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DOE OSTI2018

Final Report on CFD and Thermal-Mechanical Stress Analysis of PWR Surge Line under Transient Condition Thermal Stratification and an Evolutionary Cyclic Plasticity Based Transformative Fatigue Evaluation Approach without Using S~N Curve: Rev. 1

This report presents an evolutionary cyclic plasticity based transformative approach for fatigue evaluation of safety critical components. This approach is generic which can be used not only for the present generation light water reactor components (which is our focus) but also for advanced reactor components. The approach is based on the fundamental concept of time-evolution of progressive fatigue damage rather than the end-of-life data based conventional S~N curve approaches. Series of fatigue tests on 316 stainless steel uniaxial specimens were conducted under strain-controlled and stress-controlled cyclic loading in two different environment such as in-air at 300 °C and PWR coolant water condition at 300 °C. Material models are developed to capture the uniaxial test data and are subsequently programmed into commercially available ABAQUS code to transform the uniaxial material behavior to multiaxial loading domain. The developed evolutionary cyclic-plasticity approach is verified by both analytical and 3D-FE modeling of uniaxial fatigue test specimens. Results show that the developed material models can capture the time-dependence of material hardening and softening with great accuracy. In addition, results show that the material models not only can capture the material behavior under constant amplitude loading but also can capture the load-sequence effect under variable and random amplitude loading. The ANL developed approach is one of its kind, which shows first in the fatigue research community that fatigue evaluation of a component (in our case verified for laboratory scale fatigue test specimens with great accuracy) can be performed for its entire fatigue life, including the hardening and softening behavior, without using a conventional S~N curve based approach. Additionally results are presented related to fatigue evaluation of real reactor components such as of a pressurized water reactor (PWR) surge line (SL), under upset transient conditions. SLs of PWR experience complex thermal stratification due to the mixing of differential temperature flow from hot leg and pressurizer. A detailed parametric study of thermal stratification in SL is performed through both standalone computational fluid dynamics (CFD) analysis and fluid-structure-interaction based coupled CFD and heat transfer analysis. Results show that the mass flow rate in SL substantially affects the extent of its thermal stratification. The resulting thermal boundaries conditioned are used as inputs for thermal-mechanical stress analysis and component level fatigue evaluation. Fatigue evaluation of SL pipe under example loading conditions was performed using the above-mentioned evolutionary-plasticity based approach and ASME code (for in-air life) and NUREG-6909 (for PWR environment life) based approaches. Results show that the evolutionary plasticity based approach estimate substantially different life compared to the conventional ASME based approach. To show the entirety of the proposed evolutionary fatigue-modeling framework, this report includes the results presented in semi-annual March report (ANL/LWRS-17/01). Sections 2-5 of March report are directly included as Sections 2-5 in this report, without any significant changes. However, Sections 6-9 of this report present the work performed during March-September of 2017. Whereas, Sections 1 and 10 present the organization of this report and the summary and future work, respectively. This report (ANL/LWRS-17/03 Rev. 1) is a slightly revised version of the earlier published report (ANL/LWRS-17/03). In this revised version, some of the results and associated discussion have been corrected/updated.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Oxidation of Ammonia Catalyzed by a Molecular Iron Complex: Translating Chemical Catalysis to Mediated Electrocatalysis

Abstract Ammonia is a promising candidate in the quest for sustainable, clean energy. With its capacity to serve as an energy carrier, the oxidation of ammonia opens avenues for carbon‐neutral approaches to address worldwide growing energy needs. We report the catalytic chemical oxidation of ammonia by an Earth‐abundant transition metal complex, trans ‐ [LFe II (MeCN) 2 ][PF 6 ] 2 , where L is a macrocyclic ligand bearing four N ‐heterocyclic carbene (NHC) donors. Using triarylaminium radical cations in MeCN, up to 182 turnovers of N 2 per Fe were obtained from chemical catalysis with an extremely low loading of the Fe catalyst (0.043 mM, 0.004 mol % catalyst). This chemical catalysis was successfully transitioned to mediated electrocatalysis for the oxidation of ammonia. Molecular electrocatalysis by the Fe catalyst and the mediator ( p ‐MeOC 6 H 4 ) 3 N exhibited a catalytic half‐wave potential ( E cat/2 ) of 0.18 V vs [Cp 2 Fe] +/0 in MeCN, and achieved 9.3 turnovers of N 2 at an applied potential of 0.20 V vs [Cp 2 Fe] +/0 at −20 °C in controlled‐potential electrolysis, with a Faradaic efficiency of 75 %. Based on computational results, the catalyst undergoes sequential oxidation and deprotonation steps to form [LFe IV (NH 2 ) 2 ] 2+ , and thereafter bimetallic coupling to form an N−N bond.

