Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “load uncertainty”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Support of the Development of EPP Plus SMT Design Method (FY2020 Test Results)

Experiments in support of the development of the integrated Elastic–Perfectly Plastic (EPP) analysis and Simplified Model Test (SMT) design methodology continued in FY 2020. The previously developed single-bar SMT (SBSMT) technique was successfully extended to tubular shaped Alloy 617 specimens for evaluation of the effect of primary pressure load on SMT creep-fatigue (CF) properties at 950°C. A series of pressurized SMT tests were performed with various elastic follow-up factors and strain ranges. The results show that the primary pressure load reduces the SMT CF cycles. The reduction of SMT CF life due to primary load was found to be dependent on strain ranges, elastic follow up and test temperatures. These results are crucial for verification of the EPP strain range analysis in the EPP+SMT evaluation procedure. Additionally, hold time effect on the SMT CF life cycles is a determining factor for generating the EPP+SMT CF design curves. Lack of test data in the high cycle and low strain range region results in major uncertainty in developing the design curves. In FY2020, experiments were designed, and testing started on Alloy 617 at 950°C to fill the gap in experimental data. The on-going CF and additional SMT CF with elastic follow-up at low strain ranges will generate the information needed to verify the methods for extrapolation to long hold time and finalize the EPP+SMT design method.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Online Model-Free DER Dispatch Via Adaptive Voltage Sensitivity Estimation and Chance Constrained Programming

This paper proposes an online data-driven distributed energy resource management system (DERMS) for distribution system optimal DER dispatch as well as voltage regulation. Here, the key innovation is to leverage the Local Sensitivity Factor (LSF) for transforming the DER control into a computationally efficient linear programming (LP) problem. By taking real-time measurements, the estimation of LSF eliminates the need for an accurate distribution system model as well as full nodal load information, which is difficult to achieve in practice. A robust recursive least squares method is also developed to ensure the robust estimation of LSF, which is initialized using reasonable values from model-derived LSFs. This allows the system to adapt to changing operational conditions effectively. A scenario-based, chance-constrained framework is further employed to ensure voltage remains within acceptable limits in the presence of measurement and estimation uncertainties. Test results on a real-world, 759-node distribution network located in western Colorado, U.S., validate the effectiveness and robustness of the proposed control approach and demonstrate its superior performance as compared to alternative methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Best Practices for Shielding Analyses of Activated Metals and Spent Resins from Reactor Operation

