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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Predicting peak day and peak hour of electricity demand with ensemble machine learning

Battery energy storage systems can be used for peak demand reduction in power systems, leading to significant economic benefits. Two practical challenges are 1) accurately determining the peak load days and hours and 2) quantifying and reducing uncertainties associated with the forecast in probabilistic risk measures for dispatch decision-making. In this study, we develop a supervised machine learning approach to generate 1) the probability of the next operation day containing the peak hour of the month and 2) the probability of an hour to be the peak hour of the day. Guidance is provided on preparation and augmentation of data as well as selection of machine learning models and decision-making thresholds. The proposed approach is applied to the Duke Energy Progress system and successfully captures 69 peak days out of 72 testing months with a 3% exceedance probability threshold. On 90% of the peak days, the actual peak hour is among the 2 h with the highest probabilities.

25 ENERGY STORAGE↗
DOE OSTI2022

Online distributed price-based control of DR resources with competitive guarantees

Demand response (DR) of building HVAC load can provide crucial demand-side flexibility for the future smart grid. Compared to direct load control, price-based control can respect the customers’ autonomy and privacy. However, it is challenging for price-based control to attain provable performance guarantees under future uncertainty. In this paper, we propose a framework for a utility to perform price-based control of flexible building load within the utility’s service area, in order to attain competitive performance guarantees in terms of controlling the system peak demand under future uncertainty. By adopting a two-step approach, our online price-based control solution can attain a provable competitive ratio for all possible realizations within a given uncertainty set. Simulation experiments demonstrate that, with a robustification procedure, our solution can perform well not only for worst-case inputs, but also for average-case inputs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Titanium alloy response sensitivity to variations in spectral reconstructions of National Ignition Facility xenon line-emission x-ray sources

Thermomechanical shock experiments on the National Ignition Facility (NIF) aim to study high strain rate dynamic material response. In such experiments, the NIF laser is used to generate high fluence x-ray emission sources, which irradiate material samples of interest. Under sufficiently high x-ray energy deposition, thermomechanical impulses are generated in the materials. While it is known that the characteristics of x-ray generated impulses vary as a function of incident x-ray spectra, it remains unclear how spectral assumptions and uncertainties in NIF spectral reconstructions affect our interpretation of impulsive loading. Here, in this paper, we simulate the response of a standard titanium alloy baseline sample to synthetic analytically derived and measured NIF xenon line-emission x-ray sources with a radiation hydrodynamics code. We vary the source spectral characteristics based on different source reconstruction techniques to understand the resulting variation in baseline sample response and compare the simulated response with experimental results. We find that the response is highly sensitive to assumptions made about the spectral contents and that knowledge of spectral uncertainties bounds our understanding of the resulting material response. The results of this effort help to extend our ability to use baseline material samples to extract quantitative properties from x-ray experiments on the NIF.

Alloys↗
DOE OSTI2024

Optimal hybrid power plants for electric vehicle charging demand

Transmission constraints, increasing motivations to decarbonize, and concerns over peak electric vehicle (EV) load impacts on local grids have driven electric customers to consider behind-the-meter, hybrid power plant generation and storage at the distributed-grid level for EV charging. In this study, we develop capabilities to optimize hybrid power plant component capacities for EV charging. We then demonstrate these capabilities in a case study for Boulder, Colorado, using public EV charging data as well as wind and solar resource data. Our results show system designs that balance the cost of energy with load-meeting and peak shaving performance. Within the case study, systems designed for wind, solar photovoltaic (PV), and storage resulted in lower cost of energy than those optimized for PV and storage only. This indicates that in areas where wind resource exists, hybrid power plants that include wind, PV, and battery assets can better meet EV charging loads (including peak loads that are prone to overloading local grids) than PV and battery assets alone. Future work to address limitations in this paper include extending cost modeling to include performance losses (e.g., based on operations or weather) and charging station costs to estimate levelized cost of charging, and quantifying uncertainty and error in our aggregation methods for estimating EV charging loads at the hourly timescale.

14 SOLAR ENERGY↗
DOE OSTI2022

Using probabilistic solar power forecasts to inform flexible ramp product procurement for the California ISO

How can independent system operators (ISOs) take advantage of probabilistic solar forecasts to lower generation costs and improve reliability of power systems? We discuss one three-step approach for doing so, focusing on how such forecasts might help the California Independent System Operator (CAISO) prepare unexpected net load ramps, where net load equals gross demand minus wind and solar production. First, we enhance an existing solar forecasting system to provide well-calibrated hours-ahead probabilistic forecasts. We then relate the degree of uncertainty reflected in the forecasted prediction intervals (independent variables) to error distributions for net load ramp forecasts for the CAISO real-time market (dependent variable) using machine learning and quantile regression. Projected ramp forecast errors conditioned on solar uncertainty are translated into flexible ramp requirements that therefore reflect real-time meteorological and solar conditions, improving on typical ISO procedures. Detailed descriptions are provided on the quantile regression and kth-nearest neighbor categorization methods for accomplishing that translation. Finally, a multiple time-scale look-ahead market simulation model is applied to a 118-bus IEEE Reliability Test System, modified to represent the CAISO generation mix and demand distributions. The model runs quantify how solar-conditioned ramp requirements can, first, decrease operating costs by reducing requirements compared to often conservative unconditional methods and, second, decrease generation scarcity events and consequently improve reliability by increasing flexibility requirements at times when unconditional forecast-based requirements understate actual ramp uncertainty. Solar-conditioned ramp requirements are found to reduce generation operating costs by about 2% for the test system (which would be equivalent to over $\$100$ million per year for a CAISO-size system).

14 SOLAR ENERGY↗
DOE OSTI2020

A Data-Driven Nonparametric Approach for Probabilistic Load-Margin Assessment Considering Wind Power Penetration

A modern power system is characterized by an increasing penetration of wind power, which results in large uncertainties in its states. These uncertainties must be quantified properly; otherwise, the system security may be threatened. Facing this challenge, here we propose a cost-effective, data-driven approach to assessing a power system's load margin probabilistically. Using actual wind data, a kernel density estimator is applied to infer the nonparametric wind speed distributions, which are further merged into the framework of a vine copula. The latter enables us to simulate complex multivariate and highly dependent model inputs with a variety of bivariate copulae that precisely represent the tail dependence in the correlated samples. Furthermore, to reduce the prohibitive computational time of traditional Monte-Carlo simulations that process a large amount of samples, we propose to use a nonparametric, Gaussian-process-emulator-based reduced-order model to replace the original complicated continuation power-flow model through a Bayesian-learning framework. To accelerate the convergence rate of this Bayesian algorithm, a truncated polynomial chaos surrogate, which serves as a highly efficient, parametric Bayesian prior, is developed. This emulator allows us to execute the time-consuming continuation power-flow solver at the sampled values with a negligible computational cost. Results of simulations that are performed on several test systems reveal the impressive performance of the proposed method in the probabilistic load-margin assessment.

17 WIND ENERGY↗
DOE OSTI2021

Impacts of constraints and uncertainties on projected amount of Hanford low-activity waste glasses

A systematic evaluation of Hanford low-activity waste (LAW) loading in alkali-aluminoborosilicate glasses was performed. A set of 22 waste compositions were selected to represent the range of wastes anticipated across the Hanford mission. Glass composition was formulated for each waste to simultaneously satisfy a full cadre of property and composition constraints while maximizing waste loading. Glass properties were estimated using property models recently developed for Hanford LAW Facility operation. The impacts from the property and composition constraints on the glass mass to be produced were calculated and compared. Electrical conductivity, Vapor Hydration Test and SO 3 melter tolerance, and canister-centerline cooling crystal constraints have a large effect on reducing total glass mass, while the impact from Product Consistency Test, viscosity, and isothermal crystal constraints is relatively small. Additionally, effects of model prediction and process/composition uncertainties were quantified. The results identified areas of future research that could be useful to improve the efficiency of plant operation.

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

Stability and control of power systems with high penetrations of inverter-based resources: An accessible review of current knowledge and open questions

As power system renewable energy penetrations increase, the ways in which key renewable technologies such as wind and solar photovoltaics (PV) differ from thermal generators become more apparent. Many studies have examined the variability and uncertainty of such generators and described how generation and load can be balanced for a wide variety of annual energy penetrations, at timescales from seconds to years. Another important characteristic of these resources is asynchronicity, the result of using inverters to interface the prime energy source with the power system as opposed to synchronous generators. Unlike synchronous generators, whose frequency of alternating current (AC) injection is physically coupled to the rotation of the machine itself, inverter based asynchronous generators do not share the same physical coupling with the generated frequency. These subtle differences impact the operations of power systems developed around the characteristics of synchronous generators. In this paper we review current knowledge and open research questions concerning the interplay between asynchronous inverter-based resources (IBRs) and cycle- to second-scale power system dynamics, with a focus on how stability and control may be impacted or need to be achieved differently when there are high instantaneous penetrations of IBRs across an interconnection. This work does not seek to provide a comprehensive review of the latest developments, but is instead intended to be accessible to any reader with an engineering background and an interest in power systems and renewable energy. As such, the paper includes basic material on power electronics, control schemes for IBRs, and power system stability; and uses this background material to describe potential impacts of IBRs on power system stability, operational challenges associated with large amounts of distributed IBR generation, and modern power system simulation trends driven by IBR characteristics.

14 SOLAR ENERGY↗
DOE OSTI2020

A review on the integration of probabilistic solar forecasting in power systems

As one of the fastest growing renewable energy sources, the integration of solar power poses great challenges to power systems due to its variable and uncertain nature. As an effective approach to promote the integration of solar power in power systems, the value of probabilistic forecasts is being increasingly recognized in the recent decade. While the current use of probabilistic forecasts in power systems is limited, enormous amount of research has been conducted to promote the adoption of probabilistic forecasts and many methods have been proposed. This paper gives a comprehensive review on how probabilistic solar forecasts are utilized in power systems to address the challenges. Potential methods to deal with uncertainties in power systems are summarized, such as probabilistic load flow models, stochastic optimization, robust optimization, and chance constraints. Additionally, specific areas where these methods can be applied are discussed and state-of-the-art studies are summarized.

14 SOLAR ENERGY↗
DOE OSTI2025

Viscosity Measurements in Extreme Conditions

Radiation-hydrodynamics simulations are critical to the NNSA complex for understanding high energy density physics and for addressing problems in national security science. However, current rad-hydro codes typically do not account for viscosity, which generally leads to large uncertainties in problems involving mixing of materials under shock loading. This report details progress made towards experimental measurements of fluid viscosity at high pressures and temperatures achieved by shock wave compression techniques, as well as complementary material model development and hydrodynamic simulations.

36 MATERIALS SCIENCE↗
NASA NTRS1984

Impact of lunar and planetary missions on the space station: Preliminary STS logistics report

Space station requirements for lunar and planetary missions are discussed. Specific reference is made to projected Ceres and Kopff missions; Titan probes; Saturn and Mercury orbiters; and a Mars sample return mission. Such requirements as base design; station function; program definition; mission scenarios; uncertainties impact; launch manifest and mission schedule; and shuttle loads are considered. It is concluded that: (1) the impact of the planetary missions on the space station is not large when compared to the lunar base; (2) a quarantine module may be desirable for sample returns; (3) the Ceres and Kopff missions require the ability to stack and checkout two-stage OTVs; and (4) two to seven manweeks of on-orbit work are required of the station crew to launch a mission and, with the exception of the quarantine module, dedicated crew will not be required.

