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DOE OSTI2020

Medium Energy Electron Flux in Earth's Outer Radiation Belt (MERLIN): A Machine Learning Model

The radiation belts of the Earth, filled with energetic electrons, comprise complex and dynamic systems that pose a significant threat to satellite operation. While various models of electron flux both for low and relativistic energies have been developed, the behavior of medium energy (120–600 keV) electrons, especially in the MEO region, remains poorly quantified. At these energies, electrons are driven by both convective and diffusive transport, and their prediction usually requires sophisticated 4D modeling codes. In this paper, we present an alternative approach using the Light Gradient Boosting (LightGBM) machine learning algorithm. The Medium Energy electRon fLux In Earth's outer radiatioN belt (MERLIN) model takes as input the satellite position, a combination of geomagnetic indices and solar wind parameters including the time history of velocity, and does not use persistence. MERLIN is trained on >15 years of the GPS electron flux data and tested on more than 1.5 years of measurements. Tenfold cross validation yields that the model predicts the MEO radiation environment well, both in terms of dynamics and amplitudes o f flux. Evaluation on the test set shows high correlation between the predicted and observed electron flux (0.8) and low values of absolute error. The MERLIN model can have wide space weather applications, providing information for the scientific community in the form of radiation belts reconstructions, as well as industry for satellite mission design, nowcast of the MEO environment, and surface charging analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

REopt Lite User Manual

REopt Lite evaluates the economic viability of grid-connected solar photovoltaics, wind, combined heat and power, and electric and thermal storage at commercial and small industrial sites. It allows building owners to identify the system sizes and dispatch strategies that minimize the site’s life cycle cost of energy. REopt Lite also estimates the amount of time on-site generation and storage can sustain the site's critical load during a grid outage and allows the user the choice of optimizing for energy resilience. It is primarily used to inform project development decisions and to support research on the factors that drive project feasibility for market development and policy analysis. It is available through a web interface, application programing interface, and open-source code. This user manual provides an overview of the model, including its capabilities and typical applications; inputs and outputs; economic calculations; technology descriptions; and model parameters, variables, and equations. The model is highly flexible and is continually evolving to meet the needs of each analysis. Therefore, this report is not an exhaustive description of all capabilities, but rather a summary of the core components of the model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

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

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

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Vehicle-to-Grid Electric School Bus Commercialization Project

The Vehicle-to-Grid Electric School Bus Commercialization Project was chartered to advance the idea that the batteries in electric vehicles can play a valuable role in supporting the electric grid. As deployment of wind and solar generating resources accelerates to provide an ever-greater share of the nation’s electricity, concurrent investment in solutions that can offset their inherent intermittency will be necessary. Many types of energy storage systems have been proposed, and more than one type will find an economic fit in the grid of the future. Electric vehicle batteries have the potential to provide grid support services in an advantaged manner. The project’s method of exploring this proposition called for development and demonstration of a fleet of vehicle-to-grid (V2G) electric school buses. School buses were chosen because their energy storage capacity is large relative light-duty vehicles; they are typically domiciled in fleet settings; and the number of hours per year they are available for grid support services is high on an absolute basis (generally 80-85% of the hours in a year) and relative to other categories of medium- and heavy-duty vehicles.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Resilient Energy Transition Planning for Ouzinkie, Alaska

This report documents an energy system planning study for the village of Ouzinkie, Alaska, conducted by the U.S. Department of Energy's (DOE) Energy Transitions Initiative Partnership Project (ETIPP). Ouzinkie is a small remote community located on Spruce Island, Alaska, in the Kodiak Archipelago. The Ouzinkie community is served by a local electrical system powered by a combination of diesel generators and a hydroelectric turbine. Due to aging assets, however, the power system reliability has declined in recent years, while the cost of operating the diesel generators has increased significantly. To address these problems, Ouzinkie asked ETIPP to provide technical assistance to develop an updated integrated plan for improvements to the Ouzinkie power system, in order to transition to a more reliable and resilient system powered by renewable energy resources.

