The Experts below are selected from a list of 102 Experts worldwide ranked by ideXlab platform
Joha Akesso - One of the best experts on this subject based on the ideXlab platform.
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nonlinear model predictive control of a co2 post combustion Absorption Unit
Chemical Engineering & Technology, 2012Co-Authors: Joha Akesso, Carl D Laird, G Laveda, K Prols, Hubertus Tummeschei, Stephane Velu, Yu ZhuAbstract:A dynamic model of a chemical CO2 Absorption process with aqueous monoethanolamine (MEA) is presented, validated against experimental data. Based on the validated model, a reduced-order model is developed, suitable for an online optimization control strategy. The objective of the optimization is to enable fast adap- tations to changes in operating conditions of the power plant, while minimizing the energy consumption in the operation of the CO2 separation plant. The results indicate that model-based online optimization is a feasible technology for control of CO2 separation systems.
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dynamic model of a post combustion Absorption Unit for use in a non linear model predictive control scheme
Energy Procedia, 2011Co-Authors: Katri Prolss, Stephane Velu, Hubertus Tummeschei, Joha AkessoAbstract:With an increasing demand on load flexibility in power supply networks, advanced control systems for plants with carbon capture Units gain in significance. Minimizing the energy demand for carbon dioxide removal under these circumstances is a major task of such a control strategy. In this work a dynamic model in Modelica of a chemical Absorption process run with an aqueous monoethanolamine (MEA) is developed. Starting from a rather detailed dynamic model of the process, model reduction is performed based on physical insight. The reduced model computes distinctly faster, shows similar transient behavior and reflects trends for optimal steady-state operations reported in the literature. The model is intended to be used in the framework of JModelica.org, a platform supporting non-linear dynamic optimization.
Guoqiang Zhang - One of the best experts on this subject based on the ideXlab platform.
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exergy and environmental assessments of a novel trigeneration system taking biomass and solar energy as co feeds
Applied Thermal Engineering, 2016Co-Authors: Hongqiang Li, Xiaofeng Zhang, Rong Zeng, Guoqiang ZhangAbstract:Abstract This paper presents an exergy and environmental analysis of a novel trigeneration system with biomass and solar energy coupling utilization. The novel trigeneration system mainly consists of a biomass gasifier, a solar collector, an internal combustion engine, an Absorption Unit and a liquid desiccant Unit. The solar collector provides steam for biomass gasification process, and the product gas is fed into the internal combustion engine for generating electricity. The flue gas is utilized by the Absorption Unit for cooling production, and heat exchanger for domestic hot water successively. The jacket water is considered as the low heat resource for generating desiccant capacity. The exergy efficiency, exergy destruction and CO 2 emissions are analyzed under different parameters. The results show that the total exergy efficiency of trigeneration system in the case study is determined to 19.21%, and the solar energy contributes to decrease the consumption of biomass. It is also found that the highest exergy destruction takes place in the gasifier, follow by internal combustion engine and gas/water heat exchanger. In addition, the introduction of biomass and solar energy alleviates the impact on environment, mainly reduces the CO 2 emissions in kg/MW h; the CO 2 emissions decrease evidently compared with separated generation system.
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global optimization of Absorption chiller system by genetic algorithm and neural network
Energy and Buildings, 2002Co-Authors: T T Chow, Guoqiang Zhang, C L SongAbstract:The optimal use of fuel and electricity in a direct-fired Absorption chiller system is important in achieving economical operation. Previous work on the control schemes mainly focused on the component local feedback control. A system-based control approach, which allows an overall consideration of the interactive nature of the plant, the building and their associated variables is seen to be the right direction. This paper introduces a new concept of integrating neural network (NN) and genetic algorithm (GA) in the optimal control of Absorption chiller system. Based on a commercial Absorption Unit, neural network was used to model the system characteristics and genetic algorithm as a global optimization tool. The results appear promising.
Yu Zhu - One of the best experts on this subject based on the ideXlab platform.
