Results for “power plant model validation” — Page 8

DOE OSTI2024

Addressing Failures in Molten Salt Thermal Energy Storage Tank for Central Receiver Concentrating Solar Power Plants

The thermal energy storage (TES) system is a critical component in concentrated solar power (CSP) plants that increases the plant's capacity factor and economic competitiveness by reducing the levelized cost of energy (LCOE) while simultaneously increasing the value of the delivered energy. Failures including molten-salt leaks and diverse localized cracking after several months to a few years of operation have been reported in hot tanks for CSP plants operating around the world. A model of a molten salt thermal energy storage tank was developed and validated to analyze the impact of different tank design features on the temperature and stress distributions as a function of typical plant operation conditions. Design features included the floor plate thicknesses, friction coefficients between the tank floor and the foundation, and the sparger ring location. Maximum stresses in the tank floor frequently surpassed the yield point of the material during operation, leading to a detriment of the tank's lifetime. Recommendations on design features to improve the reliability of new molten salt tanks for CSP plants are provided.

concentrating solar power↗

DOE OSTI2026

Wind Plant Flow Physics and Power Performance in Complex Environments: Cooperative Research and Development (Final Report)

Cornell University will partner with NLR on the topic of wind farm wake effects to improve understanding of interactions between complex atmospheric flows, terrain, and wind turbine wakes and plant efficiency. Wind plant flow simulation tools will also be validated. The work performed will help improve wind farm modeling by analyzing data, applying models, designing and performing experiments to acquire additional wind farm data, and develop better models.

17 WIND ENERGY↗

DOE OSTI2021

A HPC Theory-Guided Machine Learning Cyberinfrastructure for Communicating Hydrometeorological Data Across Scales

High-resolution predictions of hydrometeorological variables are critical for supporting hydropower generation decisions and flood control at hydroelectric power plants. Traditional climate and hydrologic models rely on the numerical simulation of detailed physical processes. Therefore, running these simulations is time-, labor-, and computation-intensive. Improving the spatial and temporal resolution in these modeling outputs could lead to cubic increases in both the simulation time and computational demands, rendering high-resolution hydrometeorological predictions expensive and impractical. Many past studies apply the super resolution (SR) technique to downscale climate models using deep learners. However, deep learners are deemed “black-boxes,” as their derivation processes from low-resolution outputs to high-resolution outputs are often hidden. Their results are difficult for domain scientists to interpret and validate. Thus, there is a need for an exploratory machine learning approach that can partially integrate domain-specific theory and knowledge into the data-driven mapping process between simulation outputs of different spatial scales. The domain-specific theory and knowledge can be incorporated into the data model through an inductive approach in which process-related environmental variables are used and analyzed as key drivers (i.e., environmental surrogates) to reflect the complex physical processes. Many of these variables, such as land use land cover, soil types, topography, digital elevation, air temperature, and various watershed characteristics, can be directly measured through sensors or remote sensing techniques. Additionally, SR applications that can downscale hydrological and hydrodynamics models to efficiently produce high-resolution (1 m) flood depth grids are still rare. Since the flood depth grid can be used to support critical decisions for flood control operation at hydroelectric power plants, it is crucial to enable an SR-based capability for interpolating high-resolution flood inundation maps.

13 HYDRO ENERGY↗

DOE OSTI2020

Development of Real-Time System Identification to Detect Abnormal Operations in a Gas Turbine Cycle

Here, we present a novel online system identification methodology for monitoring the performance of power systems. This methodology was demonstrated in a gas turbine recuperated power plant designed for a hybrid configuration. A 120-kW Garrett microturbine modified to test dynamic control strategies for hybrid power systems designed at the National Energy Technology Laboratory (NETL) was used to implement and validate this online system identification methodology. The main component of this methodology consists of an empirical transfer function model implemented in parallel to the turbine speed operation and the fuel control valve, which can monitor the process response of the gas turbine system while it is operating. During fully closed-loop operations or automated control, the output of the controller, fuel valve position, and the turbine speed measurements were fed for a given period of time to a recursive algorithm that determined the transfer function parameters during the nominal condition. After the new parameters were calculated, they were fed into the transfer function model for online prediction. The turbine speed measurement was compared against the transfer function prediction, and a control logic was implemented to capture when the system operated at nominal or abnormal conditions. To validate the ability to detect abnormal conditions during dynamic operations, drifting in the performance of the gas turbine system was evaluated. A leak in the turbomachinery working fluid was emulated by bleeding 10% of the airflow from the compressor discharge to the atmosphere, and electrical load steps were performed before and after the leak. This tool could detect the leak 7 s after it had occurred, which accounted for a fuel flow increase of approximately 15.8% to maintain the same load and constant turbine speed operations.

