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DOE OSTI2020

Novel Technique for Developing Linearized Convex System Models from Experimentally Derived Data

This paper presents a novel technique for generating a convex system model from an experimentally derived data set which features variance among repeated measurements. The convex system model developed as a test case characterizes the dynamic system losses of a vanadium redox flow battery as a function of the active power output and the battery state of charge. The technique hinges on a pre-cleaning via clustering procedure which precedes the formation of a planar convex hull comprised of triangular simplices. The clustering procedure efficiently reduces the experimental data set while mitigating variance among repeated measurements and removes outliers. Ultimately, the lower evelope of the planar convex hull serves as the desired convex system model. The proposed technique reduces systematic model error which is otherwise present when directly developing a planar convex hull model based on an unreduced data set.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

A Generic Modeling and Development Approach for WECC Composite Load Model

The composite load model (CLM) proposed by Western Electricity Coordinating Council (WECC) gains increasing traction in the industry, particularly in North America. At the same time, it is recognized that further improvements in the structure, initialization and aggregation methods are needed. However, lack of an open implementation of WECC CLM becomes a roadblock for many researchers to work on improving it. This paper presents the first open reference implementation of WECC CLM. Individual load components and the CLM are first developed and tested in Matlab, then translated to the high performance computing (HPC), parallel simulation platform GridPACK. Main contributions of the paper include: 1) presenting some important yet undocumented details of modeling and initializing the CLM, particularly for a parallel simulation platform like GridPACK; 2) implementation details of the load components such as the single-phase air conditioner motor; 3) implementing the CLM in a modular and extensible manner. The implementation has been tested at both the component as well as system levels and bench-marked against commercial simulation programs.

Huang, Qiuhua↗

DOE OSTI2024

Low-Cost Heliostat for High-Flux Small-Area Receivers (Final Technical Report)

This project analyzed a two-stage heliostat concept consisting of a tracking stage and a concentrating stage. The tracking stage uses mirrors mounted on a common drive that move to track the sun. The concentrating stage consists of stationary mirrors that each have a unique angle to direct rays towards a small-area, high-flux, point-focused receiver. By splitting the collection and concentrating process into two stages, multiple small, inexpensive mirrors can share a structure and be controlled by a single drive in the tracking stage. The project effort developed modeling techniques that were specifically relevant to this two-stage heliostat concept. Both field-level and unit-level models were developed. The field-level model does not explicitly consider unit-level losses which are predicted by the unit-level model and then integrated into the field-level model through a correlation referred to as an efficiency modifier. This approach is referred to as the two-model approach; the development and demonstration of this two-model approach for a multi-stage heliostat technology is a key outcome of this work. The field-level model is used to design a field that hits a specific design day power given a set of heliostat design parameters. An oversized field is simulated and then heliostat units are removed based on their annual energy production in order to generate the highest performing field. The field reduction procedure fits a smooth curve fit to annual energy production as a function of position in the field which has the effect of reducing the noise that is otherwise caused by the Monte Carlo ray tracing technique. This approach is referred to as the annual energy fit method and substantially reduces computational run time for a given field level modeling accuracy. The annual energy fit approach enables the selection of a properly sized, high-performing field using orders of magnitude fewer rays than would otherwise be possible and the development of this approach is a second key outcome of this work. These models are used within a genetic optimization algorithm in order to optimize the geometric parameters associated with a heliostat in order to achieve the lowest cost per unit of collected design day power. The cost modeling that underlies the optimization is a simple, scaling type analysis backed up by a much more detailed Design for Manufacture and Assembly (DFMA) analysis. Although the figure of merit used for optimization was not cost per mirror area, this metric is reasonable to use as a means of comparison. The optimally designed 500 kW design has a tracking mirror specific cost of $181.85/m 2 , which is significantly larger than the target value and also larger than the current state of the art. The cost of the torque-tube type linkages contributed substantially to the overall cost. Based on this observation, potentially attractive alternative design configuration utilizing a capstan type actuation system should be investigated. Finally, NREL compared the performance of the two-stage heliostat to the performance of a focused and different sized flat conventional heliostats and showed that, as expected, additional losses versus the convention heliostat caused by a worse cosine efficiency, two stages of reflection, and interstage interactions. The two-stage heliostat requires around 75% more reflective area than a flat 1x1 meter conventional heliostat (similar to a focused heliostat) and 40% more than a flat 2x2 meter conventional heliostat.

