Towards building energy systems integrating renewable energy sources: A novel entropy-based optimization configuration approach of energy storage

In building energy systems with high renewable energy (RE) penetration, uncertainties from RE intermittency and load stochasticity hinder supply-demand matching. While hybrid energy storage systems (HESSs) offer a viable solution, achieving their full potential requires optimal capacity configuration, a task made particularly complex when integrated with efficiency-sensitive components like heat pumps (HPs). Existing researches often rely on purely economic or technical metrics, lacking a criterion that balances thermodynamic efficiency with cost, while common control strategies frequently overlook the complex operational dynamics of HPs. To address these gaps, this study proposes unit entropy reduction cost, a novel metric integrating thermodynamics and economics, providing the first physically-grounded cost-effectiveness criterion for HESS sizing. Then, advanced HP-aware control strategies are developed that explicitly account for the HP's dynamically varying coefficient of performance (COP) based on operating conditions. Results show thermal storage devices (TSDs) are more cost-efficient per unit entropy reduction, incurring only 30 %–50 % of the cost of electric storage devices (ESDs), while ESDs require only 10 % of TSD capacity for similar entropy reduction. Strategy 2 (ESD-priority) is found to be more suitable for HP-based HESS than Strategy 1 (TSD-priority), and the optimal TSD capacity is identified as 10,000 kWh across different ESD capacities. Finally, a critical HESS synergy failure in HP systems is identified, and an optimized adaptive strategy based on Strategy 2 is proposed and validated, which successfully unlocks the synergistic potential by maintaining HPs in their optimal COP range.