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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Off-Design Load Analysis of sCO2 Bottoming Cycle for a Natural Gas Combined Cycle Power Plant with Carbon Capture

As an alternative to a steam cycle, a supercritical carbon dioxide (sCO2) power cycle can be considered. Able et. al performed an analysis of an sCO2 cycle in a 2x2-1 configuration; however, this study did not include carbon capture. Previous studies assumed an H-Frame turbine and added a solvent based 95% carbon capture system and performed a levelized cost of electricity (LCOE) optimization for the plant. Their results suggest a LCOE slightly better than when using a steam cycle. In the study, steam is still generated in the heat recovery sections for the solvent regeneration in the carbon capture stripper reboiler. H-Frame gas turbines are also assumed. This work starts with the optimal design from the mentioned work to analyze the off-design performance of the power plant from 100% down to 50% load. The main operational findings and plant-efficiency for off-load conditions while maintaining the target CO2 capture rate are presented. H-Frame gas turbine off-design performance and exhaust conditions to the heat recovery section are obtained from commercial software, Thermoflow®. The CO2 turbomachinery, heat exchangers and other unit operations are sized and implemented in an Aspen Plus® model. Using the gas turbine exhaust conditions as input, the sCO2 cycle is optimized by adjusting stream split ratios, sCO2 circulation flowrate and compressor speed for maximum efficiency. This is done while keeping the target 95% CO2 capture.

Chinen, Anderson Soares↗
DOE OSTI2021

Thermal loading analysis of the ring injection dump for the Spallation Neutron Source facility

The ring injection dump (RID) is the largest beam dump in the Spallation Neutron Source facility at Oak Ridge National Laboratory and accepts a fraction of the beam from the ring that is not captured in the ring during injection. Thermo-fluid modeling of the RID components was performed during the initial design by using the software ANSYS CFX to characterize the power rating for the RID. From the calculations, the power rating was lowered from 200 kW to 150 kW, at 1.3 GeV beam energy due to concerns regarding the heating of the concrete structure. The Proton Power Upgrade project scope included reevaluating the power limit to the RID in anticipation that increasing it would provide more operational flexibility. The focus was on the shielding because it was the limiting factor, and data collected from thermocouples installed on the structure were used to benchmark the analysis. A three-stage process was adopted in the latest study. First, the already existing steady-state calculations were validated and extended with the latest Monte Carlo N-Particle source term calculations. Second, transient calculations were conducted to capture the dynamic state of the system in response to the energy dumped to the RID during the following operational period of the beam from 2005–2019 (14 years), and sensitivity analyses of crucial parameters were performed to benchmark the model with reasonable accuracy. Finally, an idealized transient cycle analysis was conducted with realistic duty factors to predict the temperature distribution at higher beam powers. Overall, the results confirmed the accuracy of the original steady state model but allowed the development of a new validated transient model with higher accuracy for future analyses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Streamlined Loads Analysis of Floating Wind Turbines With Fiber Rope Mooring Lines

This paper presents an approach for more accurate yet relatively streamlined accounting for the nonlinear characteristics of synthetic fiber rope mooring lines for floating wind turbines. First, we select a minimal set of parameters that can efficiently approximate a mooring line material's quasi-static and dynamic stiffness characteristics. We also develop a set of baseline coefficients for different rope materials based on published product information and research papers. We then expand a quasi-static mooring model to include dynamic mooring line stiffness terms in a way that allows the nonlinear stiffness behavior of fiber ropes to be considered even in quasi-static analyses. For dynamic analysis, we have updated the model MoorDyn, coupled with OpenFAST, to work with the new dynamic mooring line stiffness terms. This includes the implementation of a new viscoelastic approach that allows the tension-strain relation of each mooring line segment to vary between two stiffness values, depending on the strain rate. After presenting the formulation of the approaches for modeling synthetic ropes, they are demonstrated on a floating wind turbine mooring system with taut polyester rope mooring lines. The results are compared with those of other approaches of similar fidelity, including the static-dynamic method and separate simulations with static and dynamic stiffness values. Comparing the results shows the ability of the new method to match the results of the previous methods in a more streamlined manner.

elasticity↗
DOE OSTI2017

SWiFT V27 Wake Steering Loads Analysis

This document summarizes an analysis that was performed to identify the conditions for safe operation of the SWiFT V27 rotors during the FY16/17 wake steering experimental campaign.