14 SOLAR ENERGY↗

DOE OSTI2014

Climate Science for a Sustainable Energy Future Test Bed and Data Infrastructure Final Report

The collaborative Climate Science for a Sustainable Energy Future (CSSEF) project started in July 2011 with the goal of accelerating the development of climate model components (i.e., atmosphere, ocean and sea ice, and land surface) and enhancing their predictive capabilities while incorporating uncertainty quantification (UQ). This effort required accessing and converting observational data sets into specialized model testing and verification data sets and building a model development test bed, where model components and sub-models can be rapidly evaluated. CSSEF’s prototype test bed demonstrated, how an integrated testbed could eliminate tedious activities associated with model development and evaluation, by providing the capability to constantly compare model output—where scientists store, acquire, reformat, regrid, and analyze data sets one-by-one—to observational measurements in a controlled test bed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2011

Support to DHS Chemical Detection Field Testing and Countermeasures Studies: Report to Sponsors

This document reports on work that Lawrence Berkeley National Laboratory performed to support the Department of Homeland Security's testing of ARFCAM and LACIS systems. In the sections that follow, LBNL lists the scope of work, field analyses conducted, and preliminary results. LBNL developed a model of the Port Gaston building at the Nevada Test Site and calibrated it using data from field experiments, both blower door and tracer gas tests. Model development and comparison to data show very good agreement. The model was developed to (1) support the interpretation of data from field trials performed by Signature Science LLC, (2) support the placement of sampler equipment, and (3) predict if meteorological differences between the Wet-Run/Dry-Run and the Hot-Run might adversely affect the development of the Hot Run Test Plan. LBNL reported its findings on each task to the experiment team at scheduled planning meetings. In the end, we note that the model was used limitedly because the data from the Wet-Run/Dry Run were if such high quality. Lastly, LBNL conducted a research experiment at the end of the Wet-Run/Dry-Run to study if, and to what degree, specific TICs sorb and desorb on indoor surfaces. We found that several of the TICs either sorb onto surfaces or are lost through chemical reactions. These findings may have important implications on determining sheltering-in-place concepts of operation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2016

User Guide for the International Jobs and Economic Development Impacts Model

The International Jobs and Economic Development Impacts (I-JEDI) model is a freely available economic model that estimates gross economic impacts from wind, solar, and geothermal energy projects for several different countries. Building on the original JEDI model, which was developed for the United States, I-JEDI was developed under the USAID Enhancing Capacity for Low Emission Development Strategies (EC-LEDS) program to support countries in assessing economic impacts of LEDS actions in the energy sector. I-JEDI estimates economic impacts by characterizing the construction and operation of energy projects in terms of expenditures and the portion of these expenditures made within the country of analysis. These data are then used in a country-specific input-output (I-O) model to estimate employment, earnings, gross domestic product (GDP), and gross output impacts. Total economic impacts are presented as well as impacts by industry. This user guide presents general information about how to use I-JEDI and interpret results as well as detailed information about methodology and model limitations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2019

Novel Technique for Developing Linearized Convex System Models from Experimentally Derived Data: Preprint

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

A Predictive Transient Model of the TREAT-SIRIUS Experiments

To support experiments modeling and transient analysis of the NASA-sponsored SIRIUS experiments in the Transient Reactor Test Facility (TREAT), an innovative predictive transient model has been developed to simulate various transient experiments. The developed model is based on a new approach that utilizes steady-state Monte Carlo calculations along with a surrogate model based on polynomial regression to determine the core reactivity. The reactivity is supplied to an exact point kinetics model that determines the reactor power, and it is coupled to an adiabatic feedback model to determine the fuel average temperature. In this work, the newly developed model is introduced along with validation test results considering SIRIUS-1 experiments at different power levels. The initial test results show a very good agreement with experimental data at different power levels, which indicates that the model can be used to predict the power of other transient tests.