This report investigated best practices for performing shielding evaluations of Type B waste packages, as defined in 10 CFR Part 71 regulations on packaging and transportation of radioactive material, or packages for which the contents are not defined before loading and may include a broad range of nuclides, geometries, and non-fuel materials. The following non-fuel waste streams were analyzed: Activated metals from decommissioned commercial power reactors, including Type 304 stainless steel, reactor vessel steel, and Inconel, Control blades from boiling water reactors, Neutron-activated corrosion products on surfaces of activated metals, and Spent resins from power plant operations. Measured elemental compositions, including major constituents and impurities, for steel and Inconel samples from commercial power reactors were used in activation calculations to determine radionuclide inventories in activated metals. For a simplified cask model, 60 Co contribution to the total external package dose rate at 30 days after shutdown varied from approximately 60% to 95%, depending on the activated metal, initial cobalt impurity concentration in the metal, and the thickness of the overpack gamma shield. Its maximum contribution to the total external package dose rate of approximately 100% was reached within the time interval of 2 to 5 years after shutdown and was maintained for up to 45 to 60 years after shutdown, depending on material, initial cobalt impurity concentration, and shield thickness. Thereafter, the 60 Co contribution to external package dose rate decreased with increasing decay time. Cobalt-60 is primarily produced by neutron reactions with the cobalt impurity in steel and Inconel. Other important radionuclides in activated metals contributing to package external dose rate are radionuclides with relatively short decay times, including 51 Cr, 59 Fe, 58 Co, and 54 Mn. These radionuclides may be represented as an equivalent 60 Co activity/source because 60 Co gamma ray emissions are bounding in terms of source strength and energy to other important radionuclides identified in the analyzed activated metals. Approaches for modeling the neutron-activated corrosion products that may be attached to activated reactor components were analyzed in this report. It was demonstrated that a surface source is more conservative than a uniform volumetric source for the treatment of neutron-activated corrosion products with respect to external package dose rates. An analysis of the maximum radionuclide loadings reported on spent resins identified the radionuclides 137 Cs, 60 Co, 134 Cs, 65 Zn, and 58 Co as the primary contributors to external package dose rate. For a resin cooled for 3.08 years, the external package dose rate was entirely produced by the reported 137 Cs and 60 Co inventory. The neutron sources from actinides found on spent resins or activated metals produced negligible dose rates and may be ignored in dose rate analyses. Effects of idealized waste material, source geometry, and spatial material/source distributions on external package dose rates were determined based on dose rate results for a simplified cask model under normal conditions of transport. Type 304 stainless steel, zirconium, and aluminum with adjusted mass densities based on a maximum content weight were analyzed for material modeling effects on external package dose rate. These materials produced identical external package dose rates within the statistical uncertainties of the dose rate estimates. Among four different source geometry configurations with homogeneous material of different mass densities, uniform volumetric source distribution, and the same source strength, the geometry configuration with lowest mass density (i.e., minimum self-shielding effect among the four cases) was most conservative. Spatial source distributions that better represent localized peak 60 Co activity values were more conservative than a uniform volumetric source distribution, assuming the same weight and total source strength per package. The increase in external dose rate caused by localized source peaks can be as much as the ratio between source peak activity density to average activity density, depending on the location of the activated metal with peak activity density. Therefore, the shielding analysis may be simplified if localized peak activities and the average activity per package can be measured/determined and documented at the time of cask loading. For simplicity, external package dose rates may be determined based on average source activity and a uniform volumetric source distribution. The dose rate results from that calculation model multiplied by the ratio of peak activity density to average activity density will produce maximum dose rate values for conservative estimates.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

What does the future hold for utility electricity efficiency programs?

Here, this study develops projections of future spending and savings from electricity efficiency programs funded by electric utility customers in the United States through 2030 based on three scenarios. Our analysis relies on detailed bottom-up modeling of current state energy efficiency policies, demand-side management and integrated resource plans, and regulatory decisions. The three scenarios represent a range of potential outcomes given the policy environment at the time of the study and uncertainties in the broader economic and state policy environment in each state. We project spending to increase to $8.6 billion in 2030 in the medium scenario, about a 45 percent increase relative to 2016 spending. In the high case, annual spending increases to $11.1 billion in 2030 and remains relatively flat in the low case ($6.8 billion in 2030). Our analysis suggests that electricity efficiency programs funded by utility customers will continue to impact load growth significantly at least through 2030, as savings as a percent of retail sales are forecast at 0.7 percent in the medium scenario and 0.98 percent in the high scenario.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Hybrid AI-ML and FE-based Digital Twin Predictive Modeling Framework for a PWR Coolant System Components: Updates on Multi-Time-Series-3D-Location Dependent Usages Factor Prediction

The long-term operation (LTO) of nuclear power plants (NPP) beyond their original design life of 40 years can lead to more material damage associated with cyclic fatigue under thermal-mechanical loading cycles and associated long-term exposure of reactor material to the deleterious reactor-coolant environments. However, under this LTO condition, the reactor components can still safely operate but may require more frequent Nondestructive Evaluation (NDE) of reactor components. Requiring frequent NDE inspections may lead to frequent NPP shutdowns which can lead to power outages and additional NDE inspection cost-related economic loss. The economic loss can be minimized by reducing uncertainty in life estimation of safety-critical pressure boundary components and by implementing a more digital approach such as using upcoming digital-twin (DT) technology for predicting the structural states (e.g., time and location dependent inside/outside thickness temperature, stress, strain, plastic deformation, etc.) and associated fatigue life of a component in real time. The DT framework is based on limited experimental data, Artificial-intelligence (AI)-Machine-Learning (ML) and multiphysics-computationalmechanics such as finite element- (FE) based models. Given the real-time thermal-hydraulic process measurements from several existing plant sensors, the overall goal of the DT framework is to predict the cumulative usages factors or equivalent fatigue lives in real time and at any random 3D location of the components. This includes inaccessible locations such as inside the thickness or location of a component. This prediction can be at thousands to millions of 3D point clouds or locations like conventional FE-based models, but without running an FE model in real time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Cookoff of Powdered and Pressed Explosives using a Micromechanics Pressurization Model

