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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Understanding the Uncertainty in the Technical Performance Level Assessment for Wave Energy

In recent years, the design and development of wave energy converters (WECs) has been explored with intense interest, with highly varying design concepts emerging globally across both research enterprises and industry. The design space for WECs is vast - many concepts ranging in functionality, control systems, power development systems, materials, and scale have been ideated and prototyped, but WEC technology has yet to converge. One critical element of the technology trajectory that governs the speed of adoption is the performance of a WEC concept. In analogous but more-established industries (such as aerospace, and environmentally sustainable electronics design), performance assessment is a quantitative method, based on historical data, that is used as an iterative tool to improve the design of these systems early on in the design process. Though more nascent than these approaches, in wave energy R&D, WEC performance has been assessed using the Technology Performance Level (TPL) assessment, which provides designers with a quantitative score, situating a grid-scale WEC concept on a scale from 1-9 (1 being the lowest performance, and 9 being the highest, trending with the oft-used Technology Readiness Level, or TRL). The TPL assessment is designed to be used during design iteration, when a WEC concept is fully ideated, to enable designers to consider potential means of improving the downstream performance of the concept. One concern that may be slowing the adoption of TPL among WEC developers is the inherent uncertainty in the assessment, and how uncertainty in the individual questions asked as part of the assessment may contribute to perceived inaccuracies in the final score. In this work, we explore the uncertainty present in the assessment and quantify this uncertainty using both traditional mathematical operations and a Monte Carlo simulation. Results imply areas of improvement of the TPL assessment, where reducing uncertainty will be most helpful to end users, enabling both TPL practitioners and users to understand with more accuracy those design elements that can be improved to impact device performance most substantively.

techno-economic analysis↗
DOE OSTI2019

Seminar 13 - Advanced Methods for Grid Integration of High-Performance Residential Communities

High-performance residential communities such as net-zero energy (NZE) and NZE-ready communities are emerging across the United States as many cities and states have committed to achieve ambitious energy efficiency and renewable energy goals between now and 2050. The achievement of these goals will transform the nation's communities into the holistic paradigms consisting of pervasive solar photovoltaics (PVs) and other renewable distributed energy resources, energy storage and flexible loads. However, integrating residential communities with high PV penetration may bring many challenges to the grid. For example, during many hours of the year, electric power is flowing out of PV-enabled homes and back into the grid. When this happens simultaneously in many nearby homes, distribution feeder voltage can be raised significantly. Intermittent solar power can also cause voltage flickers, leading to potential damages on both distribution feeder and home appliances. Existing solutions, such as PV curtailment, battery storage, and direct load control, are not able to address all the challenges in a cost-effective way. Better understanding is needed on how to deploy rooftop PV, how to predict building loads, and how to coordinate the homes in a community to enhance grid reliability. This seminar consists of four integral presentations that cover different aspects of a solution to these challenges. First, we will present an automated method to identify the best surfaces to deploy PV and size PV according to the PV penetration goals in a community. Second, we will present a streamlined way to create gray-box building models that are suitable for large-scale building-grid co-simulation. Next, we will present a data-driven method to estimate the end-use energy consumption to better coordinate the behind-the-meter resources to reduce utility cost, provide grid services, and improve renewable energy integration. Lastly, we will present a hierarchical control system that integrates the building models and the estimated non-dispatchable loads into the decision-making process to enhance the reliability and resilience of the residential community. Simulation results from an NZE-ready community in Fort Collins, Colorado will be presented in all four presentations and the guidelines on better grid integration of residential communities will be provided.

14 SOLAR ENERGY↗
DOE OSTI2024

IBR Digital Supply Chain Gap Analysis and Recommendations

The adoption of clean energy technologies, including solar photovoltaics, continues to introduce non-traditional stakeholders to the operations and planning of the electric system. Stakeholders such as manufacturers, vendors, owners, aggregators, and others are enabling the adoption, integration, and optimum operations of solar technologies at accelerated rates. Inverters form the foundation of many digitally controlled energy sources for clean energy technologies, including Solar, Battery Energy Storage Systems, Hybrid Systems, and Hydrogen Fuel Cells. Their supply chain is complex, a series of microchips, electronic switches and other components making up its primary functions. The complexity of this space and the growing digitization associated with these components can create supply chain cyber risks. One measure to mitigate cybersecurity attacks is proper digital supply chain security. The U.S. Department of Energy (DOE) Solar Energy Technologies Office (SETO), in partnership with the Cybersecurity, Energy, Security, and Emergency Response (CESER) office, is hosting a workshop to bring together solar vendors and services providers to discuss digital supply chain security for solar systems and challenges and opportunities in the transitioning to a fully domestic supply chain for solar energy in the U.S. This workshop will support the Securing Solar for the Grid (S2G) and Energy Cyber Sense program activities. During the workshop, industry experts and researchers from DOE National Laboratories will discuss the current solar supply chain landscape and the transition to domestic manufacturing of solar components in the U.S. Tools and techniques to better manage and secure the digital supply chain of solar devices and systems will be discussed.

