Volume Reduction of Industrial Effluent in Multiple Effect Evaporator through Model-Based Control Schemes

Document Type : Research Article

Authors

1 Department of Instrumentation Engineering, Madras Institute of Technology Campus, Anna University, Chennai 6000444, Tamil Nadu, INDIA

2 Department of Chemical Engineering, CSIR-CLRI, Chennai 600025, Tamil Nadu, INDIA

3 Department of Instrumentation Department of Instrumentation Engineering, Madras Institute of Technology Campus, Anna University, Chennai 6000444, Tamil Nadu, INDIA

Abstract

Multi Effect Evaporator (MEE) is an important unit operation in industrial waste effluent treatment where water recovered from MEE can be reused for industrial operations thus reducing fresh water demand of the industry leading to Zero Liquid Discharge (ZLD) and environmental sustainability. Economically, multi-effect evaporators in many industries are used to improve the steam economy and cut down the waste handling cost.  In this study, a dynamic mathematical model for a seven-effect evaporator has been developed and the model is validated against the real-time data collected from an industrial evaporator available in the Common Effluent Treatment Plant (CETP) located at Pallavaram, Chennai, India. Parametric sensitivity analysis is carried out to study the effect of various input parameters on the concentration of the output stream. Parametric studies reveal that input parameters namely heat transfer coefficient and steam flow rate have more influence on the concentration of the output.  Lyapunov-based MPC (LMPC) scheme is implemented to achieve important performance characteristics like a low salt concentration in the water discharge, disturbance rejection, and stability.  The disturbance rejection efficiency of LMPC is tested by adding 1% positive disturbance in feed concentration. Also, stability is assessed by introducing an additional delay of 2 seconds in the process. The performance of LMPC is compared with other controllers like IMC-PID and MPC. The closed-loop performance of all the proposed controllers for MEE is evaluated using error criteria and settling time. In LMPC,  ISE, IAE value,, and settling time are drastically reduced by 68.15%, 88.39%, and 21.79% respectively with respect to MPC. Thus better setpoint tracking, quicker settling time and better stabilization of product concentration will pave the way for ZLD and improved water quality of the recycled water.

Keywords

Main Subjects


[1] Phiri., Mumba P., Moyo B.Z., Kadewa W., Assessment of the Impact of Industrial Effluents on Water Quality of Receiving Rivers in Urban Areas of Malawi, International Journal of Environmental Science & Technology, 2(3): 237–244 (2005).
[2] Andréa O.S., Costa., Enrique L. Lima., Modelling and Control of an Industrial Multiple-Effect Evaporator System, The Canadian Journal of Chemical Engineering, 81(5): 1032-1040 (2008).
[3] Kumar D., Kumar V., Singh V.P., Modeling and Dynamic Simulation of Mixed Feed Multi-Effect Evaporators in Paper Industry, Applied Mathematical Modelling, 37(1-2): 384–397 (2013).
[4] Hisham El-Dessouky., Imad Alatiqi.S., Bingulac., Hisham Ettouney., Steady-State Analysis of the Multiple Effect Evaporation Desalination Process, Chemical Engineering Technology, 21(5): 437- 451 (1999).
[5] Miranda V., Simpson R., Modelling and Simulation of an Industrial Multiple Effect Evaporator Tomato Concentrate, Journal of Food Engineering,  66: 203-210 (2005).
[6] Rafael M.S., Maurício M.C., Thiago F.,  José C.P., Digital Twin for Monitoring of Industrial Multi-Effect Evaporation, Processes, 7: 1-14 (2019).
[7] Di Bo., Kunru Yang., Qingsong Xie., Chang He., Bingjian Zhang., Qinglin Chen., Zhiwen Qi., Jingzheng Ren., Ming Pan., A Novel Approach for Detailed Modeling and Optimization to Improve Energy Saving in Multiple Effect Evaporator Systems, Ind. Eng. Chem. Res, 58(16): 6613−6625 (2019).
[8] Felipe Mathew Mota Sousa., Rodolpho Rodrigues Fonsea., Application of Adaptive Feedforward-Feedback Control on Multieffect Evaporator Process, Chemical Product and Process Modeling, 14(2): 1-13 (2018).
[9] Elhaq S.L., Giri F., Unbehauen H., "The Development of Controllers for a Multiple-Effect Evaporator in Sugar Industry", European Control Conference. ECC 97, July, Belgium.3318-3322 (1997).
[10] Christofides P.D., Liu J., Munoz de la Pena D., "Networked and Distributed Predictive Control Methods and Nonlinear Process Network Applications", Springer: 13-45 (2011).
[11] David Muñoz de la Peña., Panagiotis D. Christofides., Lyapunov-Based Model Predictive Control of Nonlinear Systems Subject to Data Losses, IEEE Transactions on Automatic Control, 53(9):2076-2089 (2008).
[12] Khalil., Naceur B.B., Design a Lyapunov Control Under Input Constraint for Stabilisation of a CSTR, International, Journal of Automation and Control, 10(1): 52-72 (2016).
[13] Rawlings J.B., Mayne., DQ Diehl M.M., "Model Predictive Control Theory, Computation and Design", North Hill Publication (202).
[14] Xiaojun Wang., Chao Li., Xisong Chen.,  Disturbance Rejection Control for Multiple-Effect Falling-Film Evaporator Based on Disturbance Observer, Transactions of the Institute of Measurement and Control 38(6): 1-11(2016).
[15] Andreas D., Sebastian E., Horst R., Model Predictive Control Using Neural Networks, IEEE Control Systems 15(5): 61-66 (1995).