Cookoff experiments of powdered and pressed TATB-based plastic bonded explosives (PBXs) have been modeled using a pressure-dependent universal cookoff model (UCM) in combination with a micromechanics pressurization (MMP) model described in a companion paper. The MMP model is based on the accumulation of decomposition gases at nucleation sites that load the surrounding TATB crystals and binder. This is the first cookoff model to use an analytical mechanics solution for compressibility and thermal expansion to describe internal pressurization caused by both temperature and decomposition occurring within closed-pore explosives. This approach produces more accurate predictions of ignition time and pressurization within high-density explosives than simple equation-of-state models. The current paper gives details of the reaction chemistry, model parameters, predicted uncertainty, and validation using experiments from multiple laboratories with errors less than 6 %. The UCM/MMP model framework gives more accurate thermal ignition predictions for high density explosives that are initially impermeable to decomposition gases.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Economic Analysis of an Electric Thermal Energy Storage System Using Solid Particles for Grid Electricity Storage

As renewable power generation becomes the mainstream new-built energy source, energy storage will become an indispensable need to complement the uncertainty of renewable resources to firm the power supply. When phasing out fossil-fuel power plants to meet the carbon neutral utility target in the midcentury around the world, large capacity of energy storage will be needed to provide reliable grid power. The renewable power integration with storage can support future carbon-free utility and has several significant impacts including increasing the value of renewable generation to the grid, improving the peak-load response, and balancing the electricity supply and demand. Long-duration energy storage (10–100 hours duration) can potentially complement the reduction of fossil-fuel baseload generation that otherwise would risk grid security when a large portion of grid power comes from variable renewable sources. Current energy storage methods based on pumped storage hydropower or batteries have many limitations. Thermal energy storage (TES) has unique advantages in scale and siting flexibility to provide grid-scale storage capacity. A particle-based TES system has promising cost and performance for the future growing energy storage needs. This paper introduces the system and components required for the particle TES to be technically and economically competitive. A technoeconomic analysis based on preliminary component designs and performance shows that the particle TES integrated with an efficient air-Brayton combined cycle power system can provide power for several days by low-cost, high-performance storage cycles. It addresses grid storage needs by enabling large-scale grid integration of intermittent renewables like wind and solar, thereby increasing their grid value. The design specifications and cost estimations of major components in a commercial scale system are presented in this paper. The cost model provides insights for further development and cost comparison with competing technologies.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2021

Economic Analysis of a Novel Thermal Energy Storage System Using Solid Particles for Grid Electricity Storage: Preprint

As renewable power generation becomes the mainstream new-built energy source, energy storage will become an indispensable need to complement the uncertainty of renewable resources to firm the power supply. When phasing out fossil-fuel power plants to meet the carbon neutral utility target in the midcentury around the world, large capacity of energy storage will be needed to provide reliable grid power. The integration of renewable power and storage to support future carbon-free utility has several significant and positive impacts including expanding the renewable generation into the grid, improving the peak-load response, and balancing the electricity supply and demand. Long-duration energy storage (10–100 hours duration) can potentially complement the reduction of fossil-fuel baseload generation that otherwise would risk grid security when a large portion of grid power comes from variable renewable sources. Current energy storage methods based on pumped storage hydropower or batteries have many limitations. Thermal energy storage (TES) has unique advantages in scale and siting flexibility to provide grid-scale storage capacity. A particle-based TES system has promising cost and performance for the future growing energy storage needs. This paper introduces the system and components required for the particle TES to be technically and economically competitive. A technoeconomic analysis based on preliminary component designs and performance shows that the particle TES integrated with an efficient air-Brayton combined cycle power system can provide power for several days by low-cost, high-performance storage cycles. It addresses grid storage needs by enabling large-scale grid integration of intermittent renewables like wind and solar, thereby increasing their grid value. The design specifications and cost estimations of major components in a commercial scale system are presented in this paper. The cost model provides insights for further development and cost comparison with competing technologies.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2022

