In this work, plantwide control of an absorption/stripping CO 2 capture process using monoethanol-amine was investigated using dynamic simulation. In this system, CO 2 removal ratio is influenced by operating variables such as lean solvent rate and lean solvent loading, which is in-turn determined by reboiler duty in the stripper. Moreover, we found that the long-term stability of the system cannot be achieved unless the water balance is properly maintained. Hence the following control structure was proposed. In this scheme, the CO 2 removal target is guaranteed using the lean solvent feed rate to the top of the absorber column. The overall water inventory was maintained by controlling the liquid level in the reboiler of the stripping column using makeup water. In order to operate the process with an appropriate lean solvent loading, the temperature at the bottom of stripper is controlled by the reboiler duty. This control structure was tested by disturbances involving inlet flue gas flow, CO 2 concentrations, and H 2 O concentrations as well as changes in removal targets. Dynamic simulations showed that the system can achieve removal targets and stabilize quickly while keeping optimum lean loading constant. To ensure minimum energy consumption, optimizing control can be carried out by adjusting the set point of the reboiler temperature.

Ind. Eng. Chem. Process Des. Dev. 1986, 25, 809-814 809 mi = function of the acentric factor for the correlation of a N = number of moles p i = Mathias polar parameter P = pressure R = ideal gas constant T = temperature TI = reduced temperature u = molar liquid volume of the mixture vi = molar liquid volume of pure component i xi = mole fraction of component i in the liquid phase 2 = compressibility factor of the mixture 2, = compressibility factor of pure component i Greek Letters ai( TI) = temperature-dependent part of parameter ai y L = activity coefficient of component i in the mixture y i m = infinite-dilution activity coefficient of component i 7 = a/bRT 'pi = fugacity coefficient of component i in the mixture q,* = fugacity coefficient of pure component i Subscripts i, j = component i or j k = either a pure component (k = i ) or a mixture (k = 4) below the critical temperature 0 = property at zero pressure Literature Cited Chang, E.; Calado. J. C. 0.; Street, W. B. J . Chem. Eng. Data 1982, 27, 293. Fredenslund, A.; Gmehling, J.; Rasmussen, P. Vapor-LiquM Equilibrie Using UNIFAC. A Group Conhlbufbn Method; Elsevier: Amsterdam, 1977. Gibbons, R. M.; Laughton. A. P. J . Chem. Soc., Faraday Trans. 2 1984, 80, 1019. Gmehling, J.; Onken, U.; Artl, W. Vapor-Liquid Equilibria Data Collection; DECHEMA Chemistry Data Series I ; Verlag Chemie: Frankfurt/Main, FRO, 1977. Gmehling, J.; Rasmussen. P.; Fredenslund, A. Ind. Eng . Chem. Process Des. D e v . 1982, 27, 118. Hayden, J. G.; O'Connell, J. P. Ind. Eng. Chem. Process Des. Dev. 1975, 14, 209. Hlrata. M.; Ohe. S.; Nagahama. K. Computer-Aided Data Book of Vapor-Liquid Equilibria Kodansha: Tokyo, 1975. Knapp, H.; Wing, R.; Plocker, U.; Prausnltz, J. M. Vapor-LiquidEquilibrie forTwo approaches to the on-line identification of parameters and states in systems described by nonlinear ordinary differentlal equations are compared by using an example chemical process. The first approach is based on the Kalman filter approach extended to cover nonlinear systems. The second is based on the application of nonlinear optimization methods to minimize a suitable function of the error in estimation. The Kalman filter approach was found to be sensitive to several factors: the initial guess of the state variables, the statistics of the input and measurement noises, and the nature of the nonlinearity in the describing equations. The second approach, while computationally more intensive, proved to be far superior in terms of the speed of tracking, robustness in the presence of errors in modeling the systems, and noise statistics and in terms of the ability to handle nonlinearity in the system.By use of a critical combination of zeolite catalysts, high space velocity, and high temperature, cracking of some 10 000 volumes of gas oil over 1 volume of catalyst in a single on-stream cycle (Le., without regeneration) has been accomplished. For a supposed single-cycle operation, this would imply a fresh catalyst requirement of 0.3 tons per day for a 20 000 BID cracking operation, without reg...

No abstract

About 20% power output penalties will be incurred for implementing CO 2 capture from power plant. This loss can be partially compensated by flexible operation of capture plant. However, daily large variations of liquid and gas flows may cause operation problems to packed columns. Control schemes were proposed to improve the flexibility of power output without causing substantial hydraulic disturbances in capture plant is presented. Simulations were implemented using ASPEN Plus. In varying lean solvent flow strategy, the flow rate of recycling solvent was manipulated to control the CO 2 capture rate. The liquid flow of the absorber and gas flow of the stripper will vary substantially. In an alternative strategy, the lean solvent loading will be varied. Variation of gas throughput in the stripper is avoided by recycling part of CO 2 vapor to stripper. This strategy provided more stable hydraulics condition in both columns and is recommended for flexible operation.