Liu, Liang↗

DOE OSTI2024

Oxidation of Ammonia Catalyzed by a Molecular Iron Complex: Translating Chemical Catalysis to Mediated Electrocatalysis

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Palladium/Beta Zeolite Passive NOx Adsorbers (PNA): Clarification of PNA Chemistry and the Effects of CO and Zeolite Crystallite Size on PNA Performance

Model 0.3 wt% and 1 wt% Pd/Beta was synthesized with nano-sized Beta crystals (average size <50 nm) and defect-free large micrometer sized crystals with similar Si/Al ratios ~13 and 15. With the aid of FTIR we reveal the formation of at least two Pd(II)-NO and one Pd(I)-NO complexes upon NO adsorption on those materials under conditions relevant to PNA. Under higher NO pressures at room temperature, we detect the formation of the first palladium (II) dinitrosyl Pd(NO)2 complex, not observed previously on the solid supports or in organometallic compounds. O2 in dry streams promotes NO storage via additional formation of nitrosyl (NO+) ions; it also leads to stabilization of significant amounts of N2O3 in BEA pores. In the presence of water, NO storage capacity is dramatically lowered. However, in the presence of CO (which is always present in exhaust gas) the performance improves. With the aid of spectroscopy and PNA measurements we show that in the presence of CO stable mixed palladium(II) carbonyl nitrosyl complex [Pd(II)(CO)(NO)] is formed and responsible for enhanced NOx storage. This points to a general conclusion that the species responsible for NOx storage on various zeolites in the presence of water and CO, are in fact, Pd(II)(CO)(NO). Decreasing the Pd loading to 0.3 wt% improves Pd dispersion and NO/Pd storage ratio. We also demonstrate that varying crystal sizes of BEA leads to significant changes in the NOx release temperature as well as NO/Pd ratio. Larger, defect free crystals store more NOx and release it at higher temperature. Furthermore, larger crystals stay significantly more active for PNA after hydrothermal aging, losing very little activity compared with defective nanocrystals. High-field 27Al NMR results show that larger BEA crystals are more resistant to de-alumination upon hydrothermal aging (HTA), and thus are more attractive for PNA storage with Pd.

Khivantsev, Konstantin↗

DOE OSTI2025

Nuclear microreactor transient and load-following control with deep reinforcement learning

The economic feasibility of nuclear microreactors will depend on minimizing operating costs through advancements in autonomous control, especially when these microreactors are operating alongside other types of energy systems (e.g., renewable energy). This study explores the application of deep reinforcement learning (RL) for real-time drum control in microreactors, exploring performance in regard to load-following scenarios. By leveraging a point kinetics model with thermal and xenon feedback, we first establish a baseline using a single-output RL agent, then compare it against a traditional proportional–integral–derivative (PID) controller. This study demonstrates that RL controllers, including both single- and multi-agent RL (MARL) frameworks, can achieve similar or even superior load-following performance as traditional PID control across a range of load-following scenarios. In short transients, the RL agent was able to reduce the tracking error rate in comparison to PID by one half to one third. Over extended 300-minute load-following scenarios in which xenon feedback becomes a dominant factor, PID maintained better accuracy, but RL still remained within a 1% error margin despite being trained only on short-duration scenarios. This highlights RL’s strong ability to generalize and extrapolate to longer, more complex transients, affording substantial reductions in training costs and reduced overfitting. Furthermore, when control was extended to multiple drums, MARL enabled independent drum control as well as maintained reactor symmetry constraints without sacrificing performance---an objective that standard single-agent RL could not learn. We also found that, as increasing levels of Gaussian noise were added to the power measurements, the RL controllers were able to maintain lower error rates than PID, and to do so with at least 10% and upwards of 150% less control effort. These findings illustrate RL's potential for autonomous nuclear reactor control, laying the groundwork for future integration into high-fidelity simulations and experimental validation efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2015

