Estimation-based model predictive control of an electrically-heated steam methane reforming process

Digital Chemical Engineering, Journal Year: 2024, Volume and Issue: 11, P. 100153 - 100153

Published: April 24, 2024

The surge in demand for hydrogen (H2) across diverse sectors, including clean energy transportation and chemical synthesis, underscores the need a thorough investigation into H2 production dynamics development of effective controllers industrial applications. This paper focuses on an electrically heated steam methane reforming (SMR) process production, offering advantages such as enhanced environmental sustainability, compactness, efficiency, controllability compared to conventional methods. Electric heating entire system allows adjustments current control reactor temperature, thereby impacting rates. However, accurately modeling presents formidable challenge, complex models with high precision are computationally unsuitable real-time integration. Considering these factors, accurate efficient first-principles-based lumped-parameter model is developed provide dependable estimation electrically-heated reformer. validated experimentally then utilized predictive controller (MPC). To obtain necessary state estimate information MPC, extended Luenberger observer (ELO) method employed variables from limited, infrequent delayed measurements gas-phase outlet stream frequent temperature. Simulation comparisons proportional-integral (PI) reveal much faster response achieving desired rate under estimation-based MPC. Additionally, simulations demonstrate robustness variability decrease catalyst activation energy, commonly encountered SMR process, highlighting its effectiveness maintaining stable operation varying conditions.

Language: Английский

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Deep learning performance prediction for solar-thermal-driven hydrogen production membrane reactor via bayesian optimized LSTM

International Journal of Hydrogen Energy, Journal Year: 2024, Volume and Issue: 82, P. 1402 - 1412

Published: Aug. 9, 2024

Language: Английский

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Feedback control of an experimental electrically-heated steam methane reformer

Process Safety and Environmental Protection, Journal Year: 2024, Volume and Issue: 206, P. 469 - 488

Published: May 18, 2024

Language: Английский

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Modeling and design of a combined electrified steam methane reforming-pressure swing adsorption process

Process Safety and Environmental Protection, Journal Year: 2024, Volume and Issue: 209, P. 111 - 131

Published: July 29, 2024

Language: Английский

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Machine learning-based predictive control of an electrically-heated steam methane reforming process

Digital Chemical Engineering, Journal Year: 2024, Volume and Issue: 12, P. 100173 - 100173

Published: July 23, 2024

Hydrogen plays a crucial role in improving sustainability and offering clean efficient energy carrier that significantly reduces greenhouse gas emissions. However, the primary method of industrial hydrogen production, steam methane reforming (SMR), relies on combustion hydrocarbons as heating source for reactions, resulting significant carbon To address this issue, an experimental setup electrically-heated reformer (e-SMR) has been constructed at UCLA, lumped first-principle dynamic process model was built based parameters estimated from data previous study. Subsequently, implemented into computational predictive control (MPC) scheme, successfully driving production rate to desired setpoint. While these works are important pave way developing MPC large-scale e-SMR processes, may not accurately reflect actual behavior, particularly behavior changes with time. Therefore, development establishment adaptive data-driven approach implementing is necessary. need, present work investigates construction recurrent neural network (RNN) models in-depth, utilizing experimentally-validated model. Specifically, long short-term memory (LSTM) layer utilized RNN effectively capture complex correlations long-term sequential data. LSTM-based employed design MPC, its performance evaluated through comparison proportional–integral (PI) control. potential disturbances variability typical process, three distinct approaches were developed: integrator, real-time online retraining (transfer learning), offset-free MPC. These eliminated offset caused by disturbances. Overall, study underscores effectiveness dynamics process. It also outlines strategies employing RNN-based multiple general processes partially infrequent delayed measurement feedback. This valuable scenarios where new be challenging.

Language: Английский

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Energy efficiency and productivity of a Pressure Swing Adsorption plant to purify bioethanol: Disturbance attenuation through geometric control

Digital Chemical Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 100209 - 100209

Published: Dec. 1, 2024

Language: Английский

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Kinetics and catalysis: Direct mechanisms, autonomous reaction pathways, and the constitutive rate function

The Canadian Journal of Chemical Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 23, 2024

Abstract Rate functions of catalytic reactions are derived from direct mechanisms based on an adsorption theory and a kinetic mathematical model. Often, more than one mechanism corresponds to overall chemical reaction. Since each can potentially produce distinct rate function, it is likely that independent function describes the This appears be fundamental property structure kinetics heterogeneous catalysis this article addresses possibility via examination steam methane reforming ammonia synthesis.

Language: Английский

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