17 WIND ENERGY↗
DOE OSTI2024

Streamlined Loads Analysis of Floating Wind Turbines With Fiber Rope Mooring Lines: Preprint

This paper presents an approach for more accurate yet relatively streamlined accounting for the nonlinear characteristics of synthetic fiber rope mooring lines for floating wind turbines. First, we select a minimal set of parameters that can efficiently approximate a mooring line material's quasi-static and dynamic stiffness characteristics. We also develop a set of baseline coefficients for different rope materials based on published product information and research papers. We then expand a quasi-static mooring model to include dynamic mooring line stiffness terms in a way that allows the nonlinear stiffness behavior of fiber ropes to be considered even in quasi-static analyses. For dynamic analysis, we have updated the model MoorDyn, coupled with OpenFAST, to work with the new dynamic mooring line stiffness terms. This includes the implementation of a new viscoelastic approach that allows the tension-strain relation of each mooring line segment to vary between two stiffness values depending on the strain rate. After presenting the formulation of the approaches for modeling synthetic ropes, they are demonstrated on a floating wind turbine mooring system with taut polyester rope mooring lines. The results are compared with those of other approaches of similar fidelity including the static-dynamic method and separate simulations with static and dynamic stiffness values. Comparing the results shows the ability of the new method to match the results of the previous methods in a more streamlined manner.

elasticity↗
DOE OSTI2020

Load Composition Analysis in Support of the NERC Load Modeling Task Force. 2019-2020 Field Test of the Composite Load Model

In 2015, NERC’s reliability standards were revised to require the use of dynamic load models in transmission planning studies. To comply with the standards, planners must use load models that explicitly represent the dynamic behavior of the different constituents of load at each load bus within their transmission planning models. The most important of these constituents are motor-driven and power electronics-based loads. Collectively, these representations are known as composite load models. In anticipation of the compliance date for the new standards, NERC’s Load Modeling Task Force (LMTF), in 2019, initiated a field test of composite load models involving the regional reliability planning entities. In support of the field test, DOE and BPA researchers developed region-specific composite load models that could be assigned to each non-industrial load bus in the planning models for each of the North American interconnections. Separate models were developed for each hour of a summer peak day, a winter peak day, and a spring light-load day. This report is the technical documentation for the load composition analysis that was conducted to develop these non-industrial composite load models.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Revised Heating Load Line Analysis: Addendum to ORNL/TM-2015/281

The original heating load line analysis of ORNL TM-2015/281 was modified to incorporate two adjustments of (1) removing mechanical ventilation and (2) resizing the heat pump units based on new criteria. This resulted in a lowering of the HLL slope factor from the originally rounded 1.3 level to 1.15 in DOE Region IV and V while leaving unchanged the zero-load ambient at a rounded value of 55 F. For the other four DOE regions, the zero-load ambients dropped by 1 to 2 F from those found earlier and the rounded HLL slope factors ranged from 1.05 to 1.3. The average rounded HLL slope factor over all six DOE regions is 1.15. Effects of the revised slope factor on rated HSPFs (Region IV) for single- and two-capacity units dropped from 16% in the original work to 12.6% in this report. For VS units, the HSPF reductions of 14 to 25% in the original report were lowered to a range of 9 to 21%. As in the original report, for VS units that do not limit minimum speed operation below 47 F ambient, the average HSPF reduction for the cases evaluated is approximately the same as for single- and two-capacity units. For VS units that do limit minimum speed operation below 47 F ambient, the lower 1.15 slope factor of this report generally results in small overpredictions of rated HSPF by 1 to 3% compared to functional HSPF. An exception is minimum-speed-limited VS units where the minimum speed COP at 47 F is higher than that at 62 F; one such unit was found to have an HSPF overprediction of over 14% with the 1.15 HLL slope factor level. For such VS exception cases, a default HSPF penalty should be considered. For the more typical VS units that limit minimum speed operation, use of a 1.15 slope factor for rated HSPF was found to still acceptably limit the HSPF error. If slope factors lower than 1.15 are used for HSPF ratings, some means should be considered to appropriately derate the HSPFs for VS units which limit minimum speed operation below 47 F ambient.

42 ENGINEERING↗
DOE OSTI2022

Load Following Analysis of the Holos-Quad 10MWe Micro-Reactor with Plant Dynamics Code

This report presents the load following analysis of the “Holos-Quad” 10MWe micro-reactor design developed by HolosGen LLC. This analysis is focused on the Holos-Quad micro-reactor ability to match the changing grid demand at 10%/min rate. The control mechanisms for the plant are identified, simulated, and compared. Based on the comparison results, control strategy for load following of the Holos-Quad micro-reactor is developed. The control strategy and load following capabilities are demonstrated in a full-range down-and-up reactor power transient from 100% to 0% and back to 100% load at 10%/min rate. All calculations are carried out with Argonne’s Plant Dynamics Code.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Analytic analysis of load alignment for coning extreme‐scale rotors

Abstract Extreme‐scale wind turbines (rated powers greater than 10 MW) with large rotor diameters and conventional upwind designs must resist extreme downwind and gravity loads. This can lead to significant structural design challenges and high blade masses that can impede the reduction of levelized cost of wind energy. Herein, the theoretical basis for downwind load alignment is developed. This alignment can be addressed with active downwind coning to reduce/eliminate flapwise bending loads by balancing the transverse components of thrust, centrifugal, and gravitational force. Equations are developed herein that estimates the optimal coning angle that reduces flapwise loads by a specified amount. This analysis is then applied to a 13.2‐MW scale with 100‐m‐level wind turbine blades, where it is found that a load alignment coning schedule can substantially reduce the root flapwise bending moments. This moment reduction in this example can allow the rotor mass to be decreased significantly when compared with a conventional upwind three‐bladed rotor while maintaining structural performance and annual energy output.