Systematic Optimization of Long Gradient Chromatography Mass Spectrometry for Deep Analysis of Brain Proteome

Development of high resolution liquid chromatography (LC) is essential for improving the sensitivity and throughput of mass spectrometry (MS)-based proteomics. Here we present systematic optimization of a long gradient LC-MS/MS platform to enhance protein identification from a complex mixture. The platform employed an in-house fabricated, reverse phase column (100 μm x 150 cm) coupled with Q Exactive MS. The column was capable of achieving a peak capacity of approximately 700 in a 720 min gradient of 10-45% acetonitrile. The optimal loading level was about 6 micrograms of peptides, although the column allowed loading as many as 20 micrograms. Gas phase fractionation of peptide ions further increased the number of peptide identification by ~10%. Moreover, the combination of basic pH LC pre-fractionation with the long gradient LC-MS/MS platform enabled the identification of 96,127 peptides and 10,544 proteins at 1% protein false discovery rate in a postmortem brain sample of Alzheimer’s disease. As deep RNA sequencing of the same specimen suggested that ~16,000 genes were expressed, current analysis covered more than 60% of the expressed proteome. Further improvement strategies of the LC/LC-MS/MS platform were also discussed.

Wang, Hong↗

DOE OSTI2025

Maximizing long-term biohydrogen production with Clostridium thermocellum for high solids conversion of lignocellulosic biomass

Biological hydrogen production from lignocellulosic biomass sustainably couples organic waste reduction with renewable energy generation. Efficient conversion is challenged by the structural complexity of lignocellulose and resulting recalcitrance to enzymatic degradation. Clostridium thermocellum natively breaks down biomass with highly effective hemi-/cellulases systems (i.e., cellulosomes) and generates hydrogen in anaerobic cultivation, creating a compelling platform for lignocellulosic biohydrogen production. Achieving commercially viable production rates requires balancing high biomass loading and throughput against uniform mixing conditions required for enzyme dispersion, pH and temperature control, and efficient hydrogen and metabolite removal in continuous operation. To address these barriers to process intensification, we implemented novel reactor and process designs for high-solids lignocellulosic biomass fermentations using the C. thermocellum KJC19-9 strain, genetically engineered for co-utilization of cellulose and hemicellulose sugars (i.e., xylose). Via computational fluid dynamics (CFD) modeling and experimental validation, we achieved a >50% improvement in biohydrogen production with an improved anchor-type impeller morphology, coupled to a threefold reduction in agitation rate. To further reduce rheological constraints and accumulation of toxic metabolites, we then transitioned the process to sequencing fed-batch operation. The resulting process generated 24.87 L H 2 L −1 from 160 g L −1 of deacetylated and mechanically refined (DMR)-pretreated corn stover biomass over 16 days while solubilizing >95% of influent cellulose and hemicellulose, setting a new performance benchmark for continuous production of biohydrogen from lignocellulose.

08 HYDROGEN↗

DOE OSTI2024

Autonomous Anomaly Detection for MPC Forecasts of HVAC Systems in Residential Communities

The use of residential heating, ventilation, and air conditioning (HVAC) to shift peak demand or provide ancillary services is a potential solution in the presence of older grids and distributed renewables. However, to ensure the efficient use of devices, utilities need to accurately forecast the load and adopt error correction schemes when necessary. While significant theoretical research exists in the area of predictive control of HVAC, little experimental evidence exists. The lack of experimental data in turn causes researchers to be unprepared for unsystematic errors which emerge due to the higher complexity of the data generating process. This study offers an anomaly detection methodology that uses unsupervised machine learning algorithms to detect and isolate these errors with different forecast error ranges. The results of anomaly detection procedure can then be used for error correction and would eventually help develop better predictive controllers. The methodology is tested using real world data from a smart neighborhood that currently operates in Atlanta. GA.

