Modeling, integration, and optimization of gas refinery amine circulation control system using neural network
Abstract
The Governor speed control system as one of the important components of the circulating amine pump speed control (MDEA) plays an essential role in the gas purification process and has been used in two electronic and pneumatic types in the Hashminejad Refinery. By controlling the flow of steam entering the turbine, the Governor keeps the speed of the turbine constant and finally controls the flow of amine entering the contact towers at the optimum point. With the completion of the Ramyar domestic model construction project instead of the American model with the Woodward brand, it was possible to optimize the turbine control system and make changes in it. The purpose of this research is to remove the local controller of the HIC turbine and change the minimum flow control system of the bypass path of the amine circulation pump output, as well as to simulate the speed using the neural network and control parameters. Therefore, in order to accurately model and study the control parameters using electronic registers, the turbine speed and drive were sampled, and by Honeywell software, the data change chart was entered into the Get Data software in the form of an image file. In the next step, these data were transferred to Excel and used to simulate the turbine speed using neural networks in MATLAB. Then the codes related to the control and simulation of the turbine speed were written in the Arduino software and through the OPC protocol it is possible to connect Arduino as a governor system simulator, Citect Scada software as monitoring and MATLAB as an analyzer and turbine speed simulator software. provided. Examining the output and simulation results show the optimal performance of the systems implemented in the steam turbine and the possibility of better communication between the user and the system and the significant reduction of human error. In the simulation, by comparing the actual performance of the turbine, it is possible to carefully check the control parameters in the special and critical conditions of the turbine performance, and check all the parameters of the turbine to compare with the real sample and make the desired changes in the simulator until the result Review.
References
[2] WGC, “Installation and Operation Manual US,505 Digital Governor for Steam Turbine,” Vol1,2004
[3] Aharco. Manual Book, “ Turbo Comperessor Control System Rmyar 401c, ” Iran, 2013
[4] Siemens Moor."User’s Manual, “USA, Moor 348 Field Mounted Controller,” UM348-1, Rev4,2000
[5] G. Han, L. Chen, J. Shao, Z. Sun, “Study of Fuzzy PID Controller for Industrial Steam Turbine Governing System,” China, Proceedings of ISCIT, 2005.
[6] H.Bentazi, R.A.Chentir, A.Ouadi, “A New Approach Applied to Steam Turbine Controller In Thermal Power Plant,” ICCIA, 2011
[7] T.J. Ross, “Fuzzy logic with engineering application, McGraw-Hill, Singapore,” 1995.
[8] R.S. Burns, “Advance control engineering Butterworth Heinemann,” Oxford, 2001.
[9] D.Lindsley, “Power plant control and Instrument: The control of Boiler and HRSG systems,” McGraw-Hill, NY, 2005.
[10] M.Chidambaran, “Computer control of the process, Narosa publishing house,” India, 2002.
[11] D.Bailey, “Practical Scada for Industry, Edwi Wright,” International Conference on Applied Energy – ICAE. 2016
[12] OPC Data Access (OPCDA) Versions & Compatibility at Matrikonopc .Com. 2020
https://www.matrikonopc.com/opc-server/opc-data- access-versions.aspx.
[13] CitectSCADA MANUAL". Scada software. 2020, http://www.scadasoftware.net/automation/citectscadamanual.html.
[14] R. Jackson,Translation: Al Barzi, Mahmoud, “ Introduction to neural networks,” Tehran, first edition, 2013
[15] One way, Kamaluddin, “Precision instruments and industrial control components,” Tehran, first edition, 2013
[16] A.Talebi, “Arduino comprehensive training,” Tehran, first edition, 2016
