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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Value of Nuclear Energy to the Reliability of the North American Power System: Results for Western and Eastern Interconnections

This report documents the fulfillment of a milestone for the United States (U.S.) Department of Energy Office of Nuclear Energy Light Water Reactor Sustainability Program: completing a baseline study of regional impact of nuclear power plants and hydrogen production in maintaining grid services and power quality. Models have been comprehensively demonstrated for the Western Interconnection, or Western Electric Coordinating Council area, and in the Eastern Interconnection for scenarios representative of past extreme events (e.g., drought and heat waves). Understanding the impact on the reliability of the bulk electric system of any reduction in generation capacity from nuclear power, for any reason, is the motivation of this work. Factors that might lead to the premature or unplanned closure of nuclear plants, extended outages, or repurposing of nuclear power include: • Aging infrastructure: Many nuclear power plants in the U.S. are nearing the end of their designed operating lives. Upgrading aging infrastructure can be expensive, and some utilities may choose to retire plants rather than invest in costly upgrades. • Low wholesale electricity prices: The deregulation of the electricity market in many states has led to increased competition and driven down wholesale electricity prices, causing nuclear power operators to seek other revenue sources for their heat and power such as clean hydrogen production. • Renewables growth: The rapid growth of renewable energy sources like solar and wind power is posing a challenge to traditional generation sources like nuclear. While many see renewables as a key part of the clean energy transition, their intermittent nature requires additional grid solutions for reliable power supply. • The potential for regulatory decisions to be in conflict: In its 2021 rulemaking, EPA rule (86 FR 880), the Environmental Protection Agency (EPA) set a compliance date for the ban on processing and distribution in commerce of Decabromodiphenyl Ether (DecaBDE). Since DecaBDE is in many components, particularly wiring, of nuclear power plants which are deemed safety-related or important to safety, three plants would not have been able to restart after their 2023 spring outages, and numerous others would have faced issues in the near future. Fortunately, in this case, the EPA provided relief to the nuclear energy industry. The report provides a summary of the significant role nuclear energy plays in the United States’ power generation mix, supplying around 20% of the nation’s electricity generation, spread across 28 U.S. states. Nuclear power is reliable, mostly unaffected by weather and seasonal changes, and provides a consistent source of baseload power. In terms of capacity, nuclear power plants account for as much as 26% of balancing area power generation capacity. Nuclear power also provides a substantial contribution (e.g., 10% of the inertia in the Eastern Interconnection) of the synchronous spinning mass/inertia that buffers the rate at which frequency changes when a load and generation imbalance occurs (e.g., a large plant trips or a load is suddenly shed due to a transmission outage). This contribution is critical for maintaining grid stability during sudden changes in load or generation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Methods and Tools To Assess Robustness of Nuclear Plant Outages

Refueling outages are one of the most challenging phases in a nuclear power plant (NPP) operating cycle. Refueling outages are extremely costly for an NPP due to the large amount of required resources and because of lost revenue due to plant being off the grid. Outage durations have steadily decreased across the industry over that last few decades primarily due to improved planning and coordination, but there are still many plants that struggle to meet the performance metrics accomplished by other utilities. Schedule resilience is one of the issues. NPP outages require scheduling thousands of activities within 30 days on average. Despite detailed planning, once the outage starts, numerous emergent issues typically appear along with schedule delays requiring continuous replanning and adjustment. When schedule disruption occurs during an outage, plant staff make urgent efforts to recover but are often not able to maintain the planned outage duration. These outage delays can cost a utility several million dollars per day. Tools that could help outage schedulers create a more resilient schedule and allow them to optimally reschedule emergent work could significantly reduce outage delays. One key aspect of creating a resilient schedule is to have accurate estimates for activity duration. Another important outage scheduling capability is the ability to schedule emergent work with minimal disruption. This paper focuses on developing tools and methods to support NPPs with outage schedule optimization and it describes the initial development of tools to support outage management that leverage computational and machine learning methods.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Multi-Objective PMU Allocation for Resilient Power System Monitoring

Phasor measurement units (PMUs) enable better system monitoring and security enhancement in smart grids. In order to enhance power system resilience against outages and blackouts caused by extreme weather events or man-made attacks, it remains a major challenge to determine the optimal number and location of PMUs. In this paper, a multi-objective resilient PMU placement (MORPP) problem is formulated, and solved by a modified Teaching-Learning-Based optimization (MO-TLBO) algorithm. Three objectives are considered in the MORPP problem, minimizing the number of PMUs, maximizing the system observability, and minimizing the voltage stability index. The effectiveness of the proposed method is validated through testing on IEEE 14-bus, 30-bus, and 118-bus test systems. The advantage of the MO-TLBO-based MORPP is demonstrated through the comparison with other methods in the literature, in terms of iteration number, optimality and time of convergence.

