Depropanizer Column Research Articles

Use fractionation unit to increase natural gas recovery rate

In recent years, due to the reduction of the amount of raw material gas and the change of equipment parameters, the liquefied natural gas recovery rate is reduced. According to the existing problems, the system needs to be optimized to improve the quality of the recovered liquefied natural gas. The HYSYS software was used to simulate the fractionation process. Through research, a parameter optimization scheme is proposed. Preferably, the initial stream inlet temperature, the deethanizer bottom temperature, and the depropanizer column top reflux rate are optimized for the original process flow to improve the liquefied natural gas recovery quality and reduce the equipment energy consumption.

On Entropy Generation and the Effect of Heat and Mass Transfer Coupling in a Distillation Process

AbstractThe entropy production rates as obtained from the exergy analysis, entropy balance and the nonequilibrium thermodynamics approach are compared for two distillation columns. The first case is a depropanizer column involving a mixture of ethane, propane, n-butane and n-pentane. The other is a weighed sample of Mexican crude oil distilled with a pilot scale fractionating column. The composition, temperature and flow profiles, for a given duty and operating conditions in each column, are obtained with the Aspen Plus V8.4 software by using the RateFrac model with a rate-based nonequilibrium column. For the depropanizer column the highest entropy production rate is found in the central trays where most of the mass transfer occurs, while in the second column the highest values correspond to the first three stages (where the vapor mixture is in contact with the cold liquid reflux), and to the last three stages (where the highest temperatures take place). The importance of the explicit inclusion of thermal diffusion in these processes is evaluated. In the depropanizer column, the effect of the coupling between heat and mass transfer is found to be negligible, while for the fractionating column it becomes appreciable.

Development and Validation of a Reduced-Index Dynamic Model of an Industrial High-Purity Column

A depropanizer column is a high purity distillation unit, whose modeling is challenging due to its high nonlinear behavior and intricate dynamics. Also, depending on the assumptions, a differential algebraic equation (DAE) system of high index can arise in the modeling of the column. Such systems create significant difficulties to numerical simulation. Phenomenological hydraulic relationships can be used to avoid the index problems. However, these relationships may rely on unknown and arbitrarily assumed parameters and project details. This paper presents an alternative modeling approach called dynamic design using proportional action (DDPA), which is used to simplify the hydraulic and pressure drop relation for a distillation unit. The DDPA approach generates a reduced index dynamic model by adding equations similar to a proportional controller with arbitrarily large gain. A depropanizer column was modeled using DDPA, and the model was validated with real process data obtained in an industrial-scale depr...

Optimation of Depropanizer Unit using Turbo Expander and Its Controller using Model Predictive Control

In this study, Turbo expander (TE) and Model Predictive Control (MPC) is suggested for depropanizer unit to increase propane recovery and improve control performance of the unit. The model that used in the MPC is a first order plus dead time (FOPDT), which tested the control performance using set point (SP) and disturbance change test. The measurement of the performance is the integral of the absolute error (IAE). As a result, use of TE in the depropanizer able to increase the recovery of propane of 8.44% (from 82.11% to 90.55%). The control structure of the depropanizer unit using turbo expander are pressure control for the TE (using proportional-integral control), composition control in the distillate flow (using MPC), and pressure control in depropanizer column (using MPC). The control performance after carrying out the tests show that at the SP change, the composition control and the pressure control in depropanizer unit has lower IAE values for MPC than PI contoller. Similarly when tested using disturbance rejection, the IAE of MPC is lower than PI controller. It means that MPC is better than PI controller for composition control and pressure control in depropanizer unit.

Modifier Adaptation methodology based on transient and static measurements for RTO to cope with structural uncertainty

Optimal process operation is carried out by a Real-Time Optimization (RTO) layer which is not always able to achieve its targets due to the presence of plant-model mismatch. To overcome this issue, the economic optimization problem solved in the RTO is changed following the Modifier Adaptation methodology (MA), which uses plant measurements to find a point that satisfies the necessary optimality conditions (NCO) of an uncertain process. MA proceeds by iteratively adjusting the optimization problem with first and zeroth order corrections, calculated from steady-state information at each RTO execution. This implies a long convergence time. This paper presents a new method based on a recursive identification algorithm to estimate process gradients from transient measurements to speed up the convergence of MA. The proposed approach is implemented in a simulated depropanizer column that incorporates a simplified model in the RTO, reducing by 8 the convergence time compared with traditional MA.

