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DOE OSTI2024

A Data-driven approach to Core Power distribution reconstruction in a Nuclear Reactor

This report presents the initial development of a data-driven approach for reconstructing the core power distribution in a nuclear reactor (power shape synthesis) using ex-core sensors. Traditional techniques rely on deploying a large number of detectors throughout the reactor core. However, this approach is not feasible for innovative reactor concepts like Advanced Reactors and Microreactors. First, the tight lattice pitch, designed to maximize power density, limits the space available for sensors. Secondly, the harsh operating conditions are not compatible with commercially available detectors. The method proposed in this work integrates high-fidelity modeling with data-driven techniques to accurately reconstruct power distribution across various reactor types, thereby reducing the reliance on in-core sensors. Purdue University Reactor One (PUR-1) was selected as the test case. The CAD model representing the latest configuration of the PUR-1 core was imported into the OpenMC simulation framework, and the model was built. Additionally, the previously developed MCNP6 model was updated. The two models were assessed against the data collected during an experimental campaign conducted in July 2024. Thirty gold foils were placed in three Irradiation Assemblies in PUR-1 core. Using the measured activity of the irradiated foils, the neutron flux at different core locations was estimated.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Load Disaggregation (Modeling Individual Appliance Power Generation & Consumption in Real-Time)

We developed a machine learning-based load disaggregation method to estimate the real-time output of individual appliances from the whole-house measurements. We first learn the important features associated with each type of appliances using the ground truth consumption data of individual appliances potentially available for a small set of houses equipped with submeters. The learned features are then be used to estimate the power generation/consumption of the appliances from the whole-house consumption. This developed load disaggregation software includes two steps. The first step is to identify the on/off status of different appliances using a classification method, and the second step is to estimate the appliance output using a regression method.

Hao, Jun↗

DOE OSTI2025

A knowledge-informed large language model framework for U.S. nuclear power plant shutdown initiating event classification for probabilistic risk assessment

Identifying and classifying shutdown initiating events (SDIEs) is critical for developing shutdown probabilistic risk assessment for nuclear power plants. Existing computational approaches cannot achieve satisfactory performance due to the challenges of unavailable large, labeled datasets, imbalanced event types, and label noise. To address these challenges, we propose a hybrid pipeline that integrates a knowledge-informed machine learning model to prescreen non-SDIEs and a large language model (LLM) to classify SDIEs into four types. In the prescreening stage, we proposed a set of 44 SDIE text patterns that consist of the most salient keywords and phrases from six SDIE types. Text vectorization based on the SDIE patterns generates feature vectors that are highly separable by using a simple binary classifier. The second stage builds Bidirectional Encoder Representations from Transformers (BERT)-based LLM, which learns generic English language representations from self-supervised pretraining on a large dataset and adapts to SDIE classification by fine-tuning it on an SDIE dataset. The proposed approaches are evaluated on a dataset with 10,928 events using precision, recall ratio, F 1 score, and average accuracy. In conclusion, the results demonstrate that the prescreening stage can exclude more than 97% non-SDIEs, and the LLM achieves an average accuracy of 95.1% for SDIE classification.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Spark-Assisted HCCI Residential CHP

A transformative small spark ignition (SI) internal combustion (IC) engine fueled with natural gas was developed for combined heat and power (CHP) applications using a combination of cycle simulations, computational fluid dynamics (CFD) modeling, and engine experiments. The resulting 1 kW CHP engine was demonstrated to achieve 36.1% brake thermal efficiency (BTE) while meeting aggressive exhaust emissions targets using a low-cost three-way catalyst. Starting from a “clean-sheet” design, modeling tools were used to select the optimal engine parameters and operating characteristics. The disruptive technologies developed for the CHP system have a target lifetime of at least 10 years. The engine cost at volume of 10,000 units was estimated to be $\$$1,050. A combination of experimental and simulation results were used to identify a path to the program target of 38.6% BTE. Base engine design parameters (i.e., displacement, speed, bore, stroke, valve timings, and compression ratio) were optimized to reduce friction, heat transfer, and exhaust losses. The base clean sheet prototype engine achieved 32% BTE. Optimization of the lube oil and coolant temperatures added 1.8% BTE. The addition of exhaust gas recirculation added 1.1% BTE. Novel thermal barrier coatings (TBCs) developed over the course of the project added 1.2% BTE. Further improvements in engine friction reduction (1.3% BTE) and improved combustion (1.2% BTE) are estimated to meet the program target 38.6% BTE, while also meeting the stringent criteria pollutant emissions targets.

