Optimization control of LNG regasification plant using Model Predictive Control

3rd International Conference on Chemical Engineering Sciences and Applications 2017

Wahid, A.^1 ; Adicandra, F.F.^1

Sustainable Energy Research Group, Department of Chemical Engineering, Faculty of Engineering, Universitas Indonesia, Depok

16424, Indonesia^1

关键词: Control performance;    Fine-tuning methods;    Liquified natural gas;    LNG regasification;    Optimization control;    Optimum operating conditions;    Prediction horizon;    Set-point tracking;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/334/1/012022/pdf
DOI  :  10.1088/1757-899X/334/1/012022

来源: IOP

【 摘 要 】

Optimization of liquified natural gas (LNG) regasification plant is important to minimize costs, especially operational costs. Therefore, it is important to choose optimum LNG regasification plant design and maintaining the optimum operating conditions through the implementation of model predictive control (MPC). Optimal tuning parameter for MPC such as P (prediction horizon), M (control of the horizon) and T (sampling time) are achieved by using fine-tuning method. The optimal criterion for design is the minimum amount of energy used and for control is integral of square error (ISE). As a result, the optimum design is scheme 2 which is developed by Devold with an energy savings of 40%. To maintain the optimum conditions, required MPC with P, M and T as follows: tank storage pressure: 90, 2, 1; product pressure: 95, 2, 1; temperature vaporizer: 65, 2, 2; and temperature heater: 35, 6, 5, with ISE value at set point tracking respectively 0.99, 1792.78, 34.89 and 7.54, or improvement of control performance respectively 4.6%, 63.5%, 3.1% and 58.2% compared to PI controller performance. The energy savings that MPC controllers can make when there is a disturbance in temperature rise 1°C of sea water is 0.02 MW.