Energy Loss Optimization Method Considering the Time-varying Characteristics of Battery Energy Storage Systems
A time-varying optimization strategy for battery cluster power allocation is proposed to minimize energy loss in battery energy storage systems (BESS). First, the time-dependent loss characteristics of both storage and non-storage components in BESS are analyzed. Based on this analysis, steady-state and transient methods for evaluating battery loss are proposed. Second, considering the distinct time-varying characteristics of various BESS components, the load-rate vs. equivalent-efficiency curve and the current-loss power component gradient field are introduced as analytical tools. These tools facilitate the derivation of optimization path for both time-varying and time-invariant energy components of BESS. Building on this foundation, a time-varying optimization strategy for battery cluster power allocation is developed, aiming to minimize energy loss while fully accounting for the dynamic characteristics of BESS. Compared to real-time optimization, this strategy prioritizes global optimality in the time domain, mitigates the risk of dimensionality curse, and enhances BESS efficiency. Finally, a Simulink/Simscape model is established based on real-world data to simulate internal component losses within BESS. The effectiveness of the proposed strategy is validated under a peak shaving scenario. Results indicate that, after optimization, the annual operational loss of BESS is reduced by 2.40%, while the energy round-trip efficiency is improved by 0.59%.
Authors
- Gang Mu (ORCID: https://orcid.org/0000-0002-4382-4929)
- Junhui Li (ORCID: https://orcid.org/0000-0001-5196-9960)
- Gan Guo
- Gangui Yan
Institutions
- Electric Power University (VN)
- Northeast Electric Power University (CN)
Publication Details
- Journal
- Protection and Control of Modern Power Systems
- Published
- 2025-05-30
- DOI
- https://doi.org/10.23919/pcmp.2024.000288
- Citations
- 3
- Primary Topic
- Power Systems and Renewable Energy
- Type
- article
- Field-Weighted Citation Impact
- 1.60