Optimal storage capacity for building photovoltaic-energy storage systems considering energy flexibility management
Energy storage plays a crucial role in addressing the mismatch between the energy supply of renewable energy generation and building demand and enhancing building energy flexibility. However, the specific requirement of building flexibility management is often neglected in the design of building storage systems, making it challenging to maintain economic efficiency when regulating building energy flexibility in operation. This study presents a capacity optimization model for building energy storage systems that incorporates the building energy flexibility requirement, measured by the load shifting capacity ratio (LSCR), to minimize the net present cost (NPC). The relationships between energy flexibility and cost-efficiency were analyzed for three systems: photovoltaic-battery energy storage (PV-BES), photovoltaic-thermal energy storage (PV-TES), and photovoltaic-hybrid energy storage (PV-HES). The results showed that the PV-HES system achieves the highest economic efficiency among the three systems across different LSCRs, and its NPC with the LSCR of 1 is 76% lower than that with the LSCR of 0.1. Furthermore, an analysis of the impacts of the peak-to-valley ratio for the time-of-use (TOU) tariff on storage capacity optimization for the PV-HES system demonstrates that the valley price ratio has a greater impact on the NPC than the peak price ratio for the PV-HES system. Also, it suggests that building energy flexibility can be managed by adjusting the peak-to-valley ratio of the TOU tariff. This study offers a new design method for building energy storage to promote effective energy flexibility management.
Authors
- Ruimiao Liu
- Ya‐Ling Wu (ORCID: https://orcid.org/0000-0002-3329-7141)
- Benjia Li
- Ling Zhang (ORCID: https://orcid.org/0000-0002-4881-3989)
- Haixia Liu (ORCID: https://orcid.org/0000-0001-7267-2824)
- Zhongbing Liu (ORCID: https://orcid.org/0000-0002-9486-6686)
Institutions
- Hunan University (CN)
- State Grid Corporation of China (China) (CN)
- Energy Research Institute (CN)
Publication Details
- Journal
- Energy and Buildings
- Published
- 2025-04-17
- DOI
- https://doi.org/10.1016/j.enbuild.2025.115757
- Citations
- 8
- Primary Topic
- Smart Grid Energy Management
- Type
- article
- Field-Weighted Citation Impact
- 5.84