Abstract :
An in-depth study of an MSF desalination plant control system has been conducted. The degrees of freedom
analysis based on a dynamic mathematical model was used to determine the number of controlled
(PVs) and manipulated variables (MVs). The analysis of the control problem points to a fully interacting
multivariable system. Furthermore, prudent plant practices dictate strict bounds on several of these PVs
and MVs and the desire to achieve unit optimization is felt. Thus, the MSF plant is an ideal candidate
lot" constrained model predictive control (CMPC). A locally developed CMPC was designed to achieve a
variety of operational objectives such as maximizing distillate production or performance ratio, minimizing
energy consumption, etc. CMPC provides set points to the existing PID controllers and, thus, integrity
with the existing instrumentation is maintained. The performance of CMPC was tested utilizing the
SPEEDUP dynamic simulation software and the results are excellent. For example, it is shown that for
an illustrative plant, steam savings of $1.6 million per year are possible. The potential impact of CMPC
for MSF plants is rather large considering that there are several hundred plants throughout the world all
of which are currently on PID-type control.
Keywords :
optimization , Constrained , control , MSF , Desalination