42 ENGINEERING↗

DOE OSTI2022

Grid-Forming Wind Power

This presentation is a summary of research conducted by NREL team in the area of developing and testing grid forming controls by wind power.

grid forming↗

DOE OSTI2020

Electrification Futures Study Flexible Load Profiles

This data set includes hourly profiles for flexible load developed for the Electrification Futures Study (EFS). The load profiles represent projected end-use electricity demand that is assumed to be flexible (i.e., can be shifted throughout a day) for various scenarios of flexibility (Base, Enhanced), electrification (Reference, Medium, High), and technology advancement (Slow, Moderate, Rapid), and were developed as inputs into the ReEDS model. The quantity of flexible load is estimated using assumptions on the level of flexibility and customer participation within each subsector modeled in the EFS. Detailed assumptions and modeling implementation will be documented in ongoing EFS analyses. Flexible load profiles are provided for a subset of years (2018, 2020, 2024, 2030, 2040, 2050) and are aggregated to the state and sector level. Total electricity load profiles can be found in a related EFS data set (https://dx.doi.org/10.7799/1593122). NOTE: Due to the file size, Mac users may experience issues decompressing the zip files using the Mac Archive Utility. In those cases, decompressing using the command line is recommended. - Mai, Trieu, Paige Jadun, Jeffrey Logan, Colin McMillan, Matteo Muratori, Daniel Steinberg, Laura Vimmerstedt, Ryan Jones, Benjamin Haley, and Brent Nelson. 2018. Electrification Futures Study: Scenarios of Electric Technology Adoption and Power Consumption for the United States. National Renewable Energy Laboratory. NREL/TP-6A20-71500. https://doi.org/10.2172/1459351. - Murphy, Caitlin, Trieu Mai, Yinong Sun, Paige Jadun, Matteo Muratori, Brent Nelson, Ryan Jones. Forthcoming. Electrification Futures Study: Scenarios of Power System Evolution and Infrastructure Development for the United States. National Renewable Energy Laboratory. - Sun, Yinong, Paige Jadun, Brent Nelson, Matteo Muratori, Caitlin Murphy, Jeffrey Logan, and Trieu Mai. Forthcoming. Electrification Futures Study: Methodological Approaches for Assessing Long-Term Power System Impacts of End-Use Electrification. National Renewable Energy Laboratory.

buildings↗

DOE OSTI2024

Communication Network Layer State Estimation Measurement Model for a Cyber-Secure Smart Grid

Network communication has been proven to be a very important tool and a key factor in the recent development and progress of the power grid operation. It is also considered as the foundation for the smart grid because information and communication are integrated into electricity distribution to achieve reliable and accurate knowledge of the power grid. In previous years, absorbing energy from substations and delivering it to customers was the only type of interaction we knew between utility companies and customers. Presently, the growing connections of small distributed generation units caused by the cost reduction of most of the technologies used in generation and storage of electrical energy, along with the potential benefits of renewable energy have pushed many researchers to look into the improvement of information and communication technologies (ICT) in order to ensure a bidirectional flow of power and data. Moreover, the evolution of information and communication technologies and its applications to smart grid have converted the smart grid into a cyber-physical system where vulnerabilities and additional security challenges such as cyber-threats and cyber-attacks have emerged. Previously, we have demonstrated that using machine learning-based processing on data gathered from communication networks and the power grid was a promising solution for detecting cyber threats by implementing a co-simulation of cyber-security for cross-layer strategy. Since the majority of the challenges observed can only be solved in the network communication layer, we present in this work a physics-based state estimation model of the communication network system towards enhanced cyber-physical security of the smart grid. Information integration with the previously developed machine learning model is developed, providing a enhanced cyber-physical security application for the smart grid. Easy-to-implement model, without hard-to-derive parameters, highlight potential aspects of the model for real-life applications.

