Simple and Accurate Model of Thermal Storage with Phase Change Material Tailored for Model Predictive Control

Abstract

Thermal heat storage is becoming important in systems with renewable energy sources. Their largest benefit is smoothing the intermittent production and reduction in the site peak demand. The advantages of thermal energy storage with phase-change material are storing energy at a lower temperature for reduction in thermal losses, and enabling energy transfer at a constant temperature, which reduces the risk of equipment damage. In this paper, a low-order model of latent thermal energy storage, derived in a state-space form by using the mixed logical dynamical approach, is proposed. The model is compared to a stratified model and shows significant improvements of physical accuracy and execution time. Finally, a model predictive control algorithm suited for the real case study is designed, implemented and compared to classical rule-based control. The obtained results show significant energy savings of 8.43%, and improvements in user comfort and equipment duration.