Nonlinear Dynamic Model-Based Multiobjective Sensor Network Design Algorithm for a Plant with an Estimator-Based Control System

Paul, Prokash; Bhattacharyya, Debangsu; Turton, Richard; Zitney, Stephen E.

doi:10.1021/acs.iecr.6b04020

Cited by 12 publications

(5 citation statements)

References 52 publications

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“…While there is hardly any current state-of-the-art measurement technology for real-time accurate measurement of the lean solvent loading, an estimator-based approach where the estimates are updated using measurements, whenever available, can be considered. Such estimation approaches typically work using a predictor–corrector type approach where the measurement update (the correction step) is carried out whenever the measurement data are available. , The optimal schedule for the CO 2 capture set points was taken from Bankole et al The flue gas flow rate was scaled to be consistent with a 0.5 MW equivalent pulverized coal power plant, and its composition was modified to match the pilot-plant model presented in this work. However, the variability in the flue gas flow rate was similar to the original values.…”

Section: Results and Discussionmentioning

confidence: 99%

Dynamic Data Reconciliation and Validation of a Dynamic Model for Solvent-Based CO₂ Capture Using Pilot-Plant Data

Chinen

Morgan

Omell

et al. 2019

Ind. Eng. Chem. Res.

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This paper is focused on the development and validation of a dynamic model for a monoethanolamine-based CO2 capture unit. Starting with a rigorous steady-state process model, the dynamic model is developed in Aspen Plus Dynamics using a modified Murphree efficiency approach and is validated using dynamic data collected from the National Carbon Capture Center in Wilsonville, Alabama. The dynamic test runs were designed with due consideration of process excitation and process nonlinearities constrained by the available time to conduct the test runs and implement the experimental designs in the plant control system. The experimental data include solvent composition and loading. Because the experimental data were found to violate mass and energy balances, filtering algorithms coupled with dynamic data reconciliation techniques were used. Without adjusting any model parameters, the dynamic model satisfactorily predicted the dynamic response of CO2 capture due to step changes in the solvent flow rate, flue gas flow rate, and steam flow rates. Transient studies show that the process gain and time constants can considerably change depending on the direction of the disturbance or manipulated variables, indicating process nonlinearities. Because of a storage tank between the absorber and stripper, the time constant of the full plant can be considerably longer than the time constants of the absorber or stripper individually. Furthermore, impact of the control system on the process efficiency while following an optimal CO2 capture schedule was also studied.

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Section: Results and Discussionmentioning

confidence: 99%

Dynamic Data Reconciliation and Validation of a Dynamic Model for Solvent-Based CO₂ Capture Using Pilot-Plant Data

Chinen

Morgan

Omell

et al. 2019

Ind. Eng. Chem. Res.

Self Cite

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“…Therefore, an ROM is developed through balanced truncation by using Hankel singular values. This method helps to preserve the stability of the model and can still reduce the global error bound [11,39]. The form of this model is given by: .…”

Section: Caes Model Validationmentioning

confidence: 99%

Techno-Economic Analysis and Optimization of a Compressed-Air Energy Storage System Integrated with a Natural Gas Combined-Cycle Plant