algorithms↗

DOE OSTI2023

Transient Efficiency, Flexibility, and Reliability Optimization of Coal-Fired Power Plants - Final Report

This program developed an advanced model-based monitoring and model-predictive control algorithms for a coal fired power plant (CFPP), and deployed these algorithms in a real-time platform to demonstrate performance benefits for transient flexibility and plant operation efficiency. More specifically, the objectives were successfully achieved through a combination of (i) developing a high-fidelity transient plant model in Apros, which was used as a high-fidelity plant simulation between $100-50\% TMCR$ where TMCR denotes the turbine maximum continuous rating, i.e., baseload, (ii) developing a very fast physics-based reduced-order model (ROM) of the plant, which ran more than $100\times$ faster than real-time, enabling its use as real-time embedded model for model-based estimation (MBE) and model predictive control (MPC) (iii) implementing a real-time MBE based on ROM using a robust unscented Kalman filter (UKF) to continuously tune the ROM to match the measurements from high-fidelity Apros plant model despite significant plant-model mismatch, and thus, obtain a Digital Twin of the plant (iv) designing and implementing a real-time MPC with dual objectives of transient plant load tracking with high ramp rates and minimizing coal consumption, i.e., improving plant efficiency in the baseload-partload operation range of $100-50\% TMCR$. Each key element above was developed and tested individually, and has been reported in corresponding Topical Reports. Finally, all the individual elements were integrated in an overall closed-loop system, that was successfully tested in desktop Simulink test harness simulations with ROM or high-fidelity model as the plant. Thereafter, the Simulink implementation was used to auto-generate C-code and deploy as real-time Docker microservice containers in Linux, and validate that they can run in real-time in the hardware-in-the loop (HIL) setup and produce the same results as in Simulink. The results of the integrated simulation tests in Simulink as well as the real-time HIL deployment are documented in this final report, showing good load tracking for load ramps at $3-4\%/min$ ramp rates, and achieving up to $5.5\%$ reduction in coal relative to baseline operation at $50\% TMCR$ load. The desktop and HIL simulations show successful performance of the overall model based estimation and control solution and achieve the key objectives of the program for flexible, efficient and reliable operation of subcritical coal fired power plants.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Development of the TREAT M2 experiment as a transient benchmark

A transient benchmark based on the Transient Reactor Test Facility (TREAT) M2 Calibration experiment (M2-CAL) is under development. TREAT, at Idaho National Laboratory, is a graphite moderated air-cooled research reactor which has been used extensively for fuel material testing under extreme and accident conditions. Accurate benchmark models are a beneficial component in the operations, experimental planning, and development of TREAT. In this work, we present a transient benchmark model for the M2-CAL experiment core loading. The benchmark model incorporates the coupling between the Monte Carlo Code SERPENT and the computational fluid dynamics code OpenFOAM to capture the temperature feedback mechanism. The M2-CAL transient 2580 was simulated in this work. A pre-transient analysis was performed to determine the optimum core composition and conditions before the beginning of the transient. The analysis was validated against historic TREAT kinetic measurements and the worth of the transient rod T-2. The axial power distribution in the flux wire for the M2-CAL experiment was determined and contrasted with the experiment. The model was then used to simulate the M2-CAL transient 2580 experiment based on the reported pre-transient and transient conditions. Several transient observables were calculated and compared to the experiment. The model shows good agreement with the experimental power traces, period, and average increase of power at the power ramp (time > 7.8 s). Inverse point kinetics analysis was performed during the period of the power ramp for the model and the experiment based on that, the temperature feedback component was isolated and contrasted with the experimental feedback. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Transient Efficiency, Flexibility, and Reliability Optimization of Coal-Fired Power Plants - Final Program Review