cybersecurity↗
DOE OSTI2022

Research Trends and Applications of PMUs

This work is a survey of current trends in applications of PMUs. PMUs have the potential to solve major problems in the areas of power system estimation, protection, and stability. A variety of methods are being used for these purposes, including statistical techniques, mathematical transformations, probability, and AI. The results produced by the techniques reviewed in this work are promising, but there is work to be performed in the context of implementation and standardization. As the smart grid initiative continues to advance, the number of intelligent devices monitoring the power grid continues to increase. PMUs are at the center of this initiative, and as a result, each year more PMUs are deployed across the grid. Since their introduction, myriad solutions based on PMU-technology have been suggested. The high sampling rates and synchronized measurements provided by PMUs are expected to drive significant advancements across multiple fields, such as the protection, estimation, and control of the power grid. This work offers a review of contemporary research trends and applications of PMU technology. Most solutions presented in this work were published in the last five years, and techniques showing potential for significant impact are highlighted in greater detail. Being a relatively new technology, there are several issues that must be addressed before PMU-based solutions can be successfully implemented. This survey found that key areas where improvements are needed include the establishment of PMU-observability, data processing algorithms, the handling of heterogeneous sampling rates, and the minimization of the investment in infrastructure for PMU communication. Solutions based on Bayesian estimation, as well as those having a distributed architectures, show great promise. The material presented in this document is tailored to both new researchers entering this field and experienced researchers wishing to become acquainted with emerging trends.

42 ENGINEERING↗
DOE OSTI2021

Transforming Energy through Computational Science: Computing for Clean Energy

This fact sheet discusses the opportunity space for NREL's computational science capabilities to address national clean energy objectives. Achieving a carbon-free power sector by 2035 as a step towards a decarbonized U.S. energy economy in 2050 will require major advances in power generation, autonomous energy systems, transportation, and buildings/communities. Development of integrated modeling approaches for complex energy systems will be essential for deployment. Success requires developments in optimization and control theory, complemented by machine learning (ML) and artificial intelligence (AI), all of which in turn need targeted investments in breadth and scale of computing. This document defines an opportunity space where: embracing computing can link established research and development (R&D) to a decarbonization agenda; pursuing emerging approaches can accelerate the pace of technology advancement across the portfolio; and leading by example could reduce the carbon footprint of computing worldwide.

advanced computing↗
DOE OSTI2020

Modeling and Harmonic Stability of MMC-HVDC With Passive Circulating Current Filters

A modular multilevel converter (MMC) is an emerging converter technology widely used in wind power applications using high-voltage direct current (HVDC) transmission, and it has been largely investigated in medium-voltage solar harvesting as well as electric motor drives. Different from studies dealing with active circulating current control loops, this paper focuses on impedance modeling and harmonic stability studies for MMCs with passive circulating current filters (PCCFs). A power stage circuit including a PCCF is transformed and remodeled to obtain small-signal formulations. This transformation leads to additional high-order matrix computing complexity due to the added impedance subnetwork matrix from the PCCF as well as relevant crossed-frequency impacts. To simplify the computational burden, the proposed model aims to solve one arm equation instead of all six MMC arm equations. To achieve this result, additional challenges occur when the MMC is connected to a renewable energy source instead of the grid voltage, where low-level zero-sequence components might exist in the neutral point of three phases, especially in the case of no integrated advanced modular voltage balancing control, which prevents computational simplification. To overcome this challenge, further impedance matrix adjustments are conducted in this paper to theoretically suppress the impact of zero-sequence harmonics when obtaining small-signal impedance, taking into account the frequency coupling effect. Finally, simulations are carried out to validate the developed impedance model under different operating scenarios. Harmonic stability case studies of MMCs with PCCFs connected to renewable energy current sources are also presented, where frequency-domain stability analyses based on Bode diagrams are compared to time-domain simulation waveforms and FFTs, which validate the effectiveness of the proposed impedance model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2023

PHIL Interface Design for Use With a Voltage-Regulated Amplifier: Preprint

As inverter controls have become increasingly complex, power hardware-in-the-loop (PHIL) has emerged as a leading strategy to thoroughly assess the impact of proprietary inverter controls on a specific power system. The development of a PHIL test bed typically involves the desired inverter, a power amplifier, and a digital real-time simulator (DRTS) to control the simulated power system. As a result of PHIL nonidealities, a form of digital compensation within the DRTS is used, which is commonly referred to as a PHIL interface. The interface design for PHIL test beds has been previously examined in the literature, but many existing methods use older power amplifiers that do not contain internal voltage regulation. These existing interface methods are based around a voltage regulator within the DRTS rather than one preexisting in hardware. In this study, a three-step approach of PHIL interface development for modern power amplifiers with built-in voltage regulation is introduced and validated in hardware with a single 30-kW grid-following inverter.

DRTS↗
DOE OSTI2025

Computational Algorithms for Unit Commitment with AC Power Flows (Final Report)

Security-constrained unit commitment (SCUC) is a key component in power system operations. When AC power flow constraints are considered in the SCUC model (AC-SCUC), the problem becomes extremely difficult due to its discrete and non-convex nature, as described in “Grid Optimization Competition Challenge 3 Problem Formulation (GOCC)”. There are four main challenges: (i) Discrete decisions regarding unit online/offline status and start-up/shut-down procedures for every single unit. The number of discrete decision variables increases considerably when a system integrates multiple generators; (ii) Configuration-based combined-cycle formulations, and multi-commodity models that include ramping products, spin/non-spin products, and regulation up/down products. The combined-cycle units introduce additional discrete decision variables and auxiliary service products further complicate the model by connecting multi-commodity products’ continuous and discrete variables; (iii) SCUC models with AC power flow constraints are far more complex due to massive bilinear terms in the large-scale nonlinear power balance equations. The nonlinear power balance equations are further complicated by the discrete step control variables of shunts; (iv) N − 1 contingency analysis. The size of the model increases linearly with the number of contingencies considered, greatly increasing the size of the optimization model. Accordingly, there is an emergent need to develop a robust algorithm capable of deriving a high-quality solution in a short time and passing through contingency tests simultaneously. In this project, we explore innovative techniques to address this challenging problem by integrating advanced polyhedral theory, approximation methods, relaxation strategies, decomposition techniques, and parallel computing. Each technique approaches the problem from a different perspective, leveraging its specific strengths to tackle distinct challenges. Each individual method has demonstrated its effectiveness in the PI’s previous research. Their integration is expected to significantly reduce the computational time required to solve the proposed complex problem. Successful completion of this project has the potential to transform the industry by enhancing optimization solvers capable of handling large-scale day-ahead energy market clearing models within strict time constraints, while incorporating AC power flow constraints. This advancement will lead to reduced overall generation costs and, consequently, increased social welfare.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Fifth-Generation District Heating and Cooling Substations: Demand Response with Artificial Neural Network-Based Model Predictive Control

District heating and cooling (DHC) is considered one of the most sustainable technologies to meet the heating and cooling demands of buildings in urban areas. The fifth-generation district heating and cooling (5GDHC) concept, often referred to as ambient loops, is a novel solution emerging in Europe and has become a widely discussed topic in current energy system research. 5GDHC systems operate at a temperature close to the ground and include electrically driven heat pumps and associated thermal energy storage in a building-sited energy transfer station (ETS) to satisfy user comfort. This work presents new strategies for improving the operation of these energy transfer stations by means of a model predictive control (MPC) method based on recurrent artificial neural networks. The results show that, under simple time-of-use utility rates, the advanced controller outperforms a rule-based controller for smart charging of the domestic hot water (DHW) thermal energy storage under specific boundary conditions. By exploiting the available thermal energy storage capacity, the MPC controller is capable of shifting up to 14% of the electricity consumption of the ETS from on-peak to off-peak hours. Therefore, the advanced control implemented in 5GDHC networks promotes coupling between the thermal and the electric sector, producing flexibility on the electric grid.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Managing Cyber Supply Chain Risk for Renewable Energy Technologies

On July 1, 2021, the U.S. Department of Energy (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER) hosted a virtual workshop facilitated by the National Renewable Energy Laboratory (NREL). Cybersecurity supply chain experts, researchers, and leaders in government and industry came together to share information on current and future challenges in securing emerging technologies and technical architecture. From a cybersecurity perspective, we need to move from a cybersecurity approach that focuses principally on legacy asset owners to one that incorporates more emphasis on end-point device manufacturers and third-party integrators. Cybersecurity for the global digital supply chain for manufacturers of consumer end-point devices—such as smart solar inverters and smart electric vehicle (EV) chargers—will be critical to the future cyber health of the grid.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Optimal Operation and Impact Assessment of Distributed Wind for Improving Efficiency and Resilience of Rural Electricity Systems

This project aims to empower rural utilities by developing advanced optimization models and algorithms for effectively integrating distributed wind energy alongside battery storage and other distributed energy resources (DERs). The primary objectives are to reduce peak demand, ensure reliable emergency power supply, and regulate voltage and frequency. To address operational challenges, the project introduces innovative mitigation strategies and ultrafast assessment frameworks to evaluate the impacts of distributed wind and DERs on rural grids, offering actionable solutions to potential issues. Economic viability is assessed through cost-benefit analysis using real rural utility data, ensuring the practical application of the project outcomes.

17 WIND ENERGY↗
DOE OSTI2026

Bipolar Membrane Electrodialyzers as Flexible Demand Response Resources: Co-Optimization of Cost Savings and Product Formation

Bipolar membrane electro dialyzers (BPMED) are widely used for chemical production and processing, including in the emerging ocean alkalinity enhancement (OAE) industry. In this paper, we explore the potential of BPMED devices as flexible electrochemical loads within power system operations. Using a multi-objective optimization framework, we evaluate BPMED operation across 24-hour and monthly horizons to examine how dispatch strategies respond to electricity price and grid conditions. Simulation results show that altering the relative weights of the choices in the objective function strongly shape the operating patterns, with cost-focused strategies that suppress the operation during peak prices. Furthermore, we propose alternative formulations that optimize operations to achieve both cost savings and alignment with periods of lower grid-side carbon intensity (CI), as low grid-side CI is key to maximize OAE efficiency. Additionally, a detailed sensitivity analysis highlights the importance of device properties, where low area-specific resistance (ASR) of membrane and high current efficiency (CE) are observed to jointly unlock cost-effective operation. However, even modest shunt efficiency losses are observed to erode performance and decrease system value. Importantly, the analysis demonstrates that BPMED can serve as a controllable and flexible demand response resource, shifting load to support multiple grid-side objectives, including (but not limited to) renewable integration, alleviate peak demand, and provide co-benefits for system reliability. These findings underscore BPMED’s dual role as a process technology and a grid-supporting asset, pointing to promising pathways for operational optimization of multiple objectives.

Bhattacharya, Saptarshi (ORCID:0000000308902060)↗
DOE OSTI2021

A tool for assessing demand side management and operating strategies for isolated microgrids

Globally, power system operators are exploring ways to leverage the capabilities of smart meters to implement fine-grained demand side management (DSM). Here this paper presents a new simulation tool to evaluate operating strategies for smart-meter-enabled (SME) islanded microgrids being advanced for sustainable rural electrification in emerging economies. Based on MATLAB/Simulink, the tool's component-level models of small microgrids can be easily configured. Alternative rule-based operating strategies are implemented with controllable supply and storage components as well as other components driven by external factors (e.g., weather and time of day). To account for the wide range of possible operating conditions in real-world applications, statistical metrics can be evaluated using Monte Carlo (MC) methods based on user-defined, time-dependent probability distributions for demands, supplies, and environmental variables. Features of the tool are demonstrated with case studies for a representative microgrid in rural Rwanda.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Adaptive Protection and Validated Models to Enable Deployment of High Penetrations of Solar PV (PV-MOD)

The availability and validation of various PV models in commercial tools differ, with some models not yet thoroughly validated for advanced inverter functionalities and reliable performance under weak system conditions. Many existing models do not fully incorporate new inverter control functions, which can affect system stability. The increasing deployment of solar PV and other inverter-based resources (IBRs), including distributed energy resources (DERs), is influencing the reliable operation of protection schemes in distribution systems and microgrids. Emerging adaptive protection schemes (APS) offer new opportunities for protecting these systems during varying configurations and DER operating conditions, though their demonstration and validation remain limited. Adaptive protection schemes face similar challenges, as they are typically designed for specific configurations. There is a growing need for tools and methodologies to streamline the deployment of adaptive protection for safe and reliable DER integration. The project main objective was to develop and validate high-fidelity generic models of solar PV facilities for stability, protection, EMT, and QSTS analyses. This objective was achieved, and these models can now be integrated into commercial software tools, enabling utilities, vendors, and developers to study high-penetration PV systems more confidently. The project also demonstrated advanced applications of these models, including the design and deployment of adaptive protection schemes in high-penetration field applications and microgrids, supporting grid safety and reliability. Several milestones were reached by the end of the project. A sophisticated inverter test plan was developed, and inverters representative of the North American marketplace were selected. EPRI and NREL tested various inverters, conforming to IEEE standards. Improvements were made to existing generic models of IBR units, IBR plants, and aggregated feeders for various analyses. The first generic electromagnetic transient (EMT) model for a solar PV plant was developed, conforming to IEEE Std 2800™-2022 and validated against laboratory measurements of a 2.2 MVA large-scale battery energy storage system (BESS) inverter. That model was then used to produce reference responses illustrating examples of validated and verified IBR plant models that pass or fail tests for technical minimum capability and performance as specified in the IEEE standard. The developed, tested, and validated generic models can be used for transmission planning, stability assessments, expansion planning, and evaluating potential future IBR interconnection requirements. They can also support interconnection screens and conformity assessments of IBR plants, including solar PV. The project significantly contributed to the ongoing standardization and model-based representation and verification of IBR responses. The project further addressed challenges of common distribution protection schemes with increasing deployment of DER by developing, validating, and demonstrating adaptive protection schemes (APS) that can improve the reliable and safe integration of DER into distribution systems. New APS were designed using improved DER models for three common distribution systems: a radial feeder, a meshed network, and a microgrid. Modeling and hardware-in-the-loop (HIL) testing of the APS were conducted, successfully showing their effectiveness and selectivity. Proof-of-concept field demonstration was achieved for two APS, i.e., one on a radial feeder and another one in a microgrid. Field demonstration could not be achieved for the APS on a meshed network, primarily due apprehension of one utility partner and also due to limited access to the protective algorithms in the network protectors. Guidelines developed from the lessons learned in the project lay out the general process followed in the design, installation, and commissioning of APS for various distribution systems. Distribution utility partners’ apprehension about field demonstration of the new APS were addressed—with varying success—by taking a stepped risk-management approach of modeling of a wide range of sensitivities first, performing in-depth proof-of-concept testing in the laboratory including HIL next, and finally deliberately implementing and commissioning the actual protection equipment and algorithms into parts of—or in parallel operation to—the three real distribution systems. Future work should include pilot projects that further show the acceptable performance of the developed APS before these schemes be rolled out more widely. Inclusion of both utility and original equipment manufacturers (OEMs) in future projects could increase chances of successful field demonstration. Despite challenges in achieving the field demonstration goal of the project for all three APS, the research significantly contributed to the innovation of adaptive protection solutions for scalable and reliable DER integration into distribution systems. This project significantly enhances the understanding of the impact of using appropriate inverter models on distribution and transmission (T&D) systems. By addressing the limitations of existing generic models, the project introduces high-fidelity models for stability, protection, electromagnetic transient (EMT), and quasi-static time series (QSTS) analyses. These models, integrated into commercial software tools, enable utilities, vendors, and developers to confidently study high-penetration PV systems. The project also demonstrates advanced applications, including adaptive protection schemes (APS) for distribution systems and microgrids, ensuring grid safety and reliability. The technical effectiveness and economic feasibility of the methods are evident through the development and validation of sophisticated inverter test plans and the selection of representative inverters. Testing by EPRI and NREL on retail, commercial, and utility-scale inverters, conforming to IEEE standards, underscores the robustness of the models. Improvements to existing generic models for various analyses further enhance their validity and applicability. The project also identifies gaps in common distribution protection schemes and designed new APS using improved DER models, demonstrating their effectiveness through modeling and hardware-in-the-loop (HIL) testing. The project’s benefits to the public are manifold. By advancing the standardization and model-based representation of IBR response, it supports transmission planning, stability assessments, and future IBR interconnection requirements. The generic models can facilitate better communication between transmission planners and developers, supporting expected IBR plant capability and performance. Additionally, the development of APS for radial feeders, meshed networks, and microgrids supports the integration of distributed energy resources (DERs) into distribution systems, enhancing grid reliability and safety. The project’s emphasis on thorough testing and simplicity in design ensures practical and scalable solutions for DER integration.

14 SOLAR ENERGY↗
DOE OSTI2020

Cybersecurity Resiliency of Marine Renewable Energy Systems-Part 1: Identifying Cybersecurity Vulnerabilities and Determining Risk

Technology innovation, market demand, and the potential impacts of a changing climate are driving the marine renewable energy (MRE) industry to develop market-ready systems to provide low-carbon electricity for emerging, off-grid markets. The advanced operational and information technology devices used in MRE systems create a pathway for a cyber threat actor to gain unauthorized access to data or disrupt operation. To improve the resiliency of MRE systems as a predictable, affordable, and reliable source of energy from oceans and rivers, guidance was developed for an end users' organization that describes a framework for identifying and managing cybersecurity risk. The development of the cybersecurity guidance is based on standards described in the Risk Management Framework and Cybersecurity Framework developed by the National Institute of Standards and Technology (NIST). This paper is the first of a two-part series that describes an approach to determine the cybersecurity risk for MRE systems based on assessing potential cyber threats, identifying vulnerabilities (people, processes, and technology, including physical and operational environment), and evaluating the consequences a cyberattack would have on operation of the MRE system and impact on end users' mission and business objectives. MRE developers and stakeholders can use this approach to assess their current cybersecurity risk posture to incorporate appropriate cybersecurity controls to reduce the consequences and impacts from a cyberattack on MRE systems. This approach can be refined further as MRE systems are deployed and operational configurations are available.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The Use of High-Density UN Fuel in Heat-Pipe Microreactors

Heat-pipe microreactors (HPMRs) are very small-scale nuclear reactors that employ heat pipes (HPs) for heat removal. HPMRs can be easily integrated with other forms of renewable energies, can be used for emergency responses to disaster relief zones, can be deployed in remote locations not connected to the grid, and can be removed from sites and replaced by new ones. HPMRs can also be used for space missions as HPs do not rely on gravity for heat transfer. Conventional fuel materials, such as uranium oxide (UO 2 ) and uranium oxycarbide (UCO), are currently considered in most existing HPMR designs, but ceramic uranium nitride (UN) fuel that has high uranium density, high thermal conductivity, and high melting point may become a better fuel candidate. Through neutronics calculations, this paper assesses the impact of using UN fuel in HPMRs with two different neutron spectra (fast and thermal) and two different fuel forms [traditional solid fuel pellets and TRi-structural-ISOtropic (TRISO) fuel compacts]. It was concluded that retrofitting HPMRs with UN fuel has the potential to reduce the initial 235 U enrichment requirement by ~3 wt% (to keep the same cycle length) or increase the cycle length (by keeping the same initial 235 U enrichment), which enables more compact and transportable HPMR core designs. However, using UN fuel decreases the control element worth [by up to 20% for the Special Purpose Reactor (SPR) and 5% for HP-MR] and is up to 80% more costly. Increasing 15 N enrichment can further decrease the initial 235 U enrichment requirement and increase the control element worth but is more costly. In conclusion, compared to fast-spectrum HPMRs fueled with solid pellet fuels, retrofitting UN fuel is more suitable for thermal-spectrum HPMRs fueled with TRISO fuel compacts, where the neutron spectrum hardening caused by using UN is less significant.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Designing the PR100 Study: Puerto Rico Grid Resilience and Transition to 100% Renewable Energy

Puerto Rico has committed to meeting its electricity needs with 100% renewable energy by 2050, along with realizing interim goals of 40% by 2025, 60% by 2040, the phaseout of coal-fired generation by 2028, and a 30% improvement in energy efficiency by 2040 as established in Act 17. [1] To meet these goals and support widespread end-use electrification, the territory must explore how renewable energy and other generation technologies can be developed with energy storage, distributed generation, distribution control, electric vehicles, and energy efficient and responsive loads in each of Puerto Rico's cities and communities. To support Puerto Rico in reaching its renewable energy goals; help ensure energy system resilience against future extreme weather events; improve energy justice; and provide inputs to LUMA Energy's walk, jog, and run approach in its coordinated planning roadmap, the U.S. Department of Energy, National Renewable Energy Laboratory, Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Sandia National Laboratories propose to evaluate 100% renewable energy pathways through an integrated analysis process. This talk will present steps in designing a two-year study entitled Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy (PR100). [1] U.S. Energy Information Administration (EIA). 2020. Puerto Rico Territory Energy Profile.

100% renewable energy↗