Using a Nonlinear Model Predictive Control strategy for the efficient operation of a solar-powered membrane distillation system

This paper presents an optimal operation strategy in terms of thermal efficiency and distillate flux production for a Solar Membrane Distillation (SMD) system. Firstly, a study of the Membrane Distillation (MD) module is presented, revealing the optimal operation strategy. Secondly, a hierarchical control system with two layers is developed and tested. The upper layer consists on a Nonlinear Model Predictive Control (NMPC) scheme which allows us to obtain the maximum temperature at the inlet of the MD module, by optimizing the use of solar energy. The lower layer is composed by a direct control system that is in charge of reaching the setpoint calculated by the upper layer. Simulation results are shown in order to demonstrate the effectiveness of this control approach.

[1]  W. Beckman,et al.  Solar Engineering of Thermal Processes , 1985 .

[2]  Chien-Chang Li,et al.  Modeling and optimization of a solar driven membrane distillation desalination system , 2010 .

[3]  Qingfeng He,et al.  Modeling and optimization of air gap membrane distillation system for desalination , 2014 .

[4]  Manuel Berenguel,et al.  Solar membrane distillation: A control perspective , 2015, 2015 23rd Mediterranean Conference on Control and Automation (MED).

[5]  Mohamed Khayet Souhaimi Solar desalination by membrane distillation: Dispersion in energy consumption analysis and water production costs (a review) , 2013 .

[6]  M. Berenguel,et al.  Solar field control for desalination plants , 2008 .

[7]  Guillermo Zaragoza,et al.  Productivity analysis of two spiral-wound membrane distillation prototypes coupled with solar energy. , 2015 .

[8]  Marko Bacic,et al.  Model predictive control , 2003 .

[9]  Mohamed Khayet,et al.  Air gap membrane distillation: Desalination, modeling and optimization , 2012 .

[10]  Guillermo Zaragoza,et al.  Efficiency in the use of solar thermal energy of small membrane desalination systems for decentralized water production , 2014 .

[11]  N. Hilal,et al.  Membrane distillation: A comprehensive review , 2012 .

[12]  Francisco Rodríguez,et al.  Predictive Control with Disturbance Forecasting for Greenhouse Diurnal Temperature Control , 2011 .

[13]  Julio E. Normey-Rico,et al.  A PRACTICAL APPROACH TO PREDICTIVE CONTROL FOR NONLINEAR PROCESSES , 2007 .

[14]  Hsuan Chang,et al.  Experimental and simulation study of a solar thermal driven membrane distillation desalination process , 2012 .

[15]  Lidia Roca,et al.  Dynamic modeling and simulation of a double-effect absorption heat pump , 2016 .

[16]  Andrea Cipollina,et al.  A neural network-based optimizing control system for a seawater-desalination solar-powered membrane distillation unit , 2013, Comput. Chem. Eng..

[17]  Francisco Rodríguez,et al.  Thermal comfort control using a non-linear MPC strategy: A real case of study in a bioclimatic building , 2014 .