Double-layer power optimal allocation strategy of energy storage power station considering energy efficiency and battery state

Abstract Electrochemical energy storage is popular in many fields for its quick response and flexible setup. However, at this stage, the cost of energy storage is still high; the source of income is limited, and the profit prospects are worrying. Therefore, this paper proposes a two-layer power optimization allocation strategy for energy storage power stations considering energy efficiency and battery state. Through this strategy, the operation mode of energy storage can be optimized. The single-cycle expenditure for energy storage sees a reduction. The life cycle can be prolonged, and the income can be expanded. The bi-level optimal allocation strategy is divided into the optimization layer of the power storage subsystem and the optimization layer of the unit. At the level of the subsystem, considering the relationship between the load condition of the transformer and its efficiency, the power of each transformer is determined with the minimum total energy loss of the transformer as the objective. At the energy storage unit level, the state of charge and the health of the power storage unit are considered at the same time. The output power of each unit is optimized to ensure consistent battery states and avoid the “shortboard effect”. The simulation results show that the strategy has certain feasibility and effectiveness.

Authors

Institutions

Publication Details

Journal
Journal of Physics Conference Series
Published
2025-05-01
DOI
https://doi.org/10.1088/1742-6596/3011/1/012018
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Double-layer power optimal allocation strategy of energy storage power station considering energy efficiency and battery state

Yinfei Xu, Jiajin Qi, Jizhong Zhu, Shujiang Yu et al.
Journal of Physics Conference Series
Advanced Battery Technologies Research
article

Double-layer power optimal allocation strategy of energy storage power station considering energy efficiency and battery state

Yinfei Xu, Jiajin Qi, Jizhong Zhu, Shujiang Yu, Jiangtao Li, Yunlong Chen
article en

Abstract

Abstract Electrochemical energy storage is popular in many fields for its quick response and flexible setup. However, at this stage, the cost of energy storage is still high; the source of income is limited, and the profit prospects are worrying. Therefore, this paper proposes a two-layer power optimization allocation strategy for energy storage power stations considering energy efficiency and battery state. Through this strategy, the operation mode of energy storage can be optimized. The single-cycle expenditure for energy storage sees a reduction. The life cycle can be prolonged, and the income can be expanded. The bi-level optimal allocation strategy is divided into the optimization layer of the power storage subsystem and the optimization layer of the unit. At the level of the subsystem, considering the relationship between the load condition of the transformer and its efficiency, the power of each transformer is determined with the minimum total energy loss of the transformer as the objective. At the energy storage unit level, the state of charge and the health of the power storage unit are considered at the same time. The output power of each unit is optimized to ensure consistent battery states and avoid the “shortboard effect”. The simