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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Emerging Technologies for Improved Plug Load Management Systems: Learning Behavior Algorithms and Automatic and Dynamic Load Detection

Plug loads are responsible for a significant portion of the energy consumed in commercial buildings, yet their distributed and ever-changing nature makes them one of the most challenging building end uses to manage. Plug load management systems exist today that utilize smart plugs to meter and control devices at the outlet level, however, their uptake has been relatively slow in part due to the significant labor required for installation and maintenance. Learning behavior algorithms and automatic and dynamic load detection have been identified as two technology areas that could accelerate the adoption of plug load management systems by reducing these labor demands and providing additional energy efficiency and non-energy benefits. Learning behavior algorithms learn occupant behavior and adjust plug load management systems accordingly, allowing for the automatic creation of optimized control schedules. Automatic and dynamic load detection allows a plug load management system to identify devices as they are plugged in to a building and keeps the system up to date as devices are moved throughout a building. In this paper, we present our findings with respect to the current state of these two technologies based on a review of existing research and patents, as well as a series of interviews with companies working in the plug load space. We have found that, as of now, no commercialized solutions exist for these plug load technologies and that more work is needed to bring them to market. In addition, we summarize our findings related to the technology challenges, market barriers, drivers, and opportunities for these technologies moving forward.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2018

A Deterministic and Probabilistic Framework for Forecasting of Time-Series Damage States and Associated End-of-lIfe of a Pressurizer Water Reactor Surge Line under Design-Basis and Grid-Load-Following Loading Conditions

Argonne National Laboratory in support of the Department of Energy’s Light Water Reactor Sustainability (LWRS) program. The present semi-annual report covers the period between May 2018 and September 2018. In this report, we present the work performed to further improve the capability for structural integrity prediction. Part of this work focused on validating a computational fluid dynamics model for modeling thermal stratification. We also present finite element (FE) model based thermal-mechanical stress analysis of a pressurized water reactor (PWR) surge line under grid-load-following loading condition. In addition, we present work related to end-of-life prediction of a PWR surge line based on ASME code and NUREG-6909 deterministic approaches under design-basis and grid-load-following conditions. Our research in this report period also majorly involved with the development of a strategy for probabilistic fatigue life estimation. First, we applied a Weibull probabilistic modeling approach based on end-of-life fatigue data (traditional S~N data under in-air and PWR water conditions) to estimate the probabilistic life for a given strain amplitude. Second, we developed a data analytics based Markov-Chain-Monte-Carlo (MCMC) model for probabilistic modeling of time-series fatigue damage states and the associated probabilistic end-of-life of a component. Unlike the Weibull type approach, the MCMC type may not require a large number of fatigue tests for estimating the end-of-life for given loading and environmental conditions. We demonstrated the use of this framework through symmetric fatigue tests (stress- or strain-ontrolled tests either under in-air or PWR-water conditions) obtained from our earlier experiments. The MCMC model can use base time-series data either obtained from a model or fatigue experiment. Since experimental data are typically more accurate than model-calculated data, we used experiment-based time-series data to demonstrate the MCMC framework. However, when performing a complex experiment is not possible (due to time and costs involved), a model-based approach can be used to generate the time-series data. Similar model-based data are presented in our earlier report (e.g. for cyclic hardening damage states of a PWR surge line under constant amplitude and design-basis loading [1]). However, for the MCMC work in this report, we used experiment-based time-series damage states obtained from fatigue experiments under design-basis and grid-load-following loading conditions. The experimental loading inputs were based on thermal-mechanical FE model results of a typical PWR surge line. Then, we used the experimental time-series damage state data for forecasting the probabilistic time-series damage states and end-of-life of the PWR surge line. Based on this MCMC modeling strategy, and with the assumed loading, environment and thermal-mechanical boundary conditions, we have estimated that a 316SS-pure base metal PWR surge line would survive at least 159 years with zero failure probability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1954

Determination of mean camber surfaces for wings having uniform chordwise loading and arbitrary spanwise loading in subsonic flow

The field of a uniformly loaded wing in subsonic flow is discussed in terms of the acceleration potential. It is shown that, for the design of such wings, the slope of the mean camber surface at any point can be determined by a line integration around the wing boundary. By an additional line integration around the wing boundary, this method is extended to include the case where the local section lift coefficient varies with spanwise location (the chordwise loading at every section still remaining uniform). For the uniformly loaded wing of polygonal plan form, the integrations necessary to determine the local slope of the surface and the further integration of the slopes to determine the ordinate can be done analytically. An outline of these integrations and the resulting formulas are included. Calculated results are given for a sweptback wing with uniform chordwise loading and a highly tapered spanwise loading, a uniformly loaded delta wing, a uniformly loaded sweptback wing, and the same sweptback wing with uniform chordwise loading but elliptical span load distribution.

Katzoff, S↗
NASA NTRS1959

The Effect of Beam Loading on Water Impact Loads and Motions

An investigation of the effect of beam loading on impact loads and motions has been conducted in the Langley impact basin. Water impact tests of flat-bottom 5-inch-and 8-inch-beam models having beam-loading coefficients C(sub Delta) from 62.5 to 544 and a 30 deg dead-rise 5-inch-beam model A having beam-loading coefficients from 208 to 530 are described and the results analyzed to show trends of these heavy-beam-loading data with initial flight-path angle, trim angle, dead-rise angle, and time through- out the impact. Data from flat-bottom model tests, C(sub Delta) = 4.4 to 36.5, and from 30 deg dead-rise model tests, C(sub Delta) = 0.58 and 18.8, are included, along with the heavy-beam-loading data; and variations of these data with beam-loading coefficients are shown. Each of the load and motion coefficients is found to be directly proportional to a power factor of C(sub Delta). For instance, the maximum impact lift coefficient is found C(sub L,max) to be directly proportional to C(sub Delta, exp 0,33) for the flat-bottom model and C(sub Delta, exp 0,45) for the 30 deg dead-rise model. These variations of C(sub L, max) with C(sub Delta) are found to be in agreement with theoretical variations. Finally, an empirical equation for the prediction of C(sub L,max) is presented and is shown to give good agreement with experimental C(sub L, max) for about 500 fixed-trim smooth-water impacts. The range of variables included dead-rise angles from 0 deg to deg, beam-loading coefficients from o.48 to 544, trim angles from 3 deg to deg, and initial flight-path angles from about 2 deg to about deg.

Mixson, John S.↗
NASA NTRS1959

The Effect of Beam Loading on Water Impact Loads and Motions

An investigation of the effect of beam loading on impact loads and motions has been conducted in the Langley impact basin. Water impact tests of flat-bottom 5-inch- and 8-inch-beam models having beam-loading coefficients C(sub Delta) from 62.5 to 544 and a 30 0 dead-rise 5-inch-beam model A having beam-loading coefficients from 208 to 530 are described and the results analyzed to show trends of these heavy-beam-loading data with initial flight-path angle, trim angle, dead-rise angle, and time throughout the impact. Data from flat-bottom model tests, C(sub Delta) = 4.4 to 36.5, and from 300 dead-rise model tests, C(sub Delta)A = 0.58 and 18.8, are included, along with the heavy-beam-loading data; and variations of these data with beam-loading coefficients are shown. Each of the load and motion coefficients is found to be directly proportional to a power factor ofC(sub Delta). For instance, the maximum impact lift coefficient C(sub L,max)is found to be directly proportional to C(sub Delta)(sup 0.33) for the flat-bottom model and C(sub Delta)(sup 0.45) for the 30 deg dead-rise model. These variations of C(sub L,max) C(sub Delta) are found to be in agreement with theoretical variations. Finally, an empirical equation for the prediction of C(sub L,max) is presented and is shown to give good agreement with experimental C(sub L,max) for about 500 fixed-trim smooth-water impacts. The range of variables included dead-rise angles from 0 deg to 30 deg, beam-loading coefficients from 0.48 to 544, trim angles from 3 deg to 45 deg and initial flight-path angles from about 2 deg to about 27 deg.

Mixson, John S.↗
NASA NTRS2003

Single Vector Calibration System for Multi-Axis Load Cells and Method for Calibrating a Multi-Axis Load Cell

A single vector calibration system is provided which facilitates the calibration of multi-axis load cells, including wind tunnel force balances. The single vector system provides the capability to calibrate a multi-axis load cell using a single directional load, for example loading solely in the gravitational direction. The system manipulates the load cell in three-dimensional space, while keeping the uni-directional calibration load aligned. The use of a single vector calibration load reduces the set-up time for the multi-axis load combinations needed to generate a complete calibration mathematical model. The system also reduces load application inaccuracies caused by the conventional requirement to generate multiple force vectors. The simplicity of the system reduces calibration time and cost, while simultaneously increasing calibration accuracy.

Parker, Peter A.↗
DOE OSTI2016

Method and system employing graphical electric load categorization to identify one of a plurality of different electric load types

A system for different electric loads includes sensors structured to sense voltage and current signals for each of the different electric loads; a hierarchical load feature database having a plurality of layers, with one of the layers including a plurality of different load categories; and a processor. The processor acquires voltage and current waveforms from the sensors for a corresponding one of the different electric loads; maps a voltage-current trajectory to a grid including a plurality of cells, each of which is assigned a binary value of zero or one; extracts a plurality of different features from the mapped grid of cells as a graphical signature of the corresponding one of the different electric loads; derives a category of the corresponding one of the different electric loads from the database; and identifies one of a plurality of different electric load types for the corresponding one of the different electric loads.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Online Static Load Model Estimation in Distribution Systems: Preprint

The paper focuses on parameter identification for time varying voltage dependent polynomial load models, namely the constant impedance (Z), constant current (I), and constant power (P), in the distribution systems. Typically, parameter identification has been done for aggregated loads at substations for the transmission planning studies. Given the higher voltage volatility faced by active distribution systems, this paper takes the load model estimation to the distribution networks. The paper assumes the presence of measurements at the distribution nodes from various sources, each at varying temporal resolutions. Least squares estimation (LSE) method with bounded variables is used to convert the measurements into ZIP parameter estimations for loads at various locations of the feeder. The results and discussions focus on some of the estimation issues faced in a distribution system due to varying voltage sensitivities of loads along a feeder, measurement resolution, impact of window size and sampling rate of measurement data, and the use of dynamic simulations to create synthetic measurement data in the absence of real ones.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Consensus Weighting of a Multi-Agent System for Load Shedding

An agent-based scheme is proposed for distributed underfrequency load shedding (UFLS). The key concept is a consensus weighting protocol (CWP) for agents to reach an agreement. Unlike the well adopted average-consensus protocol (ACP), the proposed CWP enables each agent to converge to its weighted portion of the sum of all initial values. Thus, the proposed CWP is more suitable for the UFLS application, as it allows load buses with a higher level of loading to shed more, rather than reducing by the same average value over all load buses as required by the ACP. Proof of convergence for the proposed CWP is derived and presented in this paper, together with the constraints. For implementation of the multi-agent system (MAS), the monitoring, estimation, and distribution steps are developed. Two study cases and the simulation results are provided to validate the performance of the proposed agent-based UFLS scheme.

Xie, Jing↗
DOE OSTI2020

COHORT: Coordination of Heterogeneous Thermostatically Controlled Loads for Demand Flexibility

Demand flexibility is increasingly important for power grids. Careful coordination of thermostatically controlled loads (TCLs) can modulate energy demand, decrease operating costs, and increase grid resiliency. We propose a novel distributed control framework for the Coordination Of HeterOgeneous Residential Thermostatically controlled loads (COHORT). COHORT is a practical, scalable, and versatile solution that coordinates a population of TCLs to jointly optimize a grid-level objective, while satisfying each TCL’s end-use requirements and operational constraints. To achieve that, we decompose the grid-scale problem into subproblems and coordi- nate their solutions to find the global optimum using the alternating direction method of multipliers (ADMM). The TCLs’ local problems are distributed to and computed in parallel at each TCL, making COHORT highly scalable and privacy-preserving. While each TCL poses combinatorial and non-convex constraints, we characterize these constraints as a convex set through relaxation, thereby making COHORT computationally viable over long planning horizons. After coordination, each TCL is responsible for its own control and tracks the agreed-upon power trajectory with its preferred strategy. In this work, we translate continuous power back to discrete on/off actuation, using pulse width modulation. COHORT is generalizable to a wide range of grid objectives, which we demonstrate through three distinct use cases: generation following, minimizing ramping, and peak load curtailment. In a notable experiment, we validated our approach through a hardware-in-the-loop simulation, including a real-world air conditioner (AC) controlled via a smart thermostat, and simulated instances of ACs modeled after real-world data traces. During the 15-day experimental period, COHORT reduced daily peak loads by an average of 12.5% and maintained comfortable temperatures.

demand response↗
DOE OSTI2020

A Nonlinear Regression Method for Composite Protection Modeling of Induction Motor Loads

Protection equipment are used to prevent damages to induction motor loads by isolating those from the power network in the event of severe faults. Modeling the response of induction motor loads and their protection is vital for power system planning and operation, especially in understanding system's response moments after a fault has occurred. This article proposes an optimization based framework to generate composite protection models for commercial building motor loads. Introducing a mathematical abstraction, the task of finding a suitable (simplified) model of the composite protection scheme is formulated as a nonlinear regression problem. Numerical examples are provided to illustrate the application of the framework.

Kundu, Soumya↗
DOE OSTI2023

Solving Unit Commitment Problems with Demand Responsive Loads

This work focuses on using variations of the Frank-Wolfe (FW) algorithm for solving unit commitment problems with high volumes of demand responsive loads on the power grid. We present a formulation of the unit commitment problem with demand responsive loads. We then show through reformulation and relaxations of the problem that variations of the Frank-Wolfe algorithm can be used to determine the time series decisions for the demand responsive loads. We show through computational experiments on the IEEE Reliability Test System that the timeseries of demand responsive load decisions obtained through our approach are near optimal and describe how large-scale parallel implementations of our approach can be highly computationally efficient.

demand response↗
DOE OSTI2018

Correlation between EVs and Other Loads in Probabilistic Load Flow for Distribution Systems

To date, most probabilistic studies have assumed independence between the various loads and other inputs on the distribution system. It is well know however, that this is typically not the case. The work presented in the paper expands upon a previous unbalanced three-phase probabilistic load flow study on a residential feeder with a 50 % penetration of electric vehicles, under three different charging schemes where different correlation scenarios between the load flow inputs are considered. The data for the probabilistic load flow study are derived from a voltage dependent time-variant deterministic load flow. Here the deterministic load flow data are examined further to gain a better understanding of the correlation between the customer and electric vehicle charging loads, and how different charging schemes may impact it further. Four different correlation scenarios are then created and details on how the probabilistic load flow inputs are created is also presented; demonstrating the need for better analysis on the correlation between system inputs. This paper hopes to open the discussion and start the push for future research into understanding the correlation and effects of various system inputs on the probabilistic nature of distribution systems, and how to apply this knowledge to future studies.

Melhorn, Alexander C.↗
DOE OSTI2018

Optimal Coordination of Building Loads and Energy Storage for Power Grid and End User Services

Demand response and energy storage play a profound role in the smart grid. The focus of this paper is to evaluate benefits of coordination of flexible loads and energy storage for power grid and end user services. We present a Generalized Battery Model (GBM) to describe the flexibility of building loads and energy storage. A Model Predictive Control (MPC) approach is proposed to characterize the GBM parameters (power and energy limits) for flexible building loads. Moreover, we develop optimal coordination algorithms for them to provide ancillary and end user services such as energy arbitrage, frequency regulation, spinning reserve, as well as energy and demand charge reduction. Several case studies have been performed to demonstrate the efficacy of the GBM and coordination algorithms, and evaluate the benefits of using their flexibility to provide grid and end user services. We show that optimal coordination yields significant cost saving and revenue. Moreover, the best option for grid services is to provide energy arbitrage and frequency regulation, because spinning reserve cannot compete with regulation service. Furthermore, when coordinating flexible loads with energy storage to provide end user services, it is recommended to consider both the time-of-use (TOU) price and demand charge rather than the TOU price only in order to flat the aggregate power profile.

Hao, He↗
DOE OSTI2016

Use of Adaptive Injection Strategies to Increase the Full Load Limit of RCCI Operation

Dual-fuel combustion using port-injection of low reactivity fuel combined with direct injection (DI) of a higher reactivity fuel, otherwise known as reactivity controlled compression ignition (RCCI), has been shown as a method to achieve low-temperature combustion with moderate peak pressure rise rates, low engine-out soot and NO x emissions, and high indicated thermal efficiency. A key requirement for extending to high-load operation is moderating the reactivity of the premixed charge prior to the diesel injection. One way to accomplish this is to use a very low reactivity fuel such as natural gas. In this work, experimental testing was conducted on a 13 l multicylinder heavy-duty diesel engine modified to operate using RCCI combustion with port injection of natural gas and DI of diesel fuel. Engine testing was conducted at an engine speed of 1200 rpm over a wide variety of loads and injection conditions. The impact on dual-fuel engine performance and emissions with respect to varying the fuel injection parameters is quantified within this study. The injection strategies used in the work were found to affect the combustion process in similar ways to both conventional diesel combustion (CDC) and RCCI combustion for phasing control and emissions performance. As the load is increased, the port fuel injection (PFI) quantity was reduced to keep peak cylinder pressure (PCP) and maximum pressure rise rate (MPRR) under the imposed limits. Overall, the peak load using the new injection strategy was shown to reach 22 bar brake mean effective pressure (BMEP) with a peak brake thermal efficiency (BTE) of 47.6%.

Hanson, Reed↗
DOE OSTI2016

Balancing Power Absorption and Fatigue Loads in Irregular Waves for an Oscillating Surge Wave Energy Converter

The aim of this paper is to describe how to control the power-to-load ratio of a novel wave energy converter (WEC) in irregular waves. The novel WEC that is being developed at the National Renewable Energy Laboratory combines an oscillating surge wave energy converter (OSWEC) with control surfaces as part of the structure; however, this work only considers one fixed geometric configuration. This work extends the optimal control problem so as to not solely maximize the time-averaged power, but to also consider the power-take-off (PTO) torque and foundation forces that arise because of WEC motion. The objective function of the controller will include competing terms that force the controller to balance power capture with structural loading. Separate penalty weights were placed on the surge-foundation force and PTO torque magnitude, which allows the controller to be tuned to emphasize either power absorption or load shedding. Results of this study found that, with proper selection of penalty weights, gains in time-averaged power would exceed the gains in structural loading while minimizing the reactive power requirement.

16 TIDAL AND WAVE POWER↗
NASA NTRS1977

A study of the effect of radical load distributions on calibrated strain gage load equations

For several decades, calibrated strain gages have been used to measure loads on airplanes. The accuracy of the equations used to relate the strain gage measurements to the applied loads has been based primarily on the results of the load calibration. An approach is presented for studying the effect of widely varying load distributions on strain gage load equations. The computational procedure provides a link between the load calibration and the load to be measured in flight. A matrix approach to equation selection is presented, which is based on equation standard error, load distribution, and influence coefficient plots of the strain gage equations, and is applied to a complex, delta-wing structure.

Jenkins, J. M.↗
NASA NTRS1985

Composite Loads Spectra for Select Space Propulsion Structural Components: Probabilistic Load Model Development

This effort is in support of the development of the expert system of computer codes to predict the loads on select structural components of a space propulsion engine. The development will be based primarily on the space shuttle main engine (SSME) test data base. Because of random variations of the many different sources of the loadings on the selected structural components and transients, a probabilistic approach to the problems was adopted. The goal of this task is to characterize all of the individual sources of loads at critical structural locations, such as the turbine blades, the transfer ducts, and liquid oxygen posts, using state-of-the-art probabilistic methods with varying levels of sophistication. The second phase of this work is the development of a composite load model based on a probabilistic synthesis of the individual load model previously developed. This model will be based on the stochastic combination of the load variables and not on the physical process for the combination of the individual loads to the composite load seen by the selected structural components.

Kurth, R.↗