13 HYDRO ENERGY↗

DOE OSTI2024

Offshore Wind Turbine Blade (85 to120meters ultra-long blade) static and fatigue test

Offshore blades are not just longer, they are wider, heavier and more flexible. These longer blades are a key component of larger wind turbines and for turbines to be more efficient in low wind speeds. These longer blades help reduce the LCOE further and make offshore wind even more competitive. As described earlier, it is essential for the blades to be fully tested to verify and validate the blade designs and manufacturing processes to ensure a reliable product is installed in the field. Through this project WTTC developed and procured new testing equipment required to test longer blades with larger deflections and higher loads. R&D’s BCDA system commissioned was the largest fatigue test exciter system in the world and set the bar for other blade testing facilities worldwide.

17 WIND ENERGY↗

DOE OSTI2023

The NASA Floater: 15MW Ultra-Light Concrete Hull with Sea-Water Ballast Tuned Mass Damper

In this project, UMaine developed the VolturnUS+ platform; a new 15MW+ ultra-light-weight, corrosion-resistant, concrete floating offshore wind turbine (FOWT) equipped with novel patent pending Heel Tank damping technology. UMaine developed this damping technology to reduce FOWT motions using existing onboard sea-water ballast, which has been integrated into the concrete cruciform hull resulting in reduced platform rigid body motions leading to a lighter hull, increased turbine performance, and a lower LCOE.

17 WIND ENERGY↗

DOE OSTI2021

Preparation of Smart Materials by Additive Manufacturing Technologies: A Review

Over the last few decades, advanced manufacturing and additive printing technologies have made incredible inroads into the fields of engineering, transportation, and healthcare. Among additive manufacturing technologies, 3D printing is gradually emerging as a powerful technique owing to a combination of attractive features, such as fast prototyping, fabrication of complex designs/structures, minimization of waste generation, and easy mass customization. Of late, 4D printing has also been initiated, which is the sophisticated version of the 3D printing. It has an extra advantageous feature: retaining shape memory and being able to provide instructions to the printed parts on how to move or adapt under some environmental conditions, such as, water, wind, light, temperature, or other environmental stimuli. This advanced printing utilizes the response of smart manufactured materials, which offer the capability of changing shapes postproduction over application of any forms of energy. The potential application of 4D printing in the biomedical field is huge. Here, the technology could be applied to tissue engineering, medicine, and configuration of smart biomedical devices. Various characteristics of next generation additive printings, namely 3D and 4D printings, and their use in enhancing the manufacturing domain, their development, and some of the applications have been discussed. Special materials with piezoelectric properties and shape-changing characteristics have also been discussed in comparison with conventional material options for additive printing.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Benchmarking Near-Surface Winds in the HRRR Analyses Using Multisource Observations over Complex Terrain in the Southeastern United States

Wind energy plays a crucial role in sustainable power generation, yet its full potential in the southeast United States (SEUS) remains underexplored. This study advances wind resource assessment in the SEUS using existing regional modeling and multisource observations. We find that terrain complexity, influenced by orography and forest canopy, significantly impacts the accuracy of modeled wind speed. While the High-Resolution Rapid Refresh (HRRR) model effectively simulates wind profiles over flat, nonforested terrain, larger errors are produced above forest canopies, and particularly for those stands in hilly and mountainous terrain where there are no observations aloft that could be used by HRRR’s data assimilation software. Seasonal variations, e.g., changes in the leaf area index, further complicate the relationship between terrain complexity and simulation errors. Here, our findings emphasize the critical need for comprehensive wind profile measurements, extending from below the canopy to height above the canopy and through the lower planetary boundary layer, to fully quantify model performance over and near forests, and for improving wind resource assessment, planning, and management. This study provides valuable insights not only for further model development but also for future field campaign deployment with the goal of further improving our understanding of wind resources in the region.

Complex terrain↗

DOE OSTI2020

Validation of RU-WRF, the Custom Atmospheric Mesoscale Model of the Rutgers Center for Ocean Observing Leadership

