Optimal Operation and Control of a Thermal Energy Storage System: Classical Advanced Control versus Model Predictive Control

Abstract

The objective of this work is to define the optimal operation and control for a thermal storage system with heat sources and a consumer, which exchange utilities using one hot water thermal energy storage tank. In this work, we compare a decentralized control structure using classical advanced control with PID controllers and logic blocks (split-range control and selectors) and a centralized control structure (model predictive control) to implement optimal operation for a simple thermal energy storage system, which is a multivariable system with constraints. We analyze a varying heat supply profile over a horizon of 24 hours. We show that the supply and demand can be balanced, and we achieve optimal operation by using the energy stored in the tank while minimizing the heat from the market.