Lebakula, Viswadeep↗

DOE OSTI2019

Initial DOE SNF Standardized Canister Storage Configuration Alternatives Study

This study looks at storage configuration alternatives for United States Department of Energy (DOE) Spent Nuclear Fuel (SNF) Standardized Canisters loaded with DOE-owned SNF. The focus of the study is for the DOE SNF Standardized Canisters that would be packaged in the Idaho Nuclear Technology and Engineering Center (INTEC) area at Idaho National Laboratory (INL), but its general findings are useful across the DOE Complex. The study considered storage in existing facilities, modified existing facilities, new facilities, and new modular systems. The existing INTEC facilities considered in the study include the CPP-603 Irradiated Fuel Storage Facility (IFSF), the CPP-749 Underground Fuel Storage Facility (UFSF), the CPP-666 SNF Wet Storage Basin Facility, CPP-1774 Three Mile Island (TMI) Independent Spent Fuel Storage Facility (ISFSF), and the CPP-2707 Cask Pad Facility. The new facilities considered in the study include the Foster Wheeler designed Idaho Spent Fuel (ISF) Independent Spent Fuel Storage Installation (ISFSI) and some conceptual designs. The new modular systems considered in the study include Holtec International’s HI-STAR/HI-STORM, NAC International’s MAGNASTOR/UMS/MPC and Orano TN’s MATRIX/NUHOMS. Based on considerations of various factors, including but not limited to capacity, impact to facility operations, capital costs, expenditure rate, licensing issues, agreements with the State of Idaho, and road ready conditions, new modular storage systems from commercial vendors may have clear advantages over other storage alternatives. This is further supported by recent experience with West Valley Demonstration Project (WVDP) storage project for High Level Waste Glass canisters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Sample problems for Section III, Division 5 design by inelastic analysis of Grade 91 components

This report works through two sample design analyses of representative Grade 91 components using the ASME Boiler & Pressure Vessel Code Section III, Division 5, Appendix HBB-T rules for the strain and deformation and creep-fatigue design criteria using a design by inelastic analysis approach. The component geometries and loadings were selected to span a wide variety of potential applications. The sample components are an endplate geometry, which is fairly representative of typical pressure vessel construction, and a core block, representing a critical component in a heat pipe microreactor, which has a complicated geometry and complex thermal stress history. These sample problems serve several functions. First, they are complete worked examples of how to apply the current design by inelastic analysis rules. Second, they serve as test cases to evaluate the current rules and provide feedback on how they could be optimized to deal with complicated component geometries or to be better automated in modern finite element analysis software. Finally, the analysis here uses an inelastic constitutive model for Grade 91 developed by Argonne National Laboratory and proposed for inclusion in the ASME Boiler & Pressure Vessel Code Section III, Division 5 rules as a reference constitutive model. Using this constitutive model in the sample problem analyses tests the model in the context of the ASME Code rules. The final conclusions of this report are that the material model and the current Code rules are satisfactory, but that the Code rules could be optimized to simplify automation and reduce over conservatism. Future work should address the specific optimization topics discussed in this report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Hamilton: Flexible, Open Source $10 Wireless Sensor System for Energy Efficient Building Operation