Insights into Methodologies and Operational Details of Resource Adequacy Assessment: A Case Study with Application to a Broader Flexibility Framework

Assessing and maintaining resource adequacy (RA) is a core pillar of power systems. However, recent changes in the physical makeup of these systems and the conditions under which these systems must operate have yielded a renewed interest in the methods, metrics, and assumptions that underpin RA assessments. In this paper, we systematically explore a wide range of RA modeling dimensions, including: the objective function and level of operational detail in the underlying model formulation; the quantity (look-ahead) and quality (accuracy) of data that is available for making operational decisions within those models; and the physical configuration of solar photovoltaics (PV) with battery storage hybrid resources. We apply a set of probabilistic RA tools and production cost modeling tools to a realistic test system based loosely on a future Electric Reliability Council of Texas power system dominated by solar PV resources. Under the assumptions of our system and models, we find that multi-stage probabilistic assessments may provide a more robust evaluation of RA by capturing a wider range of operational and system interactions, but this comes at a computational cost of 1-2 orders of magnitude longer run time depending on the specific configuration. In addition, the information on thermal generator availability impacts RA performance by an order of magnitude more than solar resource forecasts, which is driven by the comparatively larger magnitude of thermal outages than solar forecast errors within our test system. Lastly, the flexibility provided by hybrid and other resources can help reduce system load-shedding event frequencies and enable the system to be more robust to inaccurate forecast information, and alternative hybrid inverter sizes can impact RA levels by 1-2 orders of magnitude. Our results point to the importance of a broader flexibility framework to describe the interaction between (1) flexibility "supply" from both physical resource capabilities and operational constraints considered in the modeling, and (2) flexibility "demand" from forecast errors, thermal generator outages, and other sources of uncertainty, as well as their RA impacts. Results are likely sensitive to the system buildout explored; future work could consider additional system configurations and conditions.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗
DOE OSTI2026

Examining the Impacts of Microphysical-Dynamical Feedbacks on Convective Clouds in Different Aerosol Environments Using Enhanced Observational and Modeling Strategies

This project investigated how microphysical–dynamical feedbacks influence deep convective clouds across a range of aerosol conditions, storm lifecycles, and meteorological regimes, and how these sensitivities depend on the modeling framework used to represent convection and microphysics. Using the Aerosol, Cloud, Precipitation, and Climate (ACPC) Working Group model intercomparison simulations of isolated deep convection in the Houston region, we found a robust warm-phase aerosol response in most cloud-resolving models. Increased aerosol loading tended to suppress warm-rain production, increase cloud water, and reduce surface rainfall and near-surface evaporation. These impacts were typically strongest early in the convective lifecycle, with the largest aerosol-driven differences occurring during the first half of storm evolution. The ice-phase response, on the other hand, varied widely across modeling frameworks, and differed in sign, timing, and vertical structure. Ice microphysical pathways and parameterizations are therefore leading sources of uncertainty in aerosol–deep convection interactions. Theoretical analyses further suggested that aerosol-driven invigoration through cold-phase processes was much weaker than previously hypothesized for cold-based storms, and in warm-based storms could even reduce updraft strength. These results imply that any invigoration signal is more likely linked to warm-phase processes and peaks early in storm development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Cost-Benefit Analysis of Electricity Resilience Projects: State of the Art and Gap Analysis

Utilities and regulators must weigh the benefits of electricity resilience projects against their costs, which would be passed on to customers. Cost-benefit analysis (CBA) is an appropriate method for assessing this tradeoff. Here, in this paper we review the literature on CBA of electricity resilience projects and analyze gaps in the available methods and tools. The costs of resilience projects are typically straightforward to estimate but their benefits — particularly the avoided costs of power interruptions — are complex to quantify and monetize. A common perception among practitioners is that current CBA tools are not sufficiently mature to be adopted into real-world practice. We propose an electricity resilience CBA framework consisting of several elements: risks, physical impacts, power interruptions, economic impacts, and resilience projects. While methods for some elements are well-developed, there is a need for novel approaches to value avoided power interruptions, integrate multiple risks and benefit streams, and incorporate uncertainty.

