A design optimization method for solar-driven thermochemical storage systems based on building performance simulation

The challenge of the temporal mismatch between energy supply and demand in buildings is growing with the increasing share of renewable energy in total energy consumption. Among all the state-of-the-art energy storage solutions, thermochemical heat storage shows a unique potential thanks to its considerable energy density, acceptable cost, and negligible heat loss. For this reason, it becomes a promising alternative to common sensible heat storage solutions for building applications. The integration of such a novel technology in buildings necessitates a method for the assessment of its potential impact and benefit, the comparison to common alternatives, and the optimization of the system design. This work proposes a method based on modeling and simulation of the interaction between the thermochemical heat storage system and the building using a data-driven surrogate model of the storage system in combination with a building performance simulation engine. The data-driven model was developed and validated based on laboratory measurements of a novel closed-loop thermochemical heat storage system, the heat battery (HB). The method was demonstrated in a case study to identify the optimal size of the HB in a solar-driven configuration based on a residential building use case. The results show that the heat battery can digest the thermal energy transferred from the solar thermal collector to reduce the original electricity consumption for heating the detached house (0.7 MWh to 1.0 MWh in considered cases) without any obvious sacrifice in thermal comfort and that the small-scale HB (with a storage volume below 160 liters) shows efficient usage of the designed storage capacity.