Multi-Objective Optimization↗
DOE OSTI2022

Westinghouse advanced fuel management strategies leveraging high enrichment and high burnup fuel to optimize PWR economics

In the US, nuclear power plants have been focused on increasing electricity generation for over three decades via longer operating cycles, reduced number of outages and duration, and the implementation of power up-rates. The potential for zero-carbon emission credits and other carbon-reduction initiatives further makes nuclear power utilities to focus on increasing generation capability. Longer operating cycles provide increased energy generation and enable economic savings to nuclear utilities when the increase in fuel loading required to achieve the extended cycle energy target and resulting increase in total fuel cost is offset by the savings from outage avoidance and reduced replacement power costs. For the current licensed limits of 5 w/o {sup 235}U enrichment and 62 GWd/tU peak pin burnup, higher power density PWR plants, which are prevalent in the PWR fleet, require an excessively penalizing fraction of feed fuel assemblies to operate for the extended cycle duration, with inevitably poor fuel use and fuel cycle economics that cannot be counterbalanced by the savings on outage cost avoidance. To overcome this barrier, the nuclear industry is pursuing development of high enrichment/high burnup fuel technology ({sup 235}U enrichment up to 8 w/o and peak pin burnup up to 75 GWd/tU) which increases fuel energy generation capability and can enable high power density plants to achieve positive economics on 24-month cycle of operation. This paper presents advanced fuel management strategies developed by Westinghouse to enable transition of PWR reactors from 18-month to 24-month cycle of operation, with and without a core thermal power uprate, which are then used as basis to assess the economics of a direct transition from 18 to 24-month cycles with high enrichment/high burnup fuel. The results show that these fuel management strategies, especially if coupled with thermal power up-rates, present the opportunity for substantial economic benefits to utilities. The systematic review of fuel management strategies presented can provide an illustrative reference for decision makers as they consider how to maximize nuclear energy generation economically. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Random Forest Regressor-Based Approach for Detecting Fault Location and Duration in Power Systems

Power system failures or outages due to short-circuits or “faults” can result in long service interruptions leading to significant socio-economic consequences. It is critical for electrical utilities to quickly ascertain fault characteristics, including location, type, and duration, to reduce the service time of an outage. Existing fault detection mechanisms (relays and digital fault recorders) are slow to communicate the fault characteristics upstream to the substations and control centers for action to be taken quickly. Fortunately, due to availability of high-resolution phasor measurement units (PMUs), more event-driven solutions can be captured in real time. In this paper, we propose a data-driven approach for determining fault characteristics using samples of fault trajectories. A random forest regressor (RFR)-based model is used to detect real-time fault location and its duration simultaneously. This model is based on combining multiple uncorrelated trees with state-of-the-art boosting and aggregating techniques in order to obtain robust generalizations and greater accuracy without overfitting or underfitting. Four cases were studied to evaluate the performance of RFR: 1. Detecting fault location (case 1), 2. Predicting fault duration (case 2), 3. Handling missing data (case 3), and 4. Identifying fault location and length in a real-time streaming environment (case 4). A comparative analysis was conducted between the RFR algorithm and state-of-the-art models, including deep neural network, Hoeffding tree, neural network, support vector machine, decision tree, naive Bayesian, and K-nearest neighborhood. Experiments revealed that RFR consistently outperformed the other models in detection accuracy, prediction error, and processing time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Multiphysics analysis of fuel Fragmentation, Relocation, and dispersal Susceptibility–Part 2: High-Burnup Steady-State operating and fuel performance conditions