The Rutgers University Center for Ocean Observing Leadership (RU-COOL) contracted the National Renewable Energy Laboratory (NREL) to evaluate RU-COOL's atmospheric observation and modeling capabilities for characterizing the New Jersey offshore wind resource. The observational network used by RU-COOL consists of mostly public but some private coastal and offshore buoy-based stations. The core wind resource modeling capability of RU-COOL is a custom setup of the Weather Research and Forecasting (WRF) mesoscale model, referred to in this report as RU-WRF. The most unique feature of RU-WRF and not found in other WRF model setups is the use of custom sea surface temperature (SST) product generated by RU-COOL. This custom product was designed to better capture the unique coastal upwelling and strong storm mixing in the Mid-Atlantic Bight, which other typical SST products are not designed to capture. Funding for the development, maintenance, and use of RU-WRF by RU-COOL is provided by the New Jersey Board of Public Utilities, who also funded the validation work presented in this report. In this validation study, NREL was specifically tasked to: 1) Assess the observational network used by RU-COOL to validate RU-WRF and make recommendations for improvement, 2) Assess methods used by RU-COOL to validate RU-WRF and make recommendations for improvement, 3) Examine the inputs to and setup within RU-WRF, compare against available NREL data sets, and make recommendations for improvement.

17 WIND ENERGY↗

DOE OSTI2025

Short-Term Energy and Meteorological Impacts on Thanksgiving CO2 in Salt Lake City

Abstract Long-term, high-frequency atmospheric CO2 measurements at multiple sites in the Salt Lake City (SLC), Utah, reveal that annual and monthly CO2 variability aligns with a priori estimates of emissions from anthropogenic and biological sources. In this study, we investigate whether short-term fluctuations in anthropogenic emissions, as captured in the Vulcan3 dataset for the United States, can be detected in atmospheric CO2 observations. Specifically, we focus on Thanksgiving holidays, when traffic and energy usage patterns differ from the rest of November. Onroad CO2 emissions exhibit a double peak during weekday morning and evening rush hours but remain relatively low on weekends and Thanksgiving. Interestingly, CO2 mole fractions during Thanksgiving were higher than the rest of November at all SLC monitoring sites, particularly from 2008 to 2013. This increase is partially attributed to elevated energy-related emissions — especially residential sources — and meteorological factors such as weak wind speeds, cold temperature, and a low planetary boundary layer height (PBLH). While CO₂ emissions and mole fraction patterns align over time, notable spatial differences exist. For instance, the near-highway site in Murray shows the highest CO₂ mole fractions despite low local emissions, suggesting pollution transport via highways and wind advection. Random Forest model-based SHapley Additive exPlanations (SHAP) analysis reveals that onroad emissions dominate CO2 contributions on weekdays and weekends, while energy-related emissions play a larger role during Thanksgiving, alongside meteorological drivers such as wind speed and PBLH. Across six urban cities, CO2 emissions display a consistent pattern: residential and commercial (onroad) emissions peak during Thanksgiving (weekday) with substantial (minimal) year-to-year variability. These findings highlight that urban CO₂ variability is driven by the combined influence of emissions and meteorology, underscoring the need for integrated mitigation strategies. Additionally, multi-site measurements are essential for accurate source attribution and the development of effective policy interventions. 

Ryoo, Ju-Mee (ORCID:0000000234256296)↗

DOE OSTI2021

Planar Transformer With Asymmetric Integrated Leakage Inductance Using Horizontal Air Gap

This article presents a novel planar-based transformer winding and core structure with controllable leakage inductance generation for integrated magnetics applications. As a result of limitations in integrated magnetics from the literature, a new approach is proposed utilizing semi-interleaved windings and controllable leakage via a leakage flux core leg featuring a horizontal air gap. Here, the proposed transformer design is analyzed via detailed reluctance modeling to determine closed-form equations for the magnetizing and asymmetrically distributed leakage inductances. Next, a genetic-algorithm-based multiobjective design optimization problem is developed, seeking to minimize the core and winding losses of the proposed transformer subject to a set of parametric and geometric constraints in a dc-ac dual-active-bridge topology for microinverter applications. The optimization was extended to include other integrated magnetic structures from the literature, where it is determined that the proposed transformer is superior from the perspectives of efficiency, footprint area, and parasitic capacitance. Based on the results of the optimization analysis, two designs with theoretical transformer California Energy Commission (CEC) efficiency drops (i.e., CEC efficiency reduction specifically due to the transformer loss mechanisms) of 1.19% and 0.83% were fabricated and evaluated for electrical and thermal performance in the proposed 40 V, 400 W microinverter.