This program developed an advanced model-based monitoring and model-predictive control algorithms for a coal fired power plant (CFPP), and deployed these algorithms in a real-time platform to demonstrate performance benefits for transient flexibility and plant operation efficiency. More specifically, the objectives were successfully achieved through a combination of (i) developing a high-fidelity transient plant model in Apros, which was used as a high-fidelity plant simulation between $100-50\% TMCR$ where TMCR denotes the turbine maximum continuous rating, i.e., baseload, (ii) developing a very fast physics-based reduced-order model (ROM) of the plant, which ran more than $100\times$ faster than real-time, enabling its use as real-time embedded model for model-based estimation (MBE) and model predictive control (MPC) (iii) implementing a real-time MBE based on ROM using a robust unscented Kalman filter (UKF) to continuously tune the ROM to match the measurements from high-fidelity Apros plant model despite significant plant-model mismatch, and thus, obtain a Digital Twin of the plant (iv) designing and implementing a real-time MPC with dual objectives of transient plant load tracking with high ramp rates and minimizing coal consumption, i.e., improving plant efficiency in the baseload-partload operation range of $100-50\% TMCR$. Each key element above was developed and tested individually, and has been reported in corresponding Topical Reports. Finally, all the individual elements were integrated in an overall closed-loop system, that was successfully tested in desktop Simulink test harness simulations with ROM or high-fidelity model as the plant. Thereafter, the Simulink implementation was used to auto-generate C-code and deploy as real-time Docker microservice containers in Linux, and validate that they can run in real-time in the hardware-in-the loop (HIL) setup and produce the same results as in Simulink. The results of the integrated simulation tests in Simulink as well as the real-time HIL deployment are documented in this final report, showing good load tracking for load ramps at $3-4\%/min$ ramp rates, and achieving up to $5.5\%$ reduction in coal relative to baseline operation at $50\% TMCR$ load. The desktop and HIL simulations show successful performance of the overall model based estimation and control solution and achieve the key objectives of the program for flexible, efficient and reliable operation of sub-critical coal fired power plants.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Technoeconomics of Particle-based CSP Featuring Falling Particle Receivers with and without Active Heliostat Control

This report documents the results and conclusions of a recent project to understand the technoeconomics of utility-scale, particle-based concentrating solar power (CSP) facilities leveraging unique operational strategies. This project included two primary objectives. The first project objective was to build confidence in the modeling approaches applied to falling particle receivers (FPRs) including the effect s of wind. The second project objective was to create the necessary modeling capability to adequately predict and maximize the annual performance of utility-scale, particle-based CSP plants under anticipated conditions with and without active heliostat control. Results of an extensive model validation study provided the strongest evidence to date for the modeling strategies typically applied to FPRs, albeit at smaller receiver scales. This modeling strategy was then applied in a parametric study of candidate utility-scale FPRs, including both free-falling and multistage FPR concepts, to develop reduced order models for predicting the receiver thermal efficiency under anticipated environmental and operating conditions. Multistage FPRs were found to significantly improve receiver performance at utility-scales. These reduced order models were then leveraged in a sophisticated technoeconomic analysis to optimize utility-scale , particle-based CSP plants considering the potential of active heliostat control. In summary, active heliostat control did not show significant performance benefits to future utility-scale CSP systems though some benefit may still be realized in FPR designs with wide acceptance angles and/or with lower concentration ratios. Using the latest FPR technologies available, the levelized-cost of electricity was quantified for particle-based CSP facilities with nominal powers ranging from 5 MW e up to 100 MW e with many viable designs having costs < 0.06 $/kWh and local minimums occurring between ~25–35 MW e .