Mathieu, Reynold↗

DOE OSTI2022

Economic Impact of Permitting Timelines on Geothermal Power in California, Nevada, and Utah

The United States has great geothermal power potential; however, only a small fraction of this resource has been utilized for power generation. Various barriers, including technical, financial, and regulatory permit delays, are attributed to the lower penetration of geothermal energy into the national grid. Unpredictable environmental reviews and permitting timelines are some of the non-technical barriers that can cause delays in geothermal exploration and utilization plans. This document provides an assessment of the potential economic impact of permitting costs and timelines on geothermal power in California, Nevada, and Utah. Development of geothermal resources requires multi-layered regulatory permitting by local, state, and federal agencies. In this study, we collected and reviewed permit timelines and associated cost data for several existing geothermal power plants as well as for geothermal projects currently undergoing permitting processes for exploration and development activities in California, Nevada, and Utah. We interviewed several geothermal developers and staff from multiple permitting agencies to obtain insight from both sides (i.e., people applying for permits and people processing those applications for California Environmental Quality Act [CEQA] and National Environmental Policy Act [NEPA] reviews and other regulatory compliance). The intent of this project was also to identify informative pathways for the geothermal stakeholder community by which the permitting process could be streamlined.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

Non-contact Thermophysical Characterization of Solids and Fluids for Gen3 Concentrating Solar Power

In this project, we aim to develop Modulation Photothermal Radiometry (MPR), which is an attractive non-contact tool to evaluate thermophysical properties of high-temperature solids and HTFs that are otherwise time-consuming and difficult to measure and for in-situ testing of these properties. Therefore, the main objective of the project is the development and application of MPR to characterize high temperature thermophysical properties of heat transfer fluids (HTFs) and the solids (tubing and solar absorbing coating) in various components and sub-systems used in CSP plants. The measurements will be first demonstrated on a wide range of materials at UCSD and then the tool will be transferred to other facilities within the Gen3 CSP portfolio.

14 SOLAR ENERGY↗

DOE OSTI2022

AN UPDATE ON THE STATUS OF A REDUCED FLOW TEST OF A 10MW 700⁰C SCO2 INTEGRALLY GEARED COMPANDER

In order to maintain viability as a future power-generating technology, concentrating solar power (CSP) must reduce its levelized cost of electricity (LCOE). One component of solving this problem is reducing the cost of the power block while simultaneously increasing the efficiency of the thermodynamic cycle. One disruptive technology that has the promise to accomplish this is supercritical CO2 based power cycles. These cycles are conceptually similar to steam cycles; however, they have substantially smaller turbomachinery at equivalent power while also delivering more efficiency at turbine inlet temperatures of 500-700℃. This paper will summarize the current status of a US Department of Energy project to develop machinery to support a 10 MW sCO2 power cycle. The team of Southwest Research Institute® (SwRI®) and Hanwha Power Systems America, proposed to develop an integrally-geared (IG) compressor-expander (compander) for use in a nominal 10 MW-scale CSP supercritical carbon dioxide (sCO2) plant application. This integrally-geared compander (IGC) comprises multiple pinion shafts interconnected on a single bull gear to create a compact package, and utilizes a low-cost, low-speed driver. In addition, the integrally-geared architecture allows each pinion to operate at different rotational speeds to optimize performance and easily allow for inter-stage cooling and turbine re-heat to further enhance both stage and cycle efficiency. The close integration of all turbomachinery elements into a single integrally-geared (IG) machine creates a design that lends itself to power block modularization, which makes it suitable for waste heat recovery, fossil fuel power plants, and especially CSP applications.

14 SOLAR ENERGY↗

DOE OSTI2022

A High Power Prototype of a Harmonic Kicker Cavity

A harmonic kicker, a beam exchange device that can deflect the beam at an ultra-fast time scale (a few ns), has been developed in Jefferson Lab *, **. The high power prototype that can deliver more than a 100 kV kick at 7 kW was fabricated. The RF performance of cavity such as the harmonic resonant frequencies, kick profiles, it’s stability, and electric center is tested at bench. The cavity will eventually be tested with a beam at Upgraded Injector Test Facility (UITF) in Jefferson Lab. In this paper, we report some features of fabrication and bench test results. We also briefly describe our beam test plan in the future.

Park, Gunn↗

DOE OSTI2025

High Speed Medium Voltage CHP System with Advanced Grid Support

The project was a collaboration between Clemson University and TECO Westinghouse Motor Company. The goal of the project was to develop a medium voltage commercial grid-tied system with advanced grid support functions. Current state-of-the-art in medium voltage, multi-megawatt power electronic systems do not support advanced grid functions, traditionally due to power electronic limitations and required applications. The developed system is capable of interacting with the power system at the distribution level to efficiently integrate gas turbine generation systems or any other ac generation system with up to 20MWe of power production capacity. This project demonstrated a high level of technical readiness of the 1MW, 500Hz, 15000 RPM high frequency Combined Heat and Power (CHP) generator and electric machine system, utilizing advanced grid support functions required by IEEE Std. 1547-2018.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Development of an Integrated Electro-Hydraulic Machine to Electrify Off-highway Vehicles

Electrification of off-highway vehicles is notoriously challenging due to extreme power density requirements. This paper proposes and develops an axial flux machine integrated with a hydraulic pump to realize a single modular, electro-hydraulic machine to electrify off-highway vehicle implements. This integrated machine eliminates redundant bearings, couplings, and shaft seals, re-uses surfaces, and enables direct cooling of the electric machine with the hydraulic fluid, to significantly increase power density. Three popular axial flux machine variants are first compared using an FEA-based design optimization approach. The single rotor, single stator variant is identified to be the most promising for integration with the hydraulic pump. Next, a multi-physics framework of the complete integrated hydraulic pump and axial flux machine is developed to characterize the design space. The results indicate promising potential for this concept to realize efficiency over 85% and power density over 5kW/kg for the complete machine (electric machine, hydraulic pump, and thermal management system), while utilizing conventional materials (thin gauge silicon steel, N45 magnets, and enamelled copper wire). Furthermore, a prototype axial flux machine has been experimentally characterized and integrated with a hydraulic pump to demonstrate the integrated electro-hydraulic machine concept.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Exploring the Grid Value of Offshore Wind Energy in Oregon

The significant offshore wind energy potential of Oregon faces several challenges, including a power grid which was not developed for the purpose of transmitting energy from the ocean. The grid impacts of the energy resource are considered through the lenses of (i) resource complementarity with Variable Renewable Energy resources; (ii) correlations with load profiles from the four balancing authorities with territory in Oregon; and (iii) spatial value to regional and coastal grids as represented through a production cost model of the Western Interconnection. The capacity implications of the interactions between offshore wind and the historical east-to-west power flows of the region are discussed. The existing system is shown to accommodate more than two gigawatts of offshore wind interconnections with minimal curtailment. Through three gigawatts of interconnection, transmission flows indicate a reduction of coastal and statewide energy imports as well as minimal statewide energy exports.

17 WIND ENERGY↗

DOE OSTI2020

A Review on Artificial Intelligence for Grid Stability Assessment

Artificial intelligence provides a convenient route for power grid stability assessment. Compared with simulation-based approaches, artificial intelligence can potentially save time on model development and numerical computation in stability assessment. This paper first reviewed existing literature on using artificial intelligence for power grid stability assessment. Then a machine-leaning-based tool is presented and developed to assess power grid transient stability, frequency stability, and small signals stability. Test results verified the accuracy and effectiveness of the AI tool for power grid stability assessment.

You, Shutang↗

DOE OSTI2020

A Review on Artificial Intelligence (AI) for Stability Assessment: Preprint

Artificial intelligence provides a convenient route for power grid stability assessment. Compared with simulation-based approaches, artificial intelligence can potentially save time on model development and numerical computation in stability assessment. This paper first reviewed existing literature on using artificial intelligence for power grid stability assessment. Then a machine-leaning-based tool is presented and developed to assess power grid transient stability, frequency stability, and small-signal stability. Test results verified the accuracy and effectiveness of the artificial intelligence tool for power grid stability assessment.

artificial intelligence↗

DOE OSTI2022

Automotive Power Electronics Cooling Technology Research at NREL

This presentation describes power electronics thermal management technologies used for on-road EVs. Examples are provided and heat exchangers are described. Advanced cooling technologies developed are NREL to enable increased power density and enable high WBG temperature operation are then presented. The performance (e.g., thermal resistance, pumping power) of the advanced power electronics cooling technologies are compared to the performance of current, on-road technology.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Power Electronics Cooling Technology Research at NREL

DIRECT ENERGY CONVERSION↗