Retrofitting Options for Natural Gas Liquid (NGL) Fractionation Trains Using the Concept of Single Column Development

Heat pump assisted distillation (HPAD) system and self-heat recuperation technology (SHRT) have been developed as a result of intensive research to reduce energy consumption of a conventional distillation system. To determine a suitable system for natural gas liquid (NGL) fractionation trains, rigorous analysis and comparative study of several HPAD and SHRT options for the retrofitting of a single column were studied in the present work. The retrofit options considered were vapor compression (VC), mechanical vapor recompression (MVR), thermal vapor recompression (TVR), bottom flashing (BF), side heat exchanger (SHE), intermediate heating and cooling (IHC), self-heat recuperative (SHR) and modified self-heat recuperative (MSHR) distillation. A depropanizer column commonly used in typical NGL plant was selected as a case study. Aspen HYSYS V7.3 was initially used to simulate the eight selected retrofit designs under common sets of criteria. The data from the simulation was then analyzed to determine the best design in term of energy cost reduction. The analysis shows that the MVR gives the highest energy cost reduction of 68.11% as compared to that of the base case (BC) conventional column. It is followed by VC (66.65%), MSHR (64.02%), BF (62.88%), SHR (55.85%), SHE (54.23%), IHC (39.54%), and TVR (12.41%).

A Novel ARX-Based Approach for the Steady-State Identification Analysis of Industrial Depropanizer Column Datasets

This paper introduces a novel steady-state identification (SSI) method based on the auto-regressive model with exogenous inputs (ARX). This method allows the SSI with reduced tuning by analyzing the identifiability properties of the system. In particular, the singularity of the model matrices is used as an index for steady-state determination. In this contribution, the novel SSI method is compared to other available techniques, namely the F-like test, wavelet transform and a polynomial-based approach. These methods are implemented for SSI of three different case studies. In the first case, a simulated dataset is used for calibrating the output-based SSI methods. The second case corresponds to a literature nonlinear continuous stirred-tank reactor (CSTR) example running at different steady states in which the ARX-based approach is tuned with the available input-output data. Finally, an industrial case with real data of a depropanizer column from PETROBRAS S.A. considering different pieces of equipment is analyzed. The results for a reflux drum case indicate that the wavelet and the F-like test can satisfactorily detect the steady-state periods after careful tuning and when respecting their hypothesis, i.e., smooth data for the wavelet method and the presence of variance in the data for the F-like test. Through a heat exchanger case with different measurement frequencies, we demonstrate the advantages of using the ARX-based method over the other techniques, which include the aspect of online implementation.

Internal Excitation Approaches for Closed-loop Identification of Processes Controlled by MPC

This work is concerned with the model re-identification of processes controlled by MPC systems. The MPC system considered here has a two-layer structure, where in the upper layer a steady-state optimization algorithm determines a set of optimal targets for the process inputs and passes this set to the MPC controller that determines the best way to drive the process to such targets. This is the case of several commercial MPC packages applied in industry. In this paper, it is proposed two internal excitation approaches aiming to obtain closed-loop data sufficiently rich for process identifiability. Here, the term internal is used to indicate that the excitation test signal is applied within the MPC control structure. In the first excitation approach, the test signal is introduced as a weighting factor in the objective function of the target calculation layer. In the second approach, the test signal is injected as a dither signal in the objective function of the dynamic controller layer. These two approaches are compared to the usual method where the excitation signal is added to the controller output. The application of the methodologies is illustrated through numerical simulations carried out on a depropanizer column of the oil industry. The results show the effectiveness of the proposed approaches and their good potential to be applied in practice.

The Dynamics and Control of a Depropanizer

Abstract The dynamic and control behavior of a depropanizer that consists of 29 ideal trays plus condenser and reboiler, with feed introduced at the 12th tray, has been studied by digital simulation. Open loop dynamic behavior of the column was studied for step changes of up to 30% in the feed and reflux flow rates and heat input to the reboiler. For changes in feed flow rate, the disturbance variable used for the control studies, the column exhibited inverse behavior in the composition response of the light key component (propane) in the distillate and the heavy key component (isobutane) in the bottom product. However, no inverse response was observed for the controlled variables of the concentration of the heavy key in the distillate and the light key in the bottoms. Control behavior of the five component depropanizer column for conventional single product composition control as well as dual quality control was investigated using the DYCONDIST simulator. Results obtained using indirect control strategies by measuring tray liquid temperature(s) and direct control of the distillate and bottoms are presented. Performance of the dual quality control schemes is discussed with respect to predicted behavior based on static information from relative gain array and relative disturbance gain calculations.