14 SOLAR ENERGY↗

DOE OSTI2025

Simulation of Physics-Based 0-10Hz Strong Motion Using High Performance Computing Supporting Refinements to Regional Ground Motion Models for the Central Eastern US

In collaboration with the U.S. Nuclear Regulatory Commission (NRC) the LLNL has developed a computationally efficient simulation platform designed to perform physics-based ground motion simulations for crustal earthquakes in the Stable Continental Regions of Central and Eastern US (CEUS), using high-performance computing. The main objective of the earthquake simulations was to use synthetic ground motion to provide constrains to refinements of existing ergodic Ground Motion Models (GMMs), for large magnitude earthquakes and near-fault distances, for which these models are less reliable. Physics-based broadband (0-10Hz) ground motion simulations were used to estimate the near-fault ground motion amplitudes and within event and between-event variabilities associated with fault rupture characteristics. In our simulations we used a 3D regional velocity model that was based on Saikia’s 1D velocity model (1994). In simulations performed during the first stage of this project the Saikia’s velocity model demonstrated better performance in modelling high frequency regional wave propagation for the CEUS region recorded during the Mw5.0 November 7, 2016, Cushing Oklahoma (Taylor et al., 2017), and Mw5.8 September 3, 2016, Pawnee Oklahoma earthquakes. The proposed regional 3D model includes random perturbations to the 1D background model using the stochastic scheme of Pitarka and Mellors (2021). In addition, validation analysis of the rupture generator and regional wave propagation models, using comparisons with different GMMs for Mw6.5 and Mw7.0 scenario earthquakes in the CEUS region resulted in a very good match between the simulated and empirical ground motion models. For the purposes of seismic hazard assessment at the existing and planned nuclear power plants, NRC is interested in studies aimed at improving the current ground motion models (GMM) for both Stable Continental Regions (SCR) in the Central and Eastern US and Active Crustal Regions (ACR) in the Western US. Due to lack of recorded data, these improvements require synthetic data for short fault distances and large magnitude earthquakes for which the existing recorded data is not enough to uniquely constrain the GMMs. The need for simulations and strong motion data is especially critical for the CEUS region where we do not have recorded data from potentially large damaging earthquakes with moment magnitudes 6.0 and higher. In this the project, we focused on 10Hz simulations of Mw7.0 scenario earthquakes with strike slip and thrust faulting mechanisms. We used more than 50 Mw7.0 earthquake rupture scenarios to investigate the ground motion uncertainty due to unknown earthquake rupture parameters, in particular, the slip distribution, rupture velocity, and faulting mechanism, and their implication on ground motion amplification due to forward rupture directivity effects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Demonstration of low-density, high-performance operation of sustained spheromaks and favorable scalability toward compact, low-cost fusion power plants (Final Scientific/Technical Report)

This project worked to advance the technical viability of a novel method for efficiently sustaining stable, high-performance spheromak plasma configurations to serve as the basis of compact, low-cost fusion power plants. In particular, our group worked to improve the method of Steady Inductive Helicity Injection (SIHI) with Imposed-Dynamo Current Drive (IDCD) for spheromak plasma sustainment. Prior to this project demonstrations of this plasma sustainment technology have achieved plasma performance consistent with entry milestone 3 of the BETHE FOA. Research and development (R&D) activities for this project were focused on increasing plasma performance toward a level consistent with exit milestone 4. To do this the PI and his group worked to increase the performance of sustained spheromaks produced in an existing experimental prototype (HIT-SIU) while improving confidence in projections to and design of future, higher performance devices through three primary R&D activities: 1) Improved control over the density of plasma in the device throughout a discharge to provide a pathway for demonstration of spheromaks Ohmically heating to the Mercier beta limit via: a. Fueling the device directly with plasma through the installation of pre-ionized source on the injectors b. Optimization of electrical current waveforms in the driver circuits to enable low-density plasma formation with a lower fueling rate 2) Computational demonstration of a validated, realistic injector circuit coupled to a dynamic plasma model capable of use as a design tool for SIHI drivers and associated circuits for new experimental design points on the pathway to commercial reactors. The improvements in plasma performance achieved during research activity 1), and the computational projections performed in research activity 2) increased the technological readiness level (TRL) of this fusion energy concept toward a level sufficient to attract early-stage private investment and/or other forms of follow-on investment to pursue required R&D activities required for the eventual fusion power plants based on this novel technical approach.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Co-design optimization of combined heat and power-based microgrids