42 ENGINEERING↗

DOE OSTI2024

Investigation of a Hybrid Carbon Capture System at a NGCC Power Plant That Performs Direct Air Capture During Off-Peak Hours

The goal of this project was to investigate the feasibility of coupling NGCC power plants with membrane and solid sorbent carbon capture to achieve net negative carbon emissions. This novel hybrid system has a couple of potential benefits: 1) the carbon capture systems could help the NGCC plant by minimizing its carbon footprint and giving it a new revenue stream from direct air capture, and 2) the NGCC plant could help direct air capture scale up quickly and costeffectively by providing it with electricity, steam and compressed air streams. In order to investigate this hybrid design, we developed a complex, integrated system model consisting of: 1) a NGCC power plant model developed by Dr. Bhattacharyya’s team at WVU, 2) a membrane carbon capture model developed by Dr. Lipscomb’s team at U Toledo, and 3) a solid sorbent carbon capture model developed by Dr. Hornbostel’s team at U Pittsburgh. Mr. Matuszewski’s team at AristoSys LLC integrated these three models into a single, integrated model using FOQUS, an optimization tool developed by the NETL CCSI 2 program. Optimizations were then performed on this integrated model to determine the cost and carbon capture rates under a range of electricity and carbon price scenarios.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Delivery of Dynamic Thermal Energy Storage Models and Advanced Reactor Concept Models to the HYBRID Repository

This publication details newly created energy storage and reactor models developed within the HYBRID modeling repository as part of the Department of Energy Office of Nuclear Energy (DOE-NE) Integrated Energy Systems (IES) program, led by Idaho National Laboratory (INL). Model development to-date includes creation of dynamic systems-level models of a pebble bed high temperature gas reactor (HTGR), sodium fast reactor (SFR), compressed air energy storage (CAES), liquid air energy storage (LAES) and Modelica standard library based two-tank sensible heat storage (SHS) in the IES-based HYBRID repository. Models are developed using the latest publicly available data and incorporate the possibility of control strategy inclusion for use with the existing IES modeling, analysis, and optimization toolset. Simulations showcase the abilities of each technology to flexibly operate in ways consistent with IES operation expectations. When these models are available, they can be utilized within different integrated energy park concepts to understand optimal system operation, control, and dispatching. Moreover, given the generic nature of the models, industrial partner technologies can be quickly added to the repository using the existing models as a basis. Additional dynamic models for thermal energy storage concepts can be developed and added to the HYBRID repository as needed. Also detailed in this report are future development goals for the HYBRID repository including adding suites of steady-state models, economic costing information, and reduced-order models. By adding these models in addition to the physical transient models currently existing within HYBRID, HYBRID will be a fully integrable tool for FORCE users.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Surrogate Model of Flexible Research Platform EnergyPlus Models to Enable Sensitivity Analysis

This letter report describes the surrogate models developed from the EnergyPlus model of Oak Ridge National Laboratory’s Flexible Research Platform. Two data-driven black-box models were developed, and the outputs of the surrogate models were compared with the EnergyPlus model. The two models developed are a multilayer perceptron deep learning model, and a long short-term memory (LSTM) neural network model. The three factors for selecting the black-box models are scalability, computation time, and accuracy. A total of 107 input variables were the dominant variables in determining the outputs of building energy consumptions and thermal comfort. A total of 54 output variables were identified as the prediction targets, including the system- and zone-level outputs. The large set of the simulation cases were generated by integrating sensor errors into an emulator based on EnergyPlus and Python EMS, which includes advanced control sequences from ASHRAE Guideline 36-2018: High-Performance Sequences of Operation. The surrogate models were developed based on a set of large-scale simulation runs (i.e., 4,000 runs) on a cloud platform. The comparison analysis shows that the two black-box models had good accuracy for predicting new outputs for sensitivity analysis using the root mean square error metric. As a next step, the developed surrogate models will be used to perform sensitivity analysis for different sensor impacts (e.g., sensor types, sensor locations).

42 ENGINEERING↗

DOE OSTI2018

Analytical heat transfer model for laterally perforated-finned heat sinks

An analytical model is proposed to predict the average Nusselt numbers of laterally perforated-finned heat sinks (LA-PFHSs) with high aspect ratios in forced convection laminar flows. The model is developed based on the experimental data acquired from testing air-cooled heat sinks including square cross-sectional perforations distributed equidistantly along the length of the fins. The experiments were conducted using three different perforation sizes and five different porosities at each perforation size. The accuracy of the experiments was validated by comparing the experimental pressure drops and heat transfer coefficients of the heat sink without perforation with those obtained from the widely accepted correlations in the literature. Here the developed model in this study predicts the Nusselt number as a function of Reynolds number, Prandtl number, fin and perforation geometrical parameters, porosity, and the distances between perforations. The model showed excellent predictions for the Nusselt numbers of all LA-PFHSs tested in this study to be within ±12% of the experimental data and a mean absolute error of 4.90%. This study is the first attempt in the literature to develop an analytical model based on experimental data for investigating heat transfer in LA-PFHSs.