The US nuclear industry is pursuing increased cycle lengths and increasing the peak rod-averaged burnup in an effort to increase the economic viability of the US nuclear fleet. Increasing burnup will afford economic viability by enabling utilities to optimize core designs to reduce the number of fresh fuel assemblies per cycle and allow nuclear power plants to operate for a longer period of time. Longer operating periods will also decrease the number of outages experienced by a nuclear power plants and, therefore, offer utilities significant operational savings. However, extending the peak rod-averaged burnup beyond 62 GWd/tU results in operating fuel rods to higher burnup under higher power conditions. This operating regime is expected to result in higher fuel temperatures, fission gas release (FGR), and rod internal pressures (RIPs) that may challenge historical safety basis and affect high-burnup (HBU) experimental testing. In particular, these conditions directly affect fuel fragmentation, relocation, and dispersal (FFRD) susceptibility, so understanding the pretransient operating conditions is critical for developing test plans that evaluate the FFRD and develop strategies to mitigate it. This paper evaluates the operating conditions and fuel performance of HBU (greater than62 GWd/tU rod average) fuel. Additionally, it investigates fuel performance sensitivities and discusses the effect on fuel performance. Here, this work used two codes. Virtual Environment for Reactor Applications (VERA) was used to calculate steady-state power histories, identify HBU operating conditions using 10 different realistic HBU core designs, and down-select rods to a representative subset of fuel rods for subsequent BISON evaluation. The BISON fuel performance code was used to investigate steady-state HBU operating conditions and assess uncertainties associated with FGR and its effect on fuel temperatures and RIPs. The VERA and BISON results will provide direct input for HBU experimental testing and support subsequent TRACE and BISON transient fuel performance analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Equity‐aware power distribution system restoration

Abstract The efficient, reliable, and resilient supply of electricity has become essential for social and economic well‐being of the modern society. However, more frequent occurrence of extreme weather events has exposed inequity in the planning and operation practices of power distribution systems, evidenced in higher vulnerability and longer power interruptions for some parts of the grid as compared to others. This paper proposes an equity‐aware power distribution system restoration model in an effort to ensure a more equitable yet resilient power distribution operation after outages. To this end, the proposed equity‐aware distribution system restoration model balances the efficiency of the restoration operation and the equitable allocation of distributed energy resources among affected customers after an outage, while prioritizing the critical infrastructure (e.g. hospitals). The results demonstrate the effectiveness of the proposed framework to ensure a more equitable restoration process as measured by the proposed fairness and restoration performance indices.

Engineering↗
DOE OSTI2025

A Sequential Model Predictive and Deep Reinforcement Learning-Based Controller for Distribution System Outage Mitigation under Hurricane Events

This paper proposes a proactive outage mitigation framework for power distribution networks to withstand hurricane-induced disruptions. It leverages Model Predictive Control (MPC) to identify safe lines for proactive switching during hurricanes, minimizing the risk of cascading failures and voltage violations. The switching strategies optimized by MPC are sequentially integrated with a Deep Reinforcement Learning agent using the Advantage Actor-Critic algorithm, enabling dynamic line switching to maximize connected buses and minimize voltage violations in real time. Using a probabilistic hurricane model, the framework predicts line failures and adapts to varying conditions to enhance grid resilience. Simulations on the IEEE 123-bus system demonstrate its effectiveness in maintaining high connectivity and minimizing disruptions. Real-time testing with an RTDS confirms the practicality and reliability of the proposed approach.

Selim, Alaa [University of Connecticut]↗
DOE OSTI2023

Energy Resilience for Mission Assurance: Case Study Scoping Document

The Energy Resilience for Mission Assurance (ERMA) project—a Department of Energy Grid Modernization Lab Consortium effort carried out via a partnership among five national laboratories— seeks to develop metrics to quantify how improvements to energy system resilience translate to improved Department of Defense (DoD) mission assurance (MA) during wide-scale, long-duration outages of the bulk power system. DoD missions are integral to national security and highly dependent on electric power. However, energy system planners—both civilian and military—lack a clear and quantifiable mapping between electric power system resilience and MA, leaving a gap in their ability to understand and consider national security outcomes within their planning efforts. The ERMA project seeks to fill this gap, providing stakeholders with new capabilities to understand the impact of electric power system resilience on MA during hazard scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Dronebase Photovoltaic (PV) Fleet Imagery Quantitative Evaluation (CRADA CRD-22-22941 Final Report)

Combine the Dronebase aerial imagery with corresponding sites in the NLR Photovoltaic (PV) Fleets database. By combining these two data sources in an aggregated, anonymized fashion, we can perform the following analyses: quantifying power loss due to outages caused by stuck trackers, string outages, and shading/snow, validate site metadata, including tilt and azimuth, and correlate.