With the emergent need for clean and reliable energy resources, hybrid energy systems, such as the microgrid, are widely adopted in the United States. A microgrid can consist of various distributed energy resources, for instance, combined heat and power (CHP) systems. Here, the CHP module is a distributed cogeneration technology that produces electricity and recaptures heat generated as a by-product. It is an energy-efficient technology converting heat that would otherwise be wasted to valuable thermal energy. For an optimal system configuration, this study develops a novel co-design optimization framework for CHP-based cogeneration microgrids. The framework provides the stakeholder with a method to optimize investments and attain resilient operations. The proposed co-design framework has a mixed integer programming (MIP) model that outputs decisions for both plant designs and operating controls. The microgrid considered in this study contains six components: the CHP, boiler, heat recovery unit, thermal storage system, power storage system, and photovoltaic plant. After solving the MIP model, the optimal design parameters of each component can be found to minimize the total installation cost of all components in the microgrid. Furthermore, the online costs from energy production, operation, maintenance, machine startup, and disruption-induced unsatisfied loads are minimized by solving the optimal control decisions for operations. Case studies based on designing a CHP-based microgrid with empirical data are conducted. Moreover, we consider both nominal and disruptive operational scenarios to validate the performance of the proposed co-design framework in terms of a cost-effective, resilient system.

42 ENGINEERING↗

DOE OSTI2024

Demand bidding vs. demand response for industrial electrical loads

Not Available

Tang, Xin (ORCID:0009000720910131)↗

DOE OSTI2022

Automation of FARM from Alpha Phase to Beta Phase

Integrated energy systems (IES) combine different energy technologies in synergistic ways to achieve a more secure and economical energy supply. The RAVEN-based HYBRID framework and the RAVEN plugin for grid and capacity optimization (HERON) are used to find the optimal installed capacity and the optimal economical dispatch of each component of the IES, by respecting the limits on the production variables and the corresponding rates of variation (explicit constraints). Besides, there are other process variables whose evolution needs to be bounded to avoid damaging the components (e.g., condensers, heat exchangers, steam generators, etc.) or degrading the process efficiency (e.g., electrolysis in the hydrogen production process). To avoid violating these latter limits (implicit constraints), a proof-of-concept HERON validator based on Feasible Actuator Range Modifier (FARM-Alpha) was developed by Argonne National Laboratory in January 2021. This FARM-Alpha validator calculates the evolution of process variables on whom the implicit constraints are placed, and then provides feedback to HERON dispatcher to adjust the power setpoints of three IES components, i.e., Balance of Plant, Secondary Energy Source, and Thermal Energy Storage, so as to meet both the explicit and implicit constraints. FARM-Alpha was designed to assess the performance of FARM as a HERON validator only, i.e., the list of components and implicit operational constraints were hard-coded within the source code. The lack of flexibility of the corresponding software structure does not allow the deployment in production environment. This report describes the development and the implementation of an enhanced version of the FARM-based validator (FARM-Beta), which ensures more flexibility for the end user in modeling multiple IES configurations and scenarios. Several test cases of the power dispatch problem were then selected to demonstrate the capabilities offered by FARM-beta. The test cases illustrate the efficiency of the closed-loop optimization scheme and the capability to calculate set-point trajectories satisfying both explicit and implicit constraints.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1992

Techniques for optimal crop selection in a controlled ecological life support system

A Controlled Ecological Life Support System (CELSS) utilizes a plant's natural ability to regenerate air and water while being grown as a food source in a closed life support system. Current plant research is directed toward obtaining quantitative empirical data on the regenerative ability of each species of plant and the system volume and power requirements. Two techniques were adapted to optimize crop species selection while at the same time minimizing the system volume and power requirements. Each allows the level of life support supplied by the plants to be selected, as well as other system parameters. The first technique uses decision analysis in the form of a spreadsheet. The second method, which is used as a comparison with and validation of the first, utilizes standard design optimization techniques. Simple models of plant processes are used in the development of these methods.