42 ENGINEERING↗

DOE OSTI2024

Low-Flow Marine Hydrokinetic Turbine for Small Autonomous Unmanned Mobile Recharge Stations

A prototype low-flow marine current turbine for deployment from a small unmanned mobile floating platform has been developed for autonomously seeking and harnessing tidal/coastal currents. The support platform is an unmanned surface vehicle (USV), in the form of a catamaran with two electric outboard motors and with capabilities for autonomous navigation. The USV utilized is a WAM-V 16 vehicle that has been developed separately with support from the Office of Naval Research (ONR) [1]. The marine current turbine is based on a freestream waterwheel (FSWW), also known as an undershot waterwheel (FSWW), mounted on the stern of the USV. The concept of operation involves the USV autonomously navigating to a designated marine current resource. Upon arrival, the USV anchors itself, aligns with the current, and deploys the FSWW turbine using a custom cable-lift mechanism. The turbine harnesses the local current, and an onboard power-take-off (PTO) device converts the mechanical energy into electricity, which is stored in an onboard battery bank. When energy harvesting is completed, the turbine and the anchor are retrieved and the USV navigates to a selected location. These unmanned at-sea platforms can provide power to other unmanned maritime systems. Specifically, in this project, the power generated onboard can be used to charge aerial drones via a custom flight deck that has been developed for the USV. The recharging capabilities offered by a fleet of such strategically placed recharging stations can significantly benefit aerial drones operating in the maritime domain by eliminating the need to travel back and forth to land or ship based charging stations. The project has resulted in the development of subcomponents, including the FSWW turbine, a novel PTO, an automated anchoring system for the USV, an automated turbine deployment system, and a flight deck with capabilities onboard the USV for landing, direct-contact charging and takeoff of aerial drones. The design and development of these subsystems have culminated in the overall prototype marine hydrokinetic platform (MHK Platform, Fig. 1). Comprehensive lab and field testing have been conducted to validate the functionality and performance of the platform and its components. The project demonstrates the potential for autonomous, unmanned systems to harness renewable energy from marine currents, and provide sustainable power solutions for maritime applications such as coastal surveillance and environmental monitoring; shoreline mapping; search and rescue; oceanographic research; inspection and maintenance of offshore energy installations like wind turbines and oil rigs; oil spill response; maritime disaster response; and aerial surveys, as well as facilitation of data transfer drones and shore stations.

16 TIDAL AND WAVE POWER↗

DOE OSTI2022

Advances in Energy Hybridization for Resilient Supply: A Sustainable Approach to the Growing World Demand

Energy poverty, defined as a lack of access to reliable electricity and reliance on traditional biomass resources for cooking, affects over a billion people daily. The World Health Organization estimates that household air pollution from inefficient stoves causes more premature deaths than malaria, tuberculosis, and HIV/AIDS. Increasing demand for energy has led to dramatic increases in emissions. The need for reliable electricity and limiting emissions drives research on Resilient Hybrid Energy Systems (RHESs), which provide cleaner energy through combining wind, solar, and biomass energy with traditional fossil energy, increasing production efficiency and reliability and reducing generating costs and emissions. Microgrids have been shown as an efficient means of implementing RHESs, with some focused mainly on reducing the environmental impact of electric power generation. The technical challenges of designing, implementing, and applying microgrids involve conducting a cradle-to-grave Life Cycle Analysis (LCA) to evaluate these systems’ environmental and economic performance under diverse operating conditions to evaluate resiliency. A sample RHES was developed and used to demonstrate the implementation in rural applications, where the system can provide reliable electricity for heating, cooling, lighting, and pumping clean water. The model and findings can be utilized by other regions around the globe facing similar challenges.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Optimum Operation of Microgrid Systems that Employ PV Solar and Battery Systems

On a global scale, over 1.3 billion lack access to electricity (85% in rural areas), and approximately 2.8 billion people rely on traditional biomass for cooking. The World Health Organization estimates that household air pollution from inefficient stoves causes more premature deaths than malaria, tuberculosis, and HIV/AIDS. Increasing demand for energy has led to dramatic increases in emissions. The need for reliable electricity and limiting emissions drives research on Resilient Hybrid Energy Systems (RHESs), which provide cleaner energy by combining wind, solar, and biomass energy with traditional fossil energy, increasing production efficiency and reliability and reducing generating costs and emissions. Microgrids have been shown as an efficient means of implementing RHESs, with some focused mainly on reducing the environmental impact of electric power generation. The technical challenges of designing, implementing, and applying microgrids involve conducting a cradle-to-grave Life Cycle Analysis (LCA) to evaluate these systems’ environmental and economic performance under diverse operating conditions to evaluate resiliency. A sample RHES was developed and used to demonstrate the implementation in rural applications, where the system can provide reliable electricity for heating, cooling, lighting, and pumping clean water. The model and findings can be utilized by other regions around the globe facing similar challenges.

