Analysis of economic model predictive control parameters selection in an integrated solar thermal system

In this study, we investigate the practical impacts of parameters selection on the performance and computational cost of an economic model predictive controller for a domestic integrated solar thermal system. We also propose using an input-holding technique for the mentioned system, that decreases the elapsed time of solving optimization problems at each time-step, while sacrificing the efficiency of the control system to a small degree. It is observed that an optimally tuned controller can save up to 5% on energy bills while requiring a moderate amount of computational power.