Noyes, Carlos↗
DOE OSTI2017

Autonomous plug and play electric vehicle charging scenarios including reactive power provision: a probabilistic load flow analysis

Electric vehicle (EV) charging can have various impacts on low‐voltage distribution systems, along with increasing the uncertainty of network load levels. One method for capturing the statistical uncertainty is probabilistic load flow (PLF). A primary concern of such an approach is determining the correlation between the input variables. Since data are limited, a 1 min resolution bottom‐up time‐variant load model, capturing the changing voltage dependencies of the load, is used for modelling household electrical demand to provide pseudo‐meter data for the three‐phase PLF analysis of a residential distribution network. The correlation between the household and EV charging loads are implicitly taken into account by modelling the EV plug‐in and departure times with the corresponding occupancy model. Two autonomous plug‐and‐play charging scenarios are compared with a standard charging arrangement at both unity and 0.95 capacitive power factors. Four different PLF input correlation scenarios, varying from fully correlated to fully independent, are considered. The proposed charging scenarios and reactive power provision reduce the likelihood of system voltage violations introduced by EVs. The PLF results are verified against those from the initial time‐series analysis providing valuable insight into the uncertainty introduced by EVs and the correlation between household and EV loads.

Melhorn, Alexander C.↗
DOE OSTI2021

Load Decomposition Analysis Tool

This project tests the application of Bennet Meyers' signal decomposition to the residential end-use load decomposition problem.

Chassin, David P.↗
DOE OSTI2024

Time and Frequency Analysis of Load Profile Data

Technology advancements and integration of modern advanced metering systems can monitor, forecast, inform, control, and operate the building's mechanical, electrical, and plumbing (MEP) systems. They offer a higher level of information, which can contribute to making smart buildings more energy efficient and to making them closer to becoming grid-interactive energy efficient buildings (GEB). This paper builds on the ongoing research on variability analysis of a case study building with a 1-minute load profile and examines the Discrete Wavelet Transform (DWT) process in the frequency domain to quantify the signal's energy in each bandwidth, with respect to each end-use category. Moreover, the amount of variability in the total variability is not similar among the end-use categories. This information is needed to understand the behavior of the variability in the frequency domain for future applications, such as generating synthetic load profiles with a similar frequency spectrum as the measured signal.

decomposition↗
DOE OSTI2019

Load Flexibility Analysis of Residential HVAC and Water Heating and Commercial Refrigeration

The emergence of connected devices and the Internet of Things has opened the door to the concept of widespread use of building equipment for load-side flexibility. This stems from the increased use of distributed and clean energy resources for electric generation and the growing demand for a more resilient and reliable grid. A significant challenge associated with the use of building equipment as a distributed energy resource is quantifying the magnitude of power or energy flexibility. Unlike batteries that have well-defined and relatively constant capacity and maximum charge/discharge rates, building equipment often has characteristics that vary based on external factors (e.g., weather or occupant behavior). This makes quantifying the availability and flexibility of these resources difficult. Controlling a fleet of equipment while minimizing any adverse impacts to the occupants (e.g., discomfort or food spoilage) is a nontrivial matter. Although there are many different control methodologies available, this study focuses on two: priority-based control (PBC) and model-predictive control (MPC). These were selected because they represent two ends of the control spectrum. PBC is a relatively simple control strategy that requires only the current state of the devices to be controlled and an estimate of how much power each device consumes when turned on. MPC is much more complex and requires a model of the system and forecasts of any disturbances that influence the system. Because MPC has a predictive element, it can prepare for a desired response before the event and therefore is expected to provide a more optimal control relative to PBC. Both MPC and PBC are compared with a baseline simulation that uses feedback control typical of the thermostatically controlled devices being evaluated. This report investigates the load flexibility of three building systems: residential air conditioners, residential water heaters, and commercial refrigeration. Air heating and cooling and water heating account for 45% of residential electricity use, making them good candidates for providing load flexibility. Refrigeration in commercial buildings accounts for 16% of commercial building electricity use, making it another good candidate. Simplified models of each system were generated and validated based on measured data from actual equipment. These models were used to simulate the thermal and power response of the systems using PBC and MPC for a fleet of devices trying to achieve a variety of different responses, including hourly load shed, hourly load up, and daily peak demand reduction. Significant findings from each piece of equipment follow.

42 ENGINEERING↗