Model Predictive Control of a Hybrid Rooftop Unit System Integrated with Phase Change Material for Load Shifting

Thermal energy storage (TES) offers a promising solution for load shifting and reducing peak demand in buildings. The TES system under consideration in this paper is a hybrid rooftop unit (RTU) from Emerson with 5-ton cooling capacity, integrated with a patented phase change material (PCM) from NETEnergy that functions as TES. The hybrid RTU system with PCM is currently in pre-commercialization stage, and offers important advantages over equivalent ice storage systems, namely significant reduction in added weight and cost, and a lot fewer moving parts and machinery. The hybrid RTU system with PCM has the potential to reduce peak demand by up to 40% and leverage time-of-use (TOU) utility rates to reduce operational costs for the customer. The default controller used to regulate the operation of TES is rule-based control (RBC). A set of rules govern the charging and dishcarging of the PCM. The utility of the hybrid RTU + PCM can be further improved by replacing rulebased approach of RBC with an optimization-based approach of model predictive control (MPC). This paper provides the algorithm development, analysis, and results of implementing model predictive control (MPC) on the hybrid RTU with PCM using high-fidelity physics-based models as the simulation test-bed. The goal of the paper is to show how replacing RBC with MPC can provide greater benefits with regards to load shifting and peak-demand reduction. Reduced order models (ROMs) are developed for each component of the hybrid RTU and PCM, and mathematical optimization is performed to fmd the optimal charging/discharging trajectory of the PCM. MPC is then tested on highfidelity physics-based models of the RTU and PCM components, and compared with an RBC strategy in a co-simulation environment. A high demand and low demand use case are tested under a TOU rate structure, and MPC performs better than RBC when the demand is low, yielding 4.5% savings.