Mccormack, Ann↗

NASA NTRS1993

Techniques for optimal crop selection in a controlled ecological life support system

A Controlled Ecological Life Support System (CELSS) utilizes a plant's natural ability to regenerate air and water while being grown as a food source in a closed life support system. Current plant research is directed toward obtaining quantitative empirical data on the regenerative ability of each species of plant and the system volume and power requirements. Two techniques were adapted to optimize crop species selection while at the same time minimizing the system volume and power requirements. Each allows the level of life support supplied by the plants to be selected, as well as other system parameters. The first technique uses decision analysis in the form of a spreadsheet. The second method, which is used as a comparison with and validation of the first, utilizes standard design optimization techniques. Simple models of plant processes are used in the development of these methods.

Mccormack, Ann↗

DOE OSTI2020

Residual Stress Modeling with Phase Transformation for Wire Arc Additive Manufacturing of B91 Steel

Wire arc additive manufacturing (WAAM) is an energy-efficient manufacturing technique used for near-net-shape production of functional industrial components. However, heat accumulation during deposition and the associated mechanical and metallurgical changes result in complex residual stress profiles across the cross section of the fabricated components. These residual stresses are detrimental to the service life of the components. In this study, sequentially coupled thermomechanical analysis of WAAM B91 steel is conducted to quantify the residual stress variation across the component. The thermomechanical analysis includes a transient heat transfer model and a static stress model that incorporates the transformation-induced plasticity due to martensitic phase transformation. Here, the experimentally calibrated heat transfer model mirrors the temperature variation of the system during the deposition. The results from the stress model are validated via x-ray diffraction measurements, and the numerical results are in good agreement with the experimental data.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2024

Advanced grid-forming (GFM) inverter controls, modeling and system impact study for inverter dominated grids

Our main goals in this project are to understand: 1) the stability of the power system with very high penetration of PV or other inverter-based resources (IBR), 2) the interactions among IBRs and traditional generators, and 3) the impact of the GFM inverters on bulk power system. To achieve these goals, we took a holistic research and development approach. First, an impedance-based large system modeling and stability analysis tool was developed to aid the large IBR system small-signal stability analysis. Second, consensus-based control and transient overload ride through were developed to control and coordinate multiple GFM inverters in a large system to maintain transient stability during big grid events. Third, high fidelity electromagnetic transient (EMT) IBR models were developed and integrated into a large reduced WECC model to study the system impact from IBRs. Lastly, extensive validation tests of the GFM control which was developed in this project and implemented in two 1MW commercial solar inverters were performed using different validation platforms, e.g., control hardware-in-the-loop (CHIL) platform, power hardware- in-the-loop (PHIL) platform, and a real PV plant.

14 SOLAR ENERGY↗

DOE OSTI2026

Wind Conditions for Solar Energy Facility Design Based on Field Measurements at Nevada Solar One

This study characterises near-surface wind conditions at the Nevada Solar One (NSO) concentrated solar power plant using two years of measurements from a 15-m mast located 30 m west of the solar arrays. The surrounding terrain is fairly flat within 3 km, but nearby solar photovoltaic (PV) and concentrated solar power (CSP) installations introduce strong directional wind inhomogeneity, which motivates a sector-based analysis that distinguishes undisturbed inflow from waked flow. The analysis uses data from three sonic anemometers to assess whether turbulence in the surface layer can be represented as Gaussian and whether standard surface-layer scaling remains valid below 10 m height. The roughness length and displacement height are estimated for twelve directional sectors under near-neutral wind conditions, and all three velocity components show departures from Gaussian behaviour. Spectral analysis indicates that the turbulence contains low-frequency fluctuations with amplitudes higher than those predicted by standard models such as the Kaimal model or the Simiu and Scanlan model. The study introduces a new turbulence spectral model based on the eddy-surface-layer framework to better represent near-surface wind turbulence. The analysis further quantifies the influence of the surrounding power plants on mean wind profiles, one-point spectra, and vertical coherence for all velocity components. The solar collector arrays located 30 m east of the mast significantly modify the turbulence structure, whereas PV installations situated a few hundred metres away have only a limited influence on the turbulence measured at the mast. These findings highlight the limitations of conventional turbulence models for near-surface wind over solar infrastructure and provide improved parameterisations to support the structural design. The implications for the structural response of parabolic troughs and PV modules to such turbulence remain uncertain and require further investigation.

14 SOLAR ENERGY↗