200 reactor design covering steady-state operation, DLOFC and PLOFC transients. Across all cases, the SG-FVM solver demonstrated strong robustness and efficiency, and the solutions agree well with reference results and data. The finding of this work proves that SG-FVM is a viable and efficient solver pathway for compressible, gas-cooled reactor system analysis in SAM. In addition, work has been done to successfully support SAM-FVM recover/restart code feature that is essential to reactor safety analysis applications, and MultiApp code feature that is essential to multi-scale and multi-physics simulations. In summary, this work continued from previous feasibility studies, and further demonstrated that the SG-FVM will serve as a strong foundation for SAM’s advanced solver algorithm for future deployment.

Zou, Ling↗

Safe and Private Forward-trading Platform for Transactive Microgrids

Power grids are evolving at an unprecedented pace due to the rapid growth of distributed energy resources (DER) in communities. These resources are very different from traditional power sources, as they are located closer to loads and thus can significantly reduce transmission losses and carbon emissions. However, their intermittent and variable nature often results in spikes in the overall demand on distribution system operators (DSO). To manage these challenges, there has been a surge of interest in building decentralized control schemes, where a pool of DERs combined with energy storage devices can exchange energy locally to smooth fluctuations in net demand. Building a decentralized market for transactive microgrids is challenging, because even though a decentralized system provides resilience, it also must satisfy requirements such as privacy, efficiency, safety, and security, which are often in conflict with each other. As such, existing implementations of decentralized markets often focus on resilience and safety but compromise on privacy. In this article, we describe our platform, called TRANSAX, which enables participants to trade in an energy futures market, which improves efficiency by finding feasible matches for energy trades, enabling DSOs to plan their energy needs better. TRANSAX provides privacy to participants by anonymizing their trading activity using a distributed mixing service, while also enforcing constraints that limit trading activity based on safety requirements, such as keeping planned energy flow below line capacity. We show that TRANSAX can satisfy the seemingly conflicting requirements of efficiency, safety, and privacy. We also provide an analysis of how much trading efficiency is lost. Trading efficiency is improved through the problem formulation, which accounts for temporal flexibility, and system efficiency is improved using a hybrid-solver architecture. Lastly, we describe a testbed to run experiments and demonstrate its performance using simulation results.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Surface Cloud Grid Version 2 (SFCCLDGRID2) Value-Added Product: Description of Update"

This document describes the algorithm used for the Surface Cloud Grid Value-Added Product (VAP). This VAP uses as input the 15-min. output from the Shortwave (SW) Flux Analysis VAP (see Long 2001; Long and Ackerman 2000; Long et al. 1999) from the Atmospheric Radiation Measurement (ARM) Climate Reseach Facility (ACRF) Southern Great Plains (SGP) Central Facility and extended facilities. This network of 21 sites is unevenly spaced over northern Oklahoma into southern Kansas, covering an area from 95.5° to 99.5° west longitude and 34.5° to 38.5° north latitude. For research applications such as single-column modeling, an estimate of the cloud and cloud effects distribution over this entire domain is desirable. The Surface Cloud Grid VAP applies a multi-pass weighted sum analytic approximation technique (Caracena 1987), which uses Gaussian weighting and an imposed scale length, to interpolate to a 0.25° by 0.25° lat/long grid over the SGP domain. The output, like the input, includes solar elevation angles of 10° or greater.

97 MATHEMATICS AND COMPUTING↗

An Extensible Software and Communication Platform for Distributed Energy Resource Management

This paper introduces a novel Distributed Extensible Grid Control (DEGC) software and communication platform to facilitate the control of distributed energy resources on electric grids. The DEGC software platform leverages state-of-the-art advances in secure, distributed communication and decentralized authorization and authentication. We discuss how these advances enable the kind of robust and secure communication required for a distributed grid control platform, and show how DEGC applies these technologies to the agile development and deployment of grid software through an extensible and flexible API. Here, we describe how DEGC can implement both Volt-VAR voltage magnitude control and Phasor-Based Control as sample applications and demonstrate the DEGC platform in hardware with the demanding Phasor-Based Control test case, and provide performance metrics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Distributed Wind Controls: A Research Roadmap for Microgrids, Infrastructure Resilience, and Controls Launchpad (MIRACL)

The Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) project’s controls research area aims to expand the benefits from distributed wind (DW) generation assets beyond solely providing low cost power directly to consumers. To make distributed wind turbines operate more effectively there is a need for more advanced ways to control them, allowing power companies, businesses, and energy consumers to take advantage of the unique characteristics of wind energy. DW can contribute to the safe and secure operation of grid by providing services such as voltage regulation, frequency regulation, spinning reserves, and even black start capabilities. In the larger DER context where much of the research has focused around solar technologies, the inertia available in wind technologies has generally not been considered. For wind turbines to provide these services in an optimal and expanded way, development and demonstration of control methods and communication interfaces within a grid and microgrid framework are required. In this document, NREL led the literature review in collaboration with SNL, of DER controls-focused integration research to establish a baseline for the controls research under the MIRACL project to identify specific control functions to be focused on throughout this project. This literature review focused primarily on the control functions of variable distributed generation, largely pulling from past solar PV and battery controls works, with a specific focus on applicability for distributed wind energy systems. The goal of this document is to identify a research roadmap based on the open literature and past national laboratory works to inform advanced wind turbine and power electronics control functions for four use cases: 1) distributed wind in isolated systems, 2) grid-connected microgrids (wind-hybrid systems and islanded operation), 3) behind-the-meter distributed wind applications in the power distribution systems, and 4) front-of-the-meter distributed wind applications in the power distribution systems.

17 WIND ENERGY↗

Low-Cost Radiant Heater for Rapid Response, High-Temperature Heating

High-temperature processing has an irreplaceable role in many research and industrial applications. Despite remarkable development spanning over a century, the pursuit of even higher thermal flux density and more rapid thermal transients has not slowed down. As part of the ongoing energy evolution, many industrial applications are transitioning from direct combustion of fossil fuels as primary energy sources to increasing electrification, capable of adapting to renewable power grids. Thus, there is an emerging need for electrical heaters that can replace burners and supply the heat demand, especially at the highest temperatures. In this study, we report on a radiant heater design that can achieve cyclic heating/cooling rates of up to 400 K min –1 and a temperature range in excess of 1,800 K, comparable to those of commercial infrared gold image furnaces, at high surface and volumetric power densities. The heater consists of a modular unit of incandescent tungsten filament and is enclosed in an evacuated ceramic envelope, chemically inert, tolerant of thermal shock, and impervious to gasses. The material and manufacture cost of such heaters, which is estimated at ~$0.05/W, is less than 0.03% of that for infrared gold image furnaces, which is at >$2/W. Tests of more than 10,000 demanding cycles (high temperature and high heating/cooling rate) over 350 h of total operational time and in different temperature ranges confirm the robust performance of radiant heater prototypes. The design is widely applicable to high-temperature reactor and furnace designs. In thermochemistry research and practice, these radiant heaters could offer multiple benefits compared to solar simulators, lasers, infrared gold furnaces, ceramic heaters, or direct concentration of solar input.

99 GENERAL AND MISCELLANEOUS↗

Virtual Cable Impedance based Load Sharing in a Microgrid for Parallel Connected Grid Forming Converters

This paper presents a novel approach to power sharing between direct connected grid-forming converters, utilizing virtual cable impedance and droop-based outer loop control. To enhance stability, resistive droop is implemented, while virtual cable impedance with non-zero resistive and inductive components ensures improved power sharing. The inner loop controller employs a Lyapunov energy function to achieve superior dynamic performance. The proposed control architecture is validated through comprehensive modeling and real-time processor-in-the-loop simulations, demonstrating its robustness and efficiency under various operating conditions. The results highlight the potential of this control strategy to improve the reliability and efficiency of renewable energy systems. Additionally, a comparative analysis with traditional methods underscores the advantages of the proposed approach in terms of stability and performance. The proposed control architecture offers a scalable and flexible solution for grid-forming converters, enabling seamless integration of renewable energy sources. Its robustness and adaptability make it an attractive solution for real-world applications. Furthermore, the approach can be extended to other power electronic systems, enhancing overall system performance and efficiency. By providing a reliable and efficient control strategy, this paper contributes to the advancement of renewable energy systems and their adoption in the energy sector. The proposed control strategy has far-reaching implications for the widespread adoption of renewable energy sources, enabling a more sustainable and efficient energy future. The overall system is modeled in MATLAB/Simulink and PLECS software domain.