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nonlinear model predictive control of a co2 post combustion Absorption Unit
Chemical Engineering & Technology, 2012Co-Authors: Joha Akesso, Carl D Laird, G Laveda, K Prols, Hubertus Tummeschei, Stephane Velu, Yu ZhuAbstract:A dynamic model of a chemical CO2 Absorption process with aqueous monoethanolamine (MEA) is presented, validated against experimental data. Based on the validated model, a reduced-order model is developed, suitable for an online optimization control strategy. The objective of the optimization is to enable fast adap- tations to changes in operating conditions of the power plant, while minimizing the energy consumption in the operation of the CO2 separation plant. The results indicate that model-based online optimization is a feasible technology for control of CO2 separation systems.
Stephane Velu - One of the best experts on this subject based on the ideXlab platform.
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nonlinear model predictive control of a co2 post combustion Absorption Unit
Chemical Engineering & Technology, 2012Co-Authors: Joha Akesso, Carl D Laird, G Laveda, K Prols, Hubertus Tummeschei, Stephane Velu, Yu ZhuAbstract:A dynamic model of a chemical CO2 Absorption process with aqueous monoethanolamine (MEA) is presented, validated against experimental data. Based on the validated model, a reduced-order model is developed, suitable for an online optimization control strategy. The objective of the optimization is to enable fast adap- tations to changes in operating conditions of the power plant, while minimizing the energy consumption in the operation of the CO2 separation plant. The results indicate that model-based online optimization is a feasible technology for control of CO2 separation systems.
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dynamic model of a post combustion Absorption Unit for use in a non linear model predictive control scheme
Energy Procedia, 2011Co-Authors: Katri Prolss, Stephane Velu, Hubertus Tummeschei, Joha AkessoAbstract:With an increasing demand on load flexibility in power supply networks, advanced control systems for plants with carbon capture Units gain in significance. Minimizing the energy demand for carbon dioxide removal under these circumstances is a major task of such a control strategy. In this work a dynamic model in Modelica of a chemical Absorption process run with an aqueous monoethanolamine (MEA) is developed. Starting from a rather detailed dynamic model of the process, model reduction is performed based on physical insight. The reduced model computes distinctly faster, shows similar transient behavior and reflects trends for optimal steady-state operations reported in the literature. The model is intended to be used in the framework of JModelica.org, a platform supporting non-linear dynamic optimization.
Hubertus Tummeschei - One of the best experts on this subject based on the ideXlab platform.
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nonlinear model predictive control of a co2 post combustion Absorption Unit
Chemical Engineering & Technology, 2012Co-Authors: Joha Akesso, Carl D Laird, G Laveda, K Prols, Hubertus Tummeschei, Stephane Velu, Yu ZhuAbstract:A dynamic model of a chemical CO2 Absorption process with aqueous monoethanolamine (MEA) is presented, validated against experimental data. Based on the validated model, a reduced-order model is developed, suitable for an online optimization control strategy. The objective of the optimization is to enable fast adap- tations to changes in operating conditions of the power plant, while minimizing the energy consumption in the operation of the CO2 separation plant. The results indicate that model-based online optimization is a feasible technology for control of CO2 separation systems.
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dynamic model of a post combustion Absorption Unit for use in a non linear model predictive control scheme
Energy Procedia, 2011Co-Authors: Katri Prolss, Stephane Velu, Hubertus Tummeschei, Joha AkessoAbstract:With an increasing demand on load flexibility in power supply networks, advanced control systems for plants with carbon capture Units gain in significance. Minimizing the energy demand for carbon dioxide removal under these circumstances is a major task of such a control strategy. In this work a dynamic model in Modelica of a chemical Absorption process run with an aqueous monoethanolamine (MEA) is developed. Starting from a rather detailed dynamic model of the process, model reduction is performed based on physical insight. The reduced model computes distinctly faster, shows similar transient behavior and reflects trends for optimal steady-state operations reported in the literature. The model is intended to be used in the framework of JModelica.org, a platform supporting non-linear dynamic optimization.