et al. 2023

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To address the rising electricity demand and greenhouse gas concentration in the environment, considerable effort is being carried out across the globe on installing and operating renewable energy sources. However, the renewable energy production is affected by diurnal and seasonal variability. To ensure that the electric grid remains reliable and resilient even for the high penetration of renewables into the grid, various types of energy storage systems are being investigated. In this paper, a compressed-air energy storage (CAES) system integrated with a natural gas combined-cycle (NGCC) power plant is investigated where air is extracted from the gas turbine compressor or injected back into the gas turbine combustor when it is optimal to do so. First-principles dynamic models of the NGCC plant and CAES are developed along with the development of an economic model. The dynamic optimization of the integrated system is undertaken in the Python/Pyomo platform for maximizing the net present value (NPV). NPV optimization is undertaken for 14 regions/cases considering year-long locational marginal price (LMP) data with a 1 h interval. Design variables such as the storage capacity and storage pressure, as well as the operating variables such as the power plant load, air injection rate, and air extraction rate, are optimized. Results show that the integrated CAES system has a higher NPV than the NGCC-only system for all 14 regions, thus indicating the potential deployment of the integrated system under the assumption of the availability of caverns in close proximity to the NGCC plant. The levelized cost of storage is found to be in the range of 136–145 $/MWh. Roundtrip efficiency is found to be between 74.6–82.5%. A sensitivity study with respect to LMP shows that the LMP profile has a significant impact on the extent of air injection/extraction while capital expenditure reduction has a negligible effect.

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“…A sensor is a kind of state measurement device. On some special occasions, the installation of sensor can also be avoided, and the amount to be measured can be calculated by introducing an observer [18,19]. e determination of the controlled object is generally related to the purpose of the design control.…”

Section: Dynamic Mathematical Model Of Induction Motor Inmentioning

confidence: 99%

Nonlinear Control of Induction Motor Based on Network Control System

Jin

2022

Mobile Information Systems

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With the rapid development of network communication technology and computer technology, network control system has been applied in many different fields. Networked AC induction motor is controlled by a communication network to realize data transmission. This paper mainly studies the nonlinear control of induction motor based on network control system. In order to solve the nonlinear problem of AC induction motor, this paper adopts the method of the linear resolve coupling, and combined with the characteristics of the Internet, establishes the mathematical model of the AC induction motor, and considers the use of the system parameter perturbation to construct the mathematical model of the AC induction motor. Aiming at the problems of system parameter perturbation and network-induced delay in networked AC induction motor control system, the robust control of networked AC induction motor control system is studied. The experimental results show that the proposed control strategy can achieve asymptotic stability of the system with parameter perturbation under the action of the controller and can achieve asymptotic stability even with external disturbance. Compared with control strategies 1 and 2, the adjustment time of the speed waveform oversetting phenomenon is about 0.18 s and 0.26 s, and the adjustment time of the control strategy proposed in this paper is only 0.06 s. It is shown that the nonlinear control method of induction motor based on network control system can significantly improve the validity and stability of the system model.

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Nonlinear Dynamic Model-Based Multiobjective Sensor Network Design Algorithm for a Plant with an Estimator-Based Control System

Cited by 12 publications

References 52 publications

Dynamic Data Reconciliation and Validation of a Dynamic Model for Solvent-Based CO₂ Capture Using Pilot-Plant Data

Dynamic Data Reconciliation and Validation of a Dynamic Model for Solvent-Based CO₂ Capture Using Pilot-Plant Data

Techno-Economic Analysis and Optimization of a Compressed-Air Energy Storage System Integrated with a Natural Gas Combined-Cycle Plant

Nonlinear Control of Induction Motor Based on Network Control System

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Nonlinear Dynamic Model-Based Multiobjective Sensor Network Design Algorithm for a Plant with an Estimator-Based Control System

Cited by 12 publications

References 52 publications

Dynamic Data Reconciliation and Validation of a Dynamic Model for Solvent-Based CO2 Capture Using Pilot-Plant Data

Dynamic Data Reconciliation and Validation of a Dynamic Model for Solvent-Based CO2 Capture Using Pilot-Plant Data

Techno-Economic Analysis and Optimization of a Compressed-Air Energy Storage System Integrated with a Natural Gas Combined-Cycle Plant

Nonlinear Control of Induction Motor Based on Network Control System

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Dynamic Data Reconciliation and Validation of a Dynamic Model for Solvent-Based CO₂ Capture Using Pilot-Plant Data

Dynamic Data Reconciliation and Validation of a Dynamic Model for Solvent-Based CO₂ Capture Using Pilot-Plant Data