14 SOLAR ENERGY↗
DOE OSTI2024

MEASUREMENT OF THE NEUTRON FLUENCE-RATES IN THE ADVANCED TEST REACTOR

The axial neutron fluence-rate distribution at the Advanced Test Reactor (ATR) is determined using a combination of pure nickel and cobalt-aluminium alloy dosimeter wires. Most irradiation programs at ATR need to know the fast neutron fluence-rate surrounding their experiment to correlate post-irradiation examination results with neutron dose. The activated dosimeter wires, which extend beyond the full fuelled region of the reactor core, are highly radioactive following the full cycle in ATR and must therefore be measured in the ATR canal. The system that is employed for these measurements is mechanical scanning mechanism is used to scan the activated wires across the face of a columnated shield and a NaI detector. This detector is not sufficiently calibrated to provide absolute activity measurements, therefore, the count-rate is recorded and normalized to the highest activity for that wire. Then, an approximately 3-mm long portion of the wire is removed from the highest activity region in the wire. The wires are then transferred, and an absolute activity measurement is made using a calibrated ionization chamber. These measurements are combined with corrections for decay, neutron energy spectrum, burnup, dosimeter composition, reactor power fluctuations, and reactor outages to determine the average axial neutron fluence-rate at various locations within ATR during the cycle.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Material Selection and Sizing of a Thermoelectric Generator (TEG) for Power Generation in a Self-Powered Heating System

By employing the high temperature heat source to directly generate the electricity needed to power auxiliary systems in a natural gas furnace, boiler or hot water heater, a “self-powered” heating system can provide several benefits. Compared with a traditional furnace, boiler or hot water heater, when overall fuel utilization is kept constant, the self-powered system will have a higher primary energy efficiency, lower operating costs, and dramatically improved building safety and resilience during electric grid outages. Furthermore, a self-powered heating system only has a single utility connection – natural gas, without an electric connection – thus simplifying installation. A thermoelectric generator can be used for direct energy conversion of thermal energy to electricity with no moving parts, which offers a very simple means to provide power for the self-powered heating system, and the operation is without noise or vibration and can thus provide a very long system life. This paper provides an analysis focused on materials selection and the thermal power requirements for a thermoelectric generator (TEG) for use in a self-powered heating system. The dimensionless figure of merit for thermoelectric materials, zT, is used to estimate the optimal efficiency that can be achieved with a TEG to produce the electric power required in such an application. Comparisons of the predicted efficiency, the required heat transfer rate to the TEG and the heat transfer area needed for sustained operation under thermal conditions relevant to the self-powered heating application are made for several potential thermoelectric materials. This analysis was used to develop system requirements for a self-powered hot water heater using a TEG for electric power generation.

Laclair, Tim↗
DOE OSTI2020

The Local Seismoacoustic Wavefield of a Research Nuclear Reactor and Its Response to Reactor Power Level

In this article, we describe the seismoacoustic wavefield recorded outdoors but inside the facility fence of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (Tennessee). HFIR is a research nuclear reactor that generates neutrons for scattering, irradiation research, and isotope production. This reactor operates at a nominal power of 85 MW, with a full-power period between 24 and 26 days. This study uses data from a single seismoacoustic station that operated for 60 days and sampled a full operating reactor cycle, that is, full-power operation and end-of-cycle outage. The analysis presented here is based on identifying signals that characterize the steady, that is, full-power operation and end-of-cycle outage, and transitional, that is, start-up and shutdown, states of the reactor. We found that the overall seismoacoustic energy closely follows the main power cycle of the reactor and identified spectral regions excited by specific reactor operational conditions. In particular, we identified a tonal noise sequence with a fundamental frequency around 21.4 Hz and multiple harmonics that emerge as the reactor reaches 90% of nominal power in both seismic and acoustic channels. We also utilized temperature measurements from the monitoring system of the reactor to suggest links between the operation of reactor’s subsystems and seismoacoustic signals. We demonstrate that seismoacoustic monitoring of an industrial facility can identify and track some industrial processes and detect events related to operations that involve energy transport.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Hybrid power plants: An effective way of decreasing loss-of-load expectation