Cost-benefit analysis↗
DOE OSTI2022

Stochastic Strategic Participation of Active Distribution Networks With High-Penetration DERs in Wholesale Electricity Markets

With the increasing penetration of distributed energy resources (DERs), traditional distribution networks as load-serving entities in wholesale electricity markets, now evolve towards active distribution networks (ADNs) which can proactively participate in wholesale markets by optimally controlling the DERs in their networks. A stochastic bilevel optimization model is proposed in this paper for the strategic participation of ADNs and DERs to provide energy and grid services in wholesale electricity markets. The bilevel optimization model can capture the interactions between the ADN and the wholesale energy and ancillary service markets, considering the uncertainties of DERs in the ADN. In the upper-level model, the ADN makes optimal decisions on energy and reserve bidding considering the availability, uncertainties, and flexibility of DERs. The joint energy and reserve market-clearing of the independent system operator (ISO) is modeled as the lower-level problem. Using strong duality theory and Karush-Kuhn Tucker (KKT) conditions, the proposed bilevel optimization problem is reformulated as mathematical programming with equilibrium constraints (MPEC) problem and further converted into a computationally-solvable mixed-integer second-order-cone programming (MISOCP) model. The simulation results demonstrate the effectiveness of the model and the interactions between an ADN and wholesale electricity markets.

active distribution network↗
DOE OSTI2020

A Fast Flexibility-Driven Generation Portfolio Planning Method for Sustainable Power Systems

We are witnessing an acceleration in the uptake of renewable energy in power systems. Because of the associated variability and uncertainty of renewables, power systems need to have an adequate supply of flexibility to allow for suitable management of short-term operations. So far most of the work in this area has neglected how flexibility needs associated with renewables are fulfilled as part of dispatchable generation capital investments decisions. To address this challenge, we propose an approach to plan the dispatchable generation mix of a power system as needed to counteract variability and uncertainty associated with significant shares of variable renewable generation. The approach exploits the linear time-invariant feature of variable generation variability using historical phase planes of capacity (in MW) and ramp (in MW/min) to bridge the gap between long-term capacity planning and short-term intra-hour flexibility needs. This approach is much more computationally tractable than other proposals, while also being able to capture adequately short-term operational features like ramping and net load variability. Numerical tests are performed on realistic datasets to substantiate the effectiveness of the approach.

bulk power system planning↗
DOE OSTI2022

High-Fuel Loading Ignition Delay Time Characterization of Hydrogen/Natural Gas/Ammonia at Gas Turbine-Relevant Conditions Inside a High-Pressure Shock Tube

Abstract This study explores the combustion characterization of high-fuel percentage, air-diluted mixtures of H2 mixed with natural gas (NG) as well as mixtures of H2 and NH3 at temperatures and pressures relevant to turbine operating conditions (20–30 bar, 1000–1500 K). Lower temperatures (below 1070 K) exhibit preignition characteristics due to non-homogeneity. An attempt to mitigate these occurrences at high pressures is investigated using the constrained reaction volume (CRV) stage-filling technique. Due to the need to further refine the facility CRV stage-filling uncertainty, only higher temperature data will be interpreted at this time. The test conditions in this study closely replicate the temperatures, pressures, and mixtures that would be seen in hydrogen-powered gas turbines, making it the first to explore such conditions. The experimental IDTs were compared against the current state-of-the-art chemical kinetic models for mechanism validation. The current work will advance H2-powered turbines and aims to determine the optimum molecular ratio of H2 when mixed with natural gas.