42 ENGINEERING↗

DOE OSTI2021

Validation and Verification for INL Modelica-based TEDS models Via Experimental Results

This report provides an overview on the verification and validation (V&V) of the Thermal Energy Distribution System (TEDS) model developed in the Modelica process modeling ecosystem using experimental data. Model development has led to the creation of a dynamic process model of the experimental TEDS facility housed within the Energy Systems Laboratory (ESL) at Idaho National Laboratory (INL). The model was then used during the preconstruction phase of the experimental effort to inform experimental design (e.g., insulation requirements, bypass line placement, expected performance of components) and to test innovative control schemes prior to the initial operation. The TEDS model developed in Modelica includes the primary components of the TEDS experimental unit: a 200kW Chromalox heater; a single-tank packed-bed thermal energy storage system filled with 0.125-inch alumina (Al2O3) beads; an ethylene-glycol-to-Therminol-66 heat exchanger; system piping; five control valves; and all associated temperature, pressure, and volumetric flow sensors. Using the Institute of Electrical and Electronics Engineers (IEEE) V&V methodologies, considered the gold standard in the engineering field, the model was verified using a combination of static analysis, spatial convergence, and regression tests. Then using dynamic time warping (DTW) initial runs to validate and tune the TEDS model versus the experiment were conducted. This tuning method was accomplished using the INL Risk Analysis Virtual ENvironment (RAVEN) software package. Tuning is required to account for physical phenomena that are less understood within the empirical heat transfer correlations. Through the commencement of this work, a systems-level model of TEDS with associated control systems, sensors, piping diameters, and component capabilities has been created. This model was utilized in the pre-experimental phase to inform system design, insulation thicknesses, and potential control schemes to operate the system effectively and safely. Then, initial experimental startup and operational data were used to demonstrate the validation and tuning methodology. This process demonstrates the classical two-step approach of a model informing experimental design followed by the experiment validation and tuning the model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

Development and Calibration of an Online Energy Model for AHU Fan

The model development is necessary for the study of the energy consumption of Heating, Ventilation, and Air Conditioning (HVAC) systems. To predict the HVAC energy consumption accurately, one needs to model the individual HVAC components either from the measured data or based on the knowledge of the underlying physical phenomenon. Online model characterization is critical for improving the performance of real-time model-based fault detection and diagnosis (FDD) strategies. For HVAC control, models can be used to optimize the supervisory and local feedback control strategies to improve the energy consumption efficiency, or for providing ancillary services to the grid. It has been reported that, fans in HVAC systems of commercial buildings alone can provide substantial frequency regulation service, with little change in the indoor environment. In this paper, a real-time data-driven Air Handling Unit (AHU) fan model was developed based on recursive multi regression model. A generic nonlinear polynomial model has been studied to cover scenarios with different combinations of measurement variables, variable orders as well as different training and prediction horizons. Typical measurements including static pressure, mass flow rate, and damper positions are utilized as inputs to model the power consumption of the fan. The developed models have been validated both with simulation data from EnergyPlus-Dymola co-simulation model and with field measurement data for small to medium commercial buildings. The validation results show that the online model proposed can provide an effective prediction of the AHU fan power consumption.

Dong, Jin↗

DOE OSTI2018

A hybrid building thermal modeling approach for predicting temperatures in typical, detached, two-story houses

Within the residential building sector, the air-conditioning (AC) load is the main target for peak load shifting and reduction since it is the largest contributor to peak demand. By leveraging its power flexibility, residential AC is a good candidate to provide building demand response and peak load shifting. For realization of accurate and reliable control of AC loads, a building thermal model, which characterizes the properties of a building’s envelope and its thermal mass, is an essential component for accurate indoor temperature or cooling/heating demand prediction. Building thermal models include two types: “Forward” and “Data-Driven”. Due to time-saving and cost-effective characteristics, different data-driven models have been developed in a number of research studies. However, few developed models can predict temperatures in respective zones of a multiple-zone building with an open air path between zones e.g., an open stairwell connecting two floors of a home. In this research, a novel hybrid modeling approach is proposed to predict the average indoor air temperatures of both the upstairs and downstairs. This “hybrid” solution integrates both gray-box, i.e. RC model and black-box models. A developed RC model is used to predict the building mean temperature, and black-box model, in which the supervised machine learning algorithms are leveraged, is used to predict the temperature difference between the downstairs and upstairs. Compared with the measured data from a real house, the results obtained have acceptable/satisfactory accuracy. The method proposed in this study integrates the advantages of black-box and gray-box modeling. As a result, it can be used as a reliable alternative to predict the average temperatures in respective floors of typical detached two-story houses.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Discrete fracture network model benchmarks developed and applied in a DECOVALEX-2023 repository performance assessment study