Diversifying variable renewable resources by combining wind, solar photovoltaic, and battery assets in a hybrid power plant can increase renewable energy usage efficiency and improve system flexibility, particularly in distributed energy systems. However, the resilience impact of these systems, particularly outage mitigation, can be difficult to quantify due to uncertainty in resource, energy demand, and outage occurrence. Here, this study outlines a framework to quantify the incremental benefit of hybrid power plant assets for reducing loss-of-load expectation during random outage events. Hybrid power plant performance during outages (considering varying duration and severity) is simulated using a Monte Carlo methodology to reflect uncertainty associated with renewable resource, load demand, and outage timing. Results demonstrate the additional incremental value from increasingly hybrid designs, in which relative capacities of wind, solar photovoltaic, and storage assets contribute to lower loss-of-load expectation than the constituent technologies would alone. The value of added wind or solar capacity increases as the plant composition approaches an equal split. The value of added battery capacity depends on the outage duration and severity, but the first 50 MWh of added storage capacity is the most valuable for reducing the loss-of-load expectation for all plant designs.

14 SOLAR ENERGY↗
DOE OSTI2021

Kickstart Your Federal Microgrid Resiliency Project: Financing Opportunities and Best Practices

Recent high-impact events such as hurricanes and wildfires have resulted in the loss of utility grid power to federal sites, highlighting the need for energy system resilience. To sustain critical functions, site loads may need to operate during an electric grid outage or at least have power restored quickly after the event. A microgrid can provide reliable backup power to critical loads when electric utility power is interrupted, and may also provide value during normal operations.

DER↗
DOE OSTI2025

Enhancing EV Charging Station Resilience with Multifunctional Converter Leg Integration

In this paper, a multifunctional converter leg is integrated into an EV charger’s power circuit to enhance EV charging station resilience under power electronics converter device faults and grid outages. In the event of a device fault, it substitutes the failed converter leg, maintaining operation. During a grid outage, it assists the system as a fourth leg to the front-end converter, enabling grid-forming capability to supply power to the charging station critical loads while allowing limited power vehicle charging. The proposed approach’s effectiveness under both front-end power converter device faults and grid outage scenarios are validated through simulation and controller hardware-in-the-loop results.

Pereira Pinto, Joao [ORNL]↗
DOE OSTI2023

Adaptive cold-load pickup considerations in 2-stage microgrid unit commitment for enhancing microgrid resilience

In an extended main grid outage spanning multiple days, load shedding serves as a critical mechanism for islanded microgrids to maintain essential power and energy reserves that are indispensable for fulfilling reliability and resiliency mandates. However, using load shedding for such purposes leads to increasing occurrence of cold load pickup (CLPU) events. Here, this study presents an innovative adaptive CLPU model that introduces a method for determining and incorporating parameters related to CLPU power and energy requirements into a two-stage microgrid unit commitment (MGUC) algorithm. In contrast to the traditional fixed-CLPU-curve approach, this model calculates CLPU duration, power, and energy demands by considering outage durations and ambient temperature variations within the MGUC process. By integrating the adaptive CLPU model into the MGUC problem formulation, it allows for the optimal allocation of energy resources throughout the entire scheduling horizon to fulfill the CLPU requirements when scheduling multiple CLPU events. The performance of the enhanced MGUC algorithm considering CLPU needs is assessed using actual load and photovoltaic (PV) data. Simulation results demonstrate significant improvements in dispatch optimality evaluated by the amount of load served, customer comfort, energy storage operation, and adherence to energy schedules. These enhancements collectively contribute to reliable and resilient microgrid operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

MaDEVIoT: Cyberattacks on EV Charging Can Disrupt Power Grid Operation

Extensive roll-out of electric vehicles (EVs) requires large-scale deployment of high-power EV Charging Stations (EVCSs). EVCSs are connected to the internet using Internetof- Things (IoT) such as smartphones, to improve the charging experience of users and increase their profitability. This paper studies the feasibility of demand-side cyberattacks launched on power grids via such internet-connected highpower EVCSs. The attack mechanism distorts power grid frequency and voltage, and has the potential to trigger systemwide outages. The case study, based on the power grid and EV deployment plans in Manhattan, New York, illustrates potential impacts of such attacks. The results show that such attacks will become feasible in Manhattan, New York in 2030, as EV adoption increases. Furthermore, the attacks in 2030 are feasible even compromising a single company’s EVCS server in Manhattan, New York. The attacks can cause line overloads and trip over-frequency protection relays, causing system-side blackout in the power grid in Manhattan, New York. The paper informs planning authorities and power grid operators involved with the roll-out of EV charging infrastructure about potential cyberthreats to power grids via manipulating internet-connected high-power EVCSs.

Acharya, Samrat S.↗