Pierro, Michael↗
DOE OSTI2025

A Probabilistic Reasoner Based on Bayes Risk for Damage Detection in Structural Systems

Structural health monitoring (SHM) systems are used to inform operation of structural systems subject to loads and environments that may affect their integrity. SHM systems rely on continuous monitoring of the structure to determine its health state. These systems are often coupled with a model of the deployed structure to determine the consequences of changes in the system by forecasting the response to future states. These models, which may be thought of as digital twins, need to be updated to reflect the latest state of the structural system. This work makes use of an uncertainty-aware machine learning model that enforces distance preservation of the original input space to determine deviations from the training data input space distributions. This workflow enables domain shift detection to determine whether damage is present in the structure. The uncertainty metrics generated by this network are then used in a Bayes risk framework to design an optimal damage detector given cost and risk considerations. The approach is demonstrated on a computational example with simulated damage.

Najera-Flores, David [ATA Engineering, Inc.]↗
DOE OSTI2021

Climate-Induced Tradeoffs in Planning and Operating Costs of a Regional Electricity System

Electricity grid planners design the system in order to supply electricity to end users reliably and affordably. Climate change threatens both objectives through potentially compounding supply- and demand-side climate-induced impacts. Uncertainty surrounds each of these future potential impacts. Given long planning horizons, system planners must weigh investment costs against operational costs under this uncertainty. Here, we developed a comprehensive and coherent integrated modeling framework combining physically-based models with cost-minimizing optimization models in the power system. We applied this modeling framework to analyze potential tradeoffs in planning and operating costs in the power grid due to climate change in the Southeast U.S. in 2050. We find that planning decisions that do not account for climate-induced impacts would result in a substantial increase in social costs associated with loss of load. These social costs are a result of under-investment in new capacity and capacity deratings of thermal generators when we included climate change impacts in the operation stage. Finally, these results highlight the importance of including climate change effects in the planning process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Residual Insoluble Solids Expected from Saltcake Dissolution

A review of previous SRS saltcake dissolution and characterization studies was performed to inform the analysis of the amount of residual insoluble solids that may result from saltcake dissolution. A realistic value covering most cases for the maximum volume of a settled layer of residual insoluble solids that would result from dissolution of a volume of saltcake was calculated as 0.08 mL/mL (8 vol%). Applying factors to account for dissolution test uncertainty and differences between in-tank settling and laboratory testing, the recommended value for a settled layer of residual insoluble solids that would result from dissolution of a volume of saltcake is 0.16 mL/mL (16 vol%). This should apply to dissolution of saltcake with typical minimal amounts of entrained sludge but may not apply to saltcake with significant sludge. As it is composed of primarily non-radioactive isotopes, the precipitated aluminum hydroxide material does not contribute to the heat load.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Model-Free Building Temperature Control and Power Allocation Under Measurement Time Delays

Taking a step towards a greener planet has created an increased need for a higher integration of renewable energy resources into the electric grid. Nonetheless, the intermittency and uncertainty associated with renewable generation have slowed down this integration. Demand response (DR) has been recently adopted to address this challenge by utilizing demand side flexibility and enabling the participation of many grid-interactive efficient buildings (GEBs). However, existing DR methods require significant modeling and/or training efforts and are computationally expensive. To address the aforementioned issues, we propose a model-free control (MFC)-based strategy that is robust to the time delays in the temperature measurements of the thermostatically controlled loads (TCLs). It assigns to each GEB a local controller to maintain the TCLs’ temperatures within desired comfort levels, while the load aggregator (LA) allocates the assigned reference power provided by the distribution system operator (DSO) to support a specific grid service, such as demand peak reduction, load shifting, balancing supply and demand, and consuming the solar photovoltaic power locally. We investigate the effects of such loss of information on the local control action as well as on meeting the power allocation constraint. We conclude that, for an appropriate choice of design parameters, the proposed MFC controller is satisfactorily robust to measurement time delays.

Telsang, Bhagyashri↗