Sensors for improving building performance are rapidly populating the market, driven in part by the drive to reduce greenhouse gas emissions resulting from energy production as well as improve the interior environment for healthy and more productive spaces. UC Berkeley has led wireless sensor development over the past 25 years (e.g., Telos mote), with the Hamilton (named after Alexander Hamilton on the US $10 bill) as the most recent. The Hamilton sensor was designed as a low-cost high-performance sensor that is modular and interoperable. The objective of the Hamilton project was to create, evaluate and establish the technological foundations for secure and easy to deploy building energy efficiency applications utilizing pervasive, low-cost wireless sensors integrated with traditional Building Management Systems (BMS), consumer-sector building components, and powerful data analytics. The project included iterative hardware design, incorporating a high-performance database (BTrDb, http://btrdb.io/), creating and iterating the development of secure data middleware (BOSSwave, WAVE/WAVEMQ), working with and pushing the development of an open-source tiny operating system RiotOS, and implementing and improving protocols such as Thread/OpenThread and TCP/IP. The hardware benefited from careful design to drive down the cost; the design included a System-on-a-Chip (SoC), chip antenna, single crystal and five passive components. Careful design of the operating system created a low-power design to enable a long life with small batteries. The hardware included several sensors: temperature, radiant temperature, relative humidity, magnetometer, accelerometer, and light, with an optional occupancy (Passive InfraRed) sensor. The project was the basis of several applications, both internal to the research team and other researchers and professionals at other institutions. Several applications used the sensor hardware as the basis for other complex devices. Other applications used the sensors to improve building performance through interoperating with the building Heating Ventilation and Air-Conditioning (HVAC) system, such as using occupancy and/or distributed temperature sensing to reduce HVAC zone energy while still providing thermal comfort and to reduce peak loads in small commercial buildings. We demonstrated cloud-based energy analytics, implemented a schedule and a Model Predictive Controller in a small commercial building to optimize HVAC energy, occupancy and electricity price. Initial integration of these technological innovations was performed through the creation of execution containers containing the WAVE agent and various driver, proxy, or building system function logic. The research added to the understanding of efficient sensor hardware, secure middleware, time-series data management (high performance database), efficient communication protocols, and interoperating with applications and building systems. The project showed the technical effectiveness and economic feasibility of creating a low-cost, modular, and easy-to-deploy sensor. Through conversations with multiple end users, the research team discovered that many customers wanted data management and services in addition to the sensors. HamiltonIOT developed packages of sensors, border router, and data services to provide a seamless “plug-and-play” sensor deployment. Some customers were willing to pay for higher quality sensors (such as light); some customers wanted a robust enclosure (waterproof).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Simulink Modeling and Dynamic Study of Fixed-Speed, Variable-Speed, and Ternary Pumped Storage Hydropower

Pumped Storage Hydropower (PSH) is one of the most popular energy storage technologies in the world. It uses an upper reservoir to store water which can be later used during high-demand. In the United States, most of the energy storage capability actually corresponds to PSH. Moreover, PSH also brings multiple benefits to grid operation. This report presents the Simulink models of three common PSH technologies: Fixed-Speed (FS), Variable-Speed (VS), and Ternary (T)-PSH. These models are available to the general public on this GitHub repository, which contains the MATLAB model initialization files, the Simulink model files, and supplementary MATLAB code used to obtain the figures in this work. For each PSH model, an introductory description of the model components and other relevant functionalities are provided. For further information regarding the models and the initialization parameters, the reader is referred to the shared files in the repository. This report also presents the dynamic behavior of each model. The response of such models to a load event is analyzed and matched with each model's features. A custom IEEE 39 bus case is employed for the FS and T-PSH simulations, while the VS-PSH is simulated on a simplified three-bus test system due to the computational complexity of the model. For the T-PSH, the steady-state and the switching between several operating modes are also studied in this work.

13 HYDRO ENERGY↗

DOE OSTI2023

Final Seismic Shake Table Test Plan

The Spent Fuel Waste Disposition (SFWD) program is planning to conduct a full-scale seismic shake table test on the dry storage systems of spent nuclear fuel (SNF) to close the gap related to seismic loads on fuel assemblies in dry storage systems. This test will allow for quantifying the strains and accelerations on surrogate fuel assembly hardware and cladding during earthquakes of different magnitudes and frequency content. Full-scale testing is needed because a dry storage system is a complex and highly nonlinear system making it hard to predict (model) the responses to seismic excitations. The non-linearity arises from the multiple spatial gaps in the system – between fuel rods and the basket, between the basket and dry storage canister, between the dry storage canister and the storage cask (overpack), and ventilation gaps. The non-linearities pose significant limitations on the value of tests with scaled systems.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Design and Characterization of a Lens-Coupled System for Dynamic X-Ray Diffraction

