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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.

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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Quantifying the Opportunity Limits of Automatic Residential Electric Load Shaping

Electric utility residential demand response programs typically reduce load a few times a year during periods of peak energy use. In the future, utilities and consumers may monetarily and environmentally benefit from continuously shaping load by alternatively encouraging or discouraging the use of electricity. One way to shape load and introduce elasticity is to broadcast forecasts of dynamic electricity prices that orchestrate electricity supply and demand in order to maximize the efficiency of conventional generation and the use of renewable resources including wind and solar energy. A binary control algorithm that influences the on and off states of end uses was developed and applied to empirical time series data to estimate price-based instantaneous opportunities for shedding and adding electric load. To overcome the limitations of traditional stochastic methods in quantifying diverse, non-Gaussian, non-stationary distributions of observed appliance behaviour, recent developments in wavelet-based analysis were applied to capture and simulate time-frequency domain behaviour. The performance of autoregressive and spectral reconstruction methods was compared, with phase reconstruction providing the best simulation ensembles. Results show spatiotemporal differences in the amount of load that can be shed and added, which suggest further investigation is warranted in estimating the benefits anticipated from the wide-scale deployment of continuous automatic residential load shaping. Empirical data and documented software code are included to assist in reproducing and extending this work.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

Short-Term Load Forecasting Error Distributions and Implications for Renewable Integration Studies: Preprint

Load forecasting in the day-ahead timescale is a critical aspect of power system operations that is used in the unit commitment process. It is also an important factor in renewable energy integration studies, where the combination of load and wind or solar forecasting techniques create the net load uncertainty that must be managed by the economic dispatch process or with suitable reserves. An understanding of that load forecasting errors that may be expected in this process can lead to better decisions about the amount of reserves necessary to compensate errors. In this work, we performed a statistical analysis of the day-ahead (and two-day-ahead) load forecasting errors observed in two independent system operators for a one-year period. Comparisons were made with the normal distribution commonly assumed in power system operation simulations used for renewable power integration studies. Further analysis identified time periods when the load is more likely to be under- or overforecast.

17 WIND ENERGY↗
DOE OSTI2015

MC2-3 / DIF3D Analysis for the ZPPR-15 Doppler and Sodium Void Worth Measurements

This manuscript covers validation efforts for our deterministic codes at Argonne National Laboratory. The experimental results come from the ZPPR-15 work in 1985-1986 which was focused on the accuracy of physics data for the integral fast reactor concept. Results for six loadings are studied in this document and focus on Doppler sample worths and sodium void worths. The ZPPR-15 loadings are modeled using the MC2-3/DIF3D codes developed and maintained at ANL and the MCNP code from LANL. The deterministic models are generated by processing the as-built geometry information, i.e. MCNP input, and generating MC2-3 cross section generation instructions and a drawer homogenized equivalence problem. The Doppler reactivity worth measurements are small heated samples which insert very small amounts of reactivity into the system (< 2 pcm). The results generated by the MC2-3/DIF3D codes were excellent for ZPPR-15A and ZPPR-15B and good for ZPPR-15D, compared to the MCNP solutions. In all cases, notable improvements were made over the analysis techniques applied to the same problems in 1987. The sodium void worths from MC2-3/DIF3D were quite good at 37.5 pcm while MCNP result was 33 pcm and the measured result was 31.5 pcm. Copyright © (2015) by the American Nuclear Society All rights reserved.

Smith, Micheal A.↗
DOE OSTI2017

Aeroelastic oscillations of a cantilever with structural nonlinearities: theory and numerical simulation.

Our study details the derivation of the nonlinear equations of motion for the axial, biaxial bending and torsional vibrations of an aeroelastic cantilever undergoing rigid body (pitch) rotation at the base. The primary attenstion is focussed on the geometric nonlinearities of the system, whereby the aeroelastic load is modeled by the theory of linear quasisteady aerodynamics. This modelling effort is intended to mimic the wind-tunnel experimental setup at the Royal Military College of Canada. While the derivation closely follows the work of Hodges and Dowell [1] for rotor blades, this aeroelastic system contains new inertial terms which stem from the fundamentally different kinematics than those exhibited by helicopter or wind turbine blades. Using the Hamilton’s principle, a set of coupled nonlinear partial differential equations (PDEs) and an ordinary differential equation (ODE) are derived which describes the coupled axial-bending-bending-torsion-pitch motion of the aeroelastic cantilever with the pitch rotation. The finite dimensional approximation of the coupled system of PDEs are obtained using the Galerkin projection, leading to a coupled system of ODEs. Subsequently, these nonlinear ODEs are solved numerically using the built-in MATLAB implicit ODE solver and the associated numerical results are compared with those obtained using Houbolt’s method. It is demonstrated that the system undergoes coalescence flutter, leading to a limit cycle oscillation (LCO) due to coupling between the rigid body pitching mode and teh flexible mode arising from the flapwise bending motion.

42 ENGINEERING↗
DOE OSTI2019

NONLINEAR SOIL-STRUCTURE INTERACTION ANALYSIS USING CO-SIMULATION

Nonlinear soil-structure interaction (NLSSI) analysis methods are currently being developed at Idaho National Laboratory. Appendix B in ASCE (2016) includes a framework for performing NLSSI analysis. For NLSSI analysis to be widely implemented in industry, it is important to demonstrate that accurate response in dynamically loaded, nonlinear models can be achieved in an efficient manner. Both explicit and implicit dynamic solvers are applicable to NLSSI. When considering cpu time, an explicit dynamic solver is often desirable for large models with no features (e.g. small elements, stiff elements, or stiffness damping) that can drive the time step unreasonably small. An implicit dynamic solver may be desirable in models not well suited for an explicit solver. A further option is co-simulation where a portion of the model is run with an explicit dynamic solver and the rest of the model is run with an implicit dynamic solver. This study explores NLSSI examples where co-simulation could be the most cpu efficient modelling strategy.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Empirical Assessment of the Appliance-Level Load Shape and Demand Response Potential in India

Over the next 15 years, electricity demand from the key residential and commercial appliances is projected to be nearly 300 GW or ~65% of India’s total peak demand. The objective of this study is to characterize appliance level demand and temporal variation, and identify the overall DR potential in India. We use Bangalore Electricity Supply Company territory (peak load of 3,505 MW in 2016) as a case study, using actual one-minute resolution load data for 2,979 distribution feeders and a detailed load survey. Our results show that agricultural pumping and space cooling (residential, commercial, and industrial) are the main contributors to the peak demand – with shares of 23-27% and 14-23%, respectively. Both sectors have about 1,000 MW of DR potential – agricultural pumps offering load shifting service while space cooling offering shimmy service that is capable of dynamically adjusting to react to short-run ramps and grid disturbances. Residential electric water heaters contribute nearly 18% of the winter morning peak demand and can also offer about 500 MW in shimmy service. Overall, we find that shifting and shimmy services offer 1,199 MW and 1,511 MW total DR potential, respectively.

demand response↗
DOE OSTI2024

From RNNs to Foundation Models: An Empirical Study on Commercial Building Energy Consumption

Accurate short-term energy consumption forecasting for commercial buildings is crucial for smart grid operations. While smart meters and deep learning models enable forecasting using past data from multiple buildings, data heterogeneity from diverse buildings can reduce model performance. The impact of increasing dataset heterogeneity in time series forecasting, while keeping size and model constant, is understudied. We tackle this issue using the ComStock dataset, which provides synthetic energy consumption data for U.S. commercial buildings. Two curated subsets, identical in size and region but differing in building type diversity, are used to assess the performance of various time series forecasting models, including finetuned open-source foundation models (FMs). The results show that dataset heterogeneity and model architecture have a greater impact on post-training forecasting performance than the parameter count. Moreover, despite the higher computational cost, finetuned FMs demonstrate competitive performance compared to base models trained from scratch.

commercial buildings↗
DOE OSTI2014

Physics based model for online fault detection in autonomous cryogenic loading system

We report the progress in the development of the chilldown model for a rapid cryogenic loading system developed at NASA-Kennedy Space Center. The nontrivial characteristic feature of the analyzed chilldown regime is its active control by dump valves. The two-phase flow model of the chilldown is approximated as one-dimensional homogeneous fluid flow with no slip condition for the interphase velocity. The model is built using commercial SINDA/FLUINT software. The results of numerical predictions are in good agreement with the experimental time traces. The obtained results pave the way to the application of the SINDA/FLUINT model as a verification tool for the design and algorithm development required for autonomous loading operation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Modeling Workloads of a Linear Electromagnetic Code for Load Balancing Matrix Assembly

This report presents our work to model the workloads of a linear electromagnetic application based on the method of moments in the frequency domain to effectively load balance the matrix assembly. This application is particularly challenging to load balance due to its lack of persistent iterative behavior, its operation under tight memory constraint (where the matrix may fill 80% of memory on each node), and the algorithmic complexity of the computational method. This report describes the first step in our work to apply an inspector-executor approach for load balancing workloads where key parameters are exposed during the inspector phase and a pre-trained model is applied to predict relative task weights for the load balancer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Empirical Investigations of the Opportunity Limits of Automatic Residential Electric Load Shaping

Residential electric load shaping is often modeled as infrequent, utility-initiated, short-duration deferral of peak demand through direct load control. In contrast, modeled herein is the potential for frequent, transactive, intraday, consumer-configurable load shaping for storage-capable thermostatically controlled electric loads (TCLs), including refrigerators, freezers, and hot water heaters. Unique to this study are 28 months of 15-minute-interval observations of usage in 101 homes in the Pacific Northwest United States that specify exact start, duration, and usage patterns of approximately 25 submetered loads per home. The magnitudes of the load shift from voluntarily-participating TCL appliances are aggregated to form hourly upper and lower load-shaping limits for the coordination of electrical generation, transmission, distribution, storage, and demand. Empirical data are statistically analyzed to define metrics that help quantify load-shaping opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Hybrid-RL-MPC4CLR (Hybird-Reinforcement-Learning-Model-Predictive-Control-for-Reserve-Policy-Assisted-Critical-Load-Restoration-in-Distribution-Grids)

Hybrid-RL-MPC4CLR was developed as a hybrid controller for active distribution grid critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. The RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while the MPC models grid operations incorporating the RL policy actions (i.e., reserve requirements), renewable (wind and solar) power predictions, and load demand forecasts. The developers formulated 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 software is developed using various software packages in Python. The MPC's optimal power flow (OPF) model is implemented using the Pyomo package, the RL simulation environment is implemented using the MPC simulation with various scenarios of renewable energy and load demand profiles and power outage beginning times, based on the OpenAI Gym framework. The RL agent training is performed using the RLlib Ray package. The RL algorithm is trained offline using historical forecasts of renewable generation and load demand profiles. Simulation analysis and performance tests are conducted using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine, and battery.

Eseye, Abinet Tesfaye↗
DOE OSTI2025

ComStock Measure Documentation: Ideal Thermal Air Loads

This study provides hypothetical thermal heating and cooling loads for ComStock models representing the U.S. commercial building stock. This measure scenario removes all HVAC models from the baseline ComStock building model and instead uses "ideal air" to meet loads. "Ideal air" can be thought of as an HVAC unit that mixes air at the zone exhaust condition with the specified amount of outdoor air, and then adds or removes heat and moisture at 100% efficiency to produce a supply air stream at the specified conditions. The resulting ideal thermal loads are represented under the "district" fuel type for both heating and cooling and can be found in both annual and timeseries results in the ComStock public dataset. This measure scenario does not represent any real technology or improvement, but rather, serves as a resource for thermal heating and cooling loads for buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

A Model to Account for the Effects of Load Ratio and Hydrogen Pressure on the Fatigue Crack Growth Behavior of Pressure Vessel Steels

A phenomenological model for estimating the effects of load ratio R and hydrogen pressure P H2 on the hydrogen-assisted fatigue crack growth rate (HA–FCGR) behavior in the transient and steady-state regimes of pressure vessel steels is described. The “transient regime” is identified with crack growth within a severely embrittled zone of intense plasticity at the crack tip. The “steady-state” behavior is associated with the crack growing into a region of comparatively lower hydrogen concentration located further away from the crack tip. The model treats the effects of R and P H2 as being functionally separable. In the transient regime, the effects of the hydrogen pressure on the HA–FCGR behavior were negligible but were significant in the steady-state regime. The hydrogen concentration in the steady-state region is modeled as being dependent on the kinetics of lattice diffusion, which is sensitive to pressure. Experimental HA–FCGR data from the literature were used to validate the model. The new model was shown to be valid over a wide range of conditions that ranged between –1 ≤ R ≤ 0.8 and 0.02 ≤ P H2 ≤ 103 MPa for pressure vessel steels.

36 MATERIALS SCIENCE↗