Nagapurkar, Prashant↗

DOE OSTI2026

SCRES Energy Quest Workshop (Technical Report)

Energy Quest: Sitka’s Path to 2050 is a game based public engagement tool developed as part of the Sitka Community Renewable Energy Strategy and the U.S. Department of Energy’s Energy Transitions Initiative Partnership Project Cohort 3. Designed for Sitka’s isolated island microgrid, which is powered primarily by hydropower and depends on imported diesel for backup, the game translated complex long term energy planning questions into an interactive format. In facilitated workshops, residents built energy roadmaps to 2050, explored tradeoffs, and expressed priorities around four themes: affordability, reliability, self sufficiency, and innovation. Across sessions, participants showed strong support for increasing local self sufficiency and resilience, even when this required balancing near term affordability with long term investments. They emphasized reducing dependence on imported diesel, making better use of existing hydropower, and considering new renewable generation such as solar, wind, and additional hydropower. Survey and game responses also highlighted interest in using surplus hydropower to support new industries, expanding electrification of heating and transportation, and exploring emerging technologies and green fuels. The report organizes these findings into four scenario themes to guide Sitka’s 2050 energy planning. Affordability focuses on managing rate impacts, efficiency, and conservation. Reliability addresses diversified generation, backup power, and energy security. Self sufficiency emphasizes distributed generation and reduced reliance on imported fuels. Innovation explores new technologies, marine based energy solutions, and low carbon fuels. By grounding future planning in these community derived themes, Energy Quest shows how a game based approach can make technical energy planning more accessible and inclusive for remote communities. For questions about the game board and piece production email Dr. Sarah Troise (sarah.troise@pnnl.gov)

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

High-Power and Flexible Low-Frequency AC Transmission for Renewable Integration

This project develops a steady-state, dynamic, and production cost models of a multi-terminal, high-power, flexible low-frequency ac (LF-HVac) transmission system with grid-forming converters. Through both numerical analysis and EMTP simulation, the project goal is to demonstrate the feasibility of such an innovative and transformative LF-HVac system to support bulk integration of large-scale, cheap, and steady renewable resources from remote locations such as offshore wind farms to meet recent clean energy goals from DOE. The proposed adoption of low-frequency ac transmission aims to improve power transfer capability for remote large-scale renewable integration. In addition, the control for power electronics converters provides grid-support functions to improve the flexibility and resilience the existing 60-Hz HVac system. Future projects on this topic can be supported by both Energy Efficiency and Renewable Energy (DOEEE) and Office of Electricity Delivery & Energy Reliability (DOEOE) offices.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Integrated CO 2 -facilitated Hydrometallurgical and Electrochemical Technology for Sustainable Mining and Recovery of Critical Elements from Wastes and Ashes

The availability of critical materials and other metals is very important for our national security and economic growth since they are widely used in defense and energy applications including batteries and wind turbines. Unfortunately, high grade ores have become scarce and their productions is dominated by limited countries. Thus, there is a strong need to obtain these materials from domestic sources. Municipal wastes are great candidates since they often contain high concentrations of metals. Since the metals in wastes and waste ashes are not in the form found in natural ores and contain a wide range of impurities, conventional extraction processes would not be effective. Thus, our project has developed an innovative MIDAS process based on the integrated CO2-facilitated hydrometallurgical and electrochemical technology that can effectively recover critical materials and metals from waste ashes while minimizing the environmental impacts. We have (i) characterized waste ashes to understand their physico-chemical properties, (ii) developed green solvent systems for hydrometallurgical extraction of critical elements and metals from waste ashes, (iii) explored electrochemical interfaces to refine the extracted metals.

54 ENVIRONMENTAL SCIENCES↗