grid forming converters (GFM)↗

Trends and 2025 Insights on the Rise of Electric Vehicles in the USA

Plug-in electric vehicles (EVs) are reshaping the transportation energy landscape, providing a practical alternative to petroleum fuels for a growing number of applications. EV sales grew 55x in the past decade (2014-2024) and 6x since 2020, driven by technological progress enabled by policies to reduce transportation emissions as well as industrial plans motivated by strategic value of EVs for global competitiveness, jobs and geopolitics. In 2024, 22% of passenger cars sold globally were EVs and opportunities for EVs beyond on-road applications are growing, including solutions to electrify off-road vehicles, maritime and aviation. This Review updates and expands our 2020 assessment of the scientific literature and describes the current status and future projections of EV markets, charging infrastructures, vehicle-grid integration and supply chains in the USA. EV is the lowest-emission motorized on-road transportation option, with life-cycle emissions decreasing as electricity emissions continue to decrease. Charging infrastructure grew in line with EV adoption but providing ubiquitous reliable and convenient charging remains a challenge. EVs are reducing electricity costs in several US markets and coordinated EV charging can improve grid resilience and reduce electricity costs for all consumers. The current trajectory of technology improvement and industrial investments points to continued acceleration of EVs.

33 ADVANCED PROPULSION SYSTEMS↗

Characterization of solid particle candidates for application in thermal energy storage and concentrating solar power systems

Thermal energy storage (TES) enables concentrating solar power to remain competitive in the renewable energy mix by firming up intermittent solar resource and providing grid services such as load shifting. Free from siting constraints, stand-alone TES systems show promise as a low-cost alternative to traditional pumped-storage hydropower or compressed air energy storage. At the core of all TES technologies is a storage medium, the selection of which governs many aspects of system design and operation. Although the majority of commercial installations utilize molten salts, solid particles can demonstrate stability over wider temperature ranges. This amounts to increased energy storage densities and corresponding reductions in system cost which is essential in achieving low-cost energy storage. In this work, eight solid particle candidates are systematically identified and screened for application in a specific particle-TES system. The five most promising candidates (CARBO CP and HSP, calcined flint clay (CFC), brown fused alumina (BFA), and silica sand) are further characterized by size and morphology for fluidization suitability, flowability for particle transport, and thermal stability. Calcined flint clay and brown fused alumina are eventually down-selected due to thermal instability at the target operational temperature of 1200 °C. Although the physical characteristics of CARBO outperform silica sand in all categories examined, the marginal performance gains are considered insufficient to justify the additional media cost so silica sand is selected as the leading candidate. Within the silica sand (α-quartz) space, the high end of Geldart Group B particles is identified to satisfy the target fluidization regime for the application of interest without compromising particle flowability. Here, in focused testing, Silica 460 is shown to exhibit sufficient stability through long-duration (500-hour) thermal and cyclic testing (1200 °C), 10-hour testing at 1400 °C, and in contact with candidate refractory containment materials. Finally, an average heat capacity of 1.1 J/g∙ °C is measured over 300-1200 °C with a quartz inversion enthalpy (ΔH α-β ) of 10.7J/g.

14 SOLAR ENERGY↗

The Application of a Genetic Algorithm to the Optimization of a Mesoscale Model for Emergency Response

Besides solving the equations of momentum, heat, and moisture transport on the model grid, mesoscale weather models must account for subgrid-scale processes that affect the resolved model variables. These are simulated with model parameterizations, which often rely on values preset by the user. Such “free” model parameters, along with others set to initialize the model, are often poorly constrained, requiring that a user select each from a range of plausible values. Finding the values to optimize any forecasting tool can be accomplished with a search algorithm, and one such process—the genetic algorithm (GA)—has become especially popular. As applied to modeling, GAs represent a Darwinian process: an ensemble of simulations is run with a different set of parameter values for each member, and the members subsequently judged to be most accurate are selected as “parents” who pass their parameters onto a new generation. At the U.S. Department of Energy’s Savannah River Site in South Carolina, we are applying a GA to the Regional Atmospheric Modeling System (RAMS) mesoscale weather model, which supplies input to a model to simulate the dispersion of an airborne contaminant as part of the site’s emergency response preparations. An ensemble of forecasts is run each day, weather data are used to “score” the individual members of the ensemble, and the parameters from the best members are used for the next day’s forecasts. As meteorological conditions change, the parameters change as well, maintaining a model configuration that is best adapted to atmospheric conditions. Significance Statement We wanted to develop a forecasting system by which a weather model is run over the Savannah River Site each day and repeatedly adjusted according to how well it performed the previous day. To run the model, a series of values (parameters) must be set to control how the model will calculate winds, temperatures, and other desired variables. Each day the model was run several times using different combinations of these parameters and later compared with observed meteorological conditions. Parameters that produced the most accurate forecasts were preferentially reused to create the forecasts for the next day. The process was tested for the summer of 2020 and exhibited lower errors than forecasts produced by the model using default values of the parameters.

54 ENVIRONMENTAL SCIENCES↗