Lawrence Berkeley National Laboratory

As electrification and decarbonization goals become more commonplace across the country, the need for integrating thermal energy storage (TES) with HVAC to provide flexibility and load shifting is growing. Although there has been recent work related to the modeling and design of TES-integrated heat pump (HP) systems, investigation of generalized sizing and control methods for these systems remain limited. This paper details the development of generalized controls and sizing strategies applicable across different TES-integrated designs, two of which are discussed in this study. We demonstrate how model-based design enables an informed sizing and controls design process using the control-oriented Modelica language to generate high-fidelity models that accurately represent real-world behavior. We detail our development and testing of both heuristic and model predictive control (MPC) algorithms to determine the optimal charge and discharge schedule with dynamic varying utility prices. Experimental results show MPC provides operating costs reduction of nearly 20% for a minimum TES sizing scenario. In addition, we provide a generalized and intuitive control algorithm with near-optimal performance to control HP + TES systems and test its performance in simulation. This generalized control algorithm is also used to drive the results of our cost analysis, providing insights for engineers designing new TES-integrated HVAC systems. The cost analysis demonstrates the tradeoff between higher initial hardware costs from larger equipment and the resulting operational cost benefits, and enables a cost-effective sizing method which is applicable to any system. The paper concludes with design recommendations for new integrated HP-TES control systems in buildings.