X-ray diffraction (XRD) is a necessary technique for understanding states of materials under static and dynamic loading conditions. The higher-pressure Equation of State (EOS) of many materials can only be explored via shock or ramp compression at temperatures and pressures of interest. While static XRD work has yielded EOS measurements in the 100 - 200 GPa regime, dynamic X-ray diffraction (DXRD) can explore EOS phases in the TPa regime, which closely resembles inner-core planetary conditions. DXRD hinges on the ability to measure the exact phase or phase change of a material while under dynamic loading conditions. Macroscopic diagnostic systems (e.g. velocimetry and pyrometry) can infer a phase change but not identify the specific phase entered by a material. While microscopic (atomic-level) diagnostic systems (e.g. DXRD) have been designed and implemented in Department of Energy’s (DOE) National Laboratories complex, the unique nature of Sandia National Laboratories’ Pulsed Power Facility (Z Machine) prohibits the use of such devices. The destructive nature of Z experiments presents a challenge to data capture and retrieval. Furthermore there are electromagnetic interference, X-ray background, and mechanical constraints to consider. Thus, a multi-part X-ray diagnostic for use on the Z Machine and Z-Beamlet Laser system has been designed and analyzed. Portions of this new DYnamic SCintillator Optic (DYSCO) have been built, tested and fielded. A data analysis software has been written. Finally, the radiance profile of the DYSCO’s scintillator has been characterized through experiments performed at the University of Arizona.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Distribution System State Estimation in the Presence of High Solar Penetration

In recent years, the low-to-medium voltage distribution networks are experiencing rising levels of distributed energy resources, including renewable generation, along with improved sensing, communication and automation infrastructure. As such, state estimation methods for distribution systems are becoming increasingly relevant as a means to enable better control strategies that can both leverage the benefits and mitigate the risks associated with high penetration of variable and uncertain distributed generation resources. Primary challenges of this problem include modeling complexities (nonlinear non-convex power-flow equations), limited availability of sensor measurements, and high penetration of uncertain renewable generation. This paper formulates the distribution system state estimation as a nonlinear weighted least squares problem, based on sensor measurements as well as forecasts data (both load and generation). We investigate the sensitivity of state estimator accuracy to (load/generation) forecast uncertainties, sensor accuracy, and sensor coverage levels.

Distribution system state estimation, nonlinear op↗

DOE OSTI2023

Yaw-Augmented Control for Wind Farm Power Tracking: Preprint

This paper presents an inner-outer control loop structure which uses wake steering (yaw control) to augment pitch control for wind farms to track a power reference signal. The outer-loop yaw controller employs a recently proposed dynamic yaw model with a time-varying graph structure that accounts for dynamic changes in the farm wake interactions due to the yaw action of upstream turbines. The wake interactions within the model include the physics of the streamwise and lateral wake evolution, which collectively determine its impact on downstream turbines. The inner-loop employs a compensation scheme to account for the slow timescale effects of the yaw control actions within the faster timescale pitch control. The controller is applied to track two power trajectories (typical of secondary frequency regulation signals) using a large eddy simulation wind farm plant. The results demonstrate that the additional control authority from yaw provides some added benefit in reducing the required turbine derates needed for wind farms to track transient power increases in the proposed setting. However, the benefit decreases and pitch control alone is sufficient when the turbines are derated beyond a certain level. These findings suggest that augmenting pitch control with yaw may provide financial incentives in terms of allowing wind farms to maximize power supply to the bulk power market while still providing regulation services. Further work is needed analyze the costs versus benefits of the additional control complexity versus bandwidth in augmenting pitch control with wake steering offers in these applications.

active power control↗

DOE OSTI2021

Low Carbon Technology Strategies: Large Office

This document includes steps that building owners and operators can implement to achieve smart, healthy, and low-carbon large office buildings within their existing building portfolios. Large offices are typically over 50,000 square feet and often include complex heating and cooling systems.

analytics↗

DOE OSTI2017

Optimal scheduling and its Lyapunov stability for advanced load-following energy plants with CO 2 capture

In this study, a two-level control methodology consisting of an upper-level scheduler and a lower-level supervisory controller is proposed for an advanced load-following energy plant with CO 2 capture. With the use of an economic objective function that considers fluctuation in electricity demand and price at the upper level, optimal scheduling of energy plant electricity production and carbon capture with respect to several carbon tax scenarios is implemented. The optimal operational profiles are then passed down to corresponding lower-level supervisory controllers designed using a methodological approach that balances control complexity with performance. Finally, it is shown how optimal carbon capture and electricity production rate profiles for an energy plant such as the integrated gasification combined cycle (IGCC) plant are affected by electricity demand and price fluctuations under different carbon tax scenarios. As a result, the paper also presents a Lyapunov stability analysis of the proposed scheme.

01 COAL, LIGNITE, AND PEAT↗