This study presents newly developed benchmarks for modeling flow and transport within discrete fracture networks (DFNs) and useful methods for analyzing the results. The new benchmarks are designed to test modeling approaches for use in probabilistic performance assessment models of deep geologic repositories in fractured rock. The benchmarks simulate flow and transport through a 1 km 3 block of fractured rock. The first simulates migration of a short pulse of tracer through a simple network of four intersecting fractures. The second adds 1089 stochastically generated fractures. The third changes the pulse to a continuous point source. Evaluation of model performance relies on moment analysis and comparison of the results of different models. The expected nondimensional first moment of the conservative tracer for each benchmark is 1. The benchmarks were simulated by teams from Canada, Czechia, Germany, Korea, Sweden, Taiwan, and the United States as part of a DECOVALEX-2023 study (decovalex.org). The teams used various approaches, including explicit DFN modeling, DFN upscaling to an equivalent continuous porous medium (ECPM), and a combination of both methods. Transport mechanisms are modeled using either the advection-dispersion equation or particle tracking. Results demonstrate strong agreement among the models in breakthrough behavior up to the 75th percentile. Significant deviations in first moments and well-clustered outputs led to the identification of inaccuracies in several models. Such findings exemplify the benefit of exercising these benchmarks and using the presented methods to test DFN flow and transport models.

Benchmark↗

DOE OSTI2012

Infrastructure development assistance modeling for nuclear power plant

The purpose of this paper is to develop a model, a general frame to be utilized in assisting newcomer countries to start a nuclear power program. A nuclear power plant project involves technical complexity and high level of investment with long duration. Considering newcomers are mostly developing countries that lack the national infrastructure, key infrastructure issues may constitute the principal constraints to the development of a nuclear power program. In this regard, it is important to provide guidance and support to set up an appropriate infrastructure when we help them with the first launch of nuclear power plant project. To date, as a sole nuclear power generation company, KHNP has been invited many times to mentor or assist newcomer countries for their successful start of a nuclear power program since Republic of Korea is an exemplary case of a developing country which began nuclear power program from scratch and became a major world nuclear energy country in a short period of time. Through hosting events organized to aid newcomer countries' initiation of nuclear power projects, difficulties have been recognized. Each event had different contents according to circumstances because they were held as an unstructured and one-off thing. By developing a general model, we can give more adequate and effective aid in an efficient way. In this paper, we created a model to identify necessary infrastructures at the right stage, which was mainly based on a case of Korea. Taking into account the assistance we received from foreign companies and our own efforts for technological self-reliance, we have developed a general time table and specified activities required to do at each stage. From a donor's perspective, we explored various ways to help nuclear infrastructure development including technical support programs, training courses, and participating in IAEA technical cooperation programs on a regular basis. If we further develop the model, the next task would be to make the model more sophisticated as a 'semi-tailored model' so that it can be applied to a certain country reflecting its unique conditions. In accordance with its degree of established infrastructure, we can adjust or modify the model. Despite lots of benefits of using this model, there remain limitations such as time and budget constraints. These problems, however, can be addressed by cooperating with international organization such as the IAEA and other companies that share the same goal of helping newcomer countries introduce nuclear power. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2011

Application of Monitoring and Prognostics to Small Modular Reactors

Prognostics is one component of a full health monitoring system, which generally includes plant condition monitoring, fault detection, fault diagnostics, and estimation of remaining useful life. Empirical methods for prognostics have been widely studied, and the efficacy of these models is well accepted. However, these methods typically require large amounts of run-to-failure data for accurate model development. This has been one of the main roadblocks for developing prognostic models for high reliability or safety critical systems: equipment rarely malfunctions; when it does, it is often times repaired before failure occurs. This paper presents the work completed in developing and validating an accurate prognostic system for several potential IRIS system fault modes using high-fidelity simulated data before any plant operation takes place. Fault modes under investigation include heat exchanger fouling, sensor calibration drifts, and pump degradation. Prognostic models are developed which can be applied to the IRIS plant from day one of operation to facilitate the final step in a full health monitoring system. These estimates of remaining useful life can be used to inform both operations and maintenance planning to reduce plant downtime and provide the highest level of power production from the beginning of operation.

On-Line Monitoring↗