Source record↗
NASA NTRS2012

Reliability of COPVs Accounting for Margin of Safety on Design Burst

In this paper, the stress rupture reliability of Carbon/Epoxy Composite Overwrapped Pressure Vessels (COPVs) is examined utilizing the classic Phoenix model and accounting for the differences between the design and the actual burst pressure, and the liner contribution effects. Stress rupture life primarily depends upon the fiber stress ratio which is defined as the ratio of stress in fibers at the maximum expected operating pressure to actual delivered fiber strength. The actual delivered fiber strength is calculated using the actual burst pressures of vessels established through burst tests. However, during the design phase the actual burst pressure is generally not known and to estimate the reliability of the vessels calculations are usually performed based upon the design burst pressure only. Since the design burst is lower than the actual burst, this process yields a much higher value for the stress ratio and consequently a conservative estimate for the reliability. Other complications arise due to the fact that the actual burst pressure and the liner contributions have inherent variability and therefore must be treated as random variables in order to compute the stress rupture reliability. Furthermore, the model parameters, which have to be established based on stress rupture tests of subscale vessels or coupons, have significant variability as well due to limited available data and hence must be properly accounted for. In this work an assessment of reliability of COPVs including both parameter uncertainties and physical variability inherent in liner and overwrap material behavior is made and estimates are provided in terms of degree of uncertainty in the actual burst pressure and the liner load sharing.

Murthy, Pappu L.N.↗
NASA NTRS1993

Probabilistic assessment of composite structures

A general computational simulation methodology for an integrated probabilistic assessment of composite structures is discussed and demonstrated using aircraft fuselage (stiffened composite cylindrical shell) structures with rectangular cutouts. The computational simulation was performed for the probabilistic assessment of the structural behavior including buckling loads, vibration frequencies, global displacements, and local stresses. The scatter in the structural response is simulated based on the inherent uncertainties in the primitive (independent random) variables at the fiber matrix constituent, ply, laminate, and structural scales that describe the composite structures. The effect of uncertainties due to fabrication process variables such as fiber volume ratio, void volume ratio, ply orientation, and ply thickness is also included. The methodology has been embedded in the computer code IPACS (Integrated Probabilistic Assessment of Composite Structures). In addition to the simulated scatter, the IPACS code also calculates the sensitivity of the composite structural behavior to all the primitive variables that influence the structural behavior. This information is useful for assessing reliability and providing guidance for improvement. The results from the probabilistic assessment for the composite structure with rectangular cutouts indicate that the uncertainty in the longitudinal ply stress is mainly caused by the uncertainty in the laminate thickness, and the large overlap of the scatter in the first four buckling loads implies that the buckling mode shape for a specific buckling load can be either of the four modes.

Shiao, Michael E.↗
DOE OSTI2022

A Hybrid Reinforcement Learning-MPC Approach for Distribution System Critical Load Restoration

This paper proposes a hybrid control approach for distribution system critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while MPC models grid operations incorporating RL policy actions (i.e., reserve requirements), renewable (wind and solar) power predictions, and load demand forecasts. We formulate the reserve requirement determination problem as a sequential decision-making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC simulation. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The RL algorithm is trained offline using a historical forecast of renewable generation and load demand. The method is tested using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine, and battery. Case studies demonstrated that the proposed method outperforms other policies with static operating reserves.

distribution system↗
NASA NTRS2003

Probabilistic Evaluation of Advanced Ceramic Matrix Composite Structures

The objective of this report is to summarize the deterministic and probabilistic structural evaluation results of two structures made with advanced ceramic composites (CMC): internally pressurized tube and uniformly loaded flange. The deterministic structural evaluation includes stress, displacement, and buckling analyses. It is carried out using the finite element code MHOST, developed for the 3-D inelastic analysis of structures that are made with advanced materials. The probabilistic evaluation is performed using the integrated probabilistic assessment of composite structures computer code IPACS. The affects of uncertainties in primitive variables related to the material, fabrication process, and loadings on the material property and structural response behavior are quantified. The primitive variables considered are: thermo-mechanical properties of fiber and matrix, fiber and void volume ratios, use temperature, and pressure. The probabilistic structural analysis and probabilistic strength results are used by IPACS to perform reliability and risk evaluation of the two structures. The results will show that the sensitivity information obtained for the two composite structures from the computational simulation can be used to alter the design process to meet desired service requirements. In addition to detailed probabilistic analysis of the two structures, the following were performed specifically on the CMC tube: (1) predicted the failure load and the buckling load, (2) performed coupled non-deterministic multi-disciplinary structural analysis, and (3) demonstrated that probabilistic sensitivities can be used to select a reduced set of design variables for optimization.

Abumeri, Galib H.↗
DOE OSTI2021

Peak Reduction in a Residential Community Through Bayesian Optimization of Transactive Control Signals

Daily residential power consumption in aggregate tends to have a large peak that places stress on the distribution system and induces high operational costs. This work shows that coordinated transactive control of noncritical loads within a residential community or microgrid can help to alleviate peak-time stress on the distribution system by flattening the aggregate load curve. Treating the load forecaster as a high-fidelity, expensive black-box function, a new algorithm utilizing Bayesian optimization (BO) is proposed to achieve the best solution under uncertainty with minimal computing effort. The proposed BO algorithm manipulates the shape of the load based on transactive signals sent to each home. The thermostatically controlled loads (TCLs) act out of self-interest in response to the given price while maintaining comfort, and the optimizer exploits the thermal energy retention of the homes for the benefit of the community. Simulations confirm consistent neighborhood-level peak power reduction and energy cost savings.

Schomer, Ian↗
NASA NTRSDate not supplied

A Modern Load Relief Guidance Scheme for Space Launch Vehicles

Launch vehicle load relief algorithms are concerned with realizing a reduction of transient bending moments near maximum dynamic pressure. Traditional approaches to load relief typically use inner-loop acceleration feedback to reduce the wind-induced angle of attack. When implemented in the inner loop, load relief bandwidth is necessarily limited by the achievable stability margins, and when acceleration feedback is employed, by the uncertainty associated with structural modes that couple with the body-mounted accelerometer. The structure of inner loop load relief increases the dimensionality of the flight control gain and filter optimization problem. Most importantly, classical load relief laws do not take advantage of high-rate and high-accuracy GPS-aided inertial velocity data that is readily available from modern strap down IMUs. In this paper, a novel load relief guidance scheme is described that uses direct angle-of-attack feedback in a clever mechanization. The steering commands are determined by examining the wind-perturbed dynamics of a launch vehicle with respect to a gravity turn ascent trajectory. An angle of attack estimate is derived from GPS-aided inertial data and pre-launch range wind measurements, and it is shown that a reduction worst-case rigid-body loads can be realized without requiring air data. The algorithm also includes a high-rate navigation data preprocessing scheme that operates directly on the IMU delta-theta and delta-velocity measurements in order to produce a filtered acceleration estimate at the vehicle center of mass. The outer-loop guidance scheme simplifies the design process for the classical inner-loop autopilot. Algorithm performance is demonstrated using Monte Carlo analysis of a representative liquid booster in a production high fidelity launch vehicle simulation.

NESC↗
DOE OSTI2021

Cesium Batch Contact Equilibrium Testing of Crystalline Silicotitanate (CST) Sieve Cuts in SRS Average Simulant and Examination of CST Samples Aged in Caustic and Simulant in Support of Tank Closure Cesium Removal 1A (TCCR-1A)

Batch contact testing to determine cesium equilibrium loading on Crystalline Silicotitanate ion exchange media in Savannah River Site Average Waste Simulant at 25 °C indicated that smaller diameter particles isolated by sieving pretreated CST media may load slightly higher (<10%) amounts of cesium, though the differences are within analytical uncertainty. In addition, ion exchange media sub-samples stored in 2-4 M NaOH and caustic simulant solutions for ~2.5 years were examined by optical microscopy and the 3 M NaOH sample was also analyzed to determine whether changes in the particle size distribution occurred during storage. No visual indications of particle attrition or agglomeration were observed for any sample. Particle size analysis indicated that a slight decrease occurred in the average particle diameter following contact with 3 M NaOH (541 µm average diameter versus 566 µm for the pretreated CST prior to contact). A small increase (from 0 to <0.5 wt. %) in the number of particles ranging from 271 and 322 µm was also observed for the CST sample contacted with 3 M NaOH relative to a sample of the original pretreated material. However, this small change could be due to sub-sampling differences or analytical uncertainty. It does not appear that small particles are formed to a significant degree during CST caustic contact or that small particles which do form (presumably from attrition of larger particles during pretreatment) load significantly more cesium than the bulk material. Minimal other negative consequences were observed associated with CST extended caustic or simulant contact, except for the tendency for more concentrated salt solutions to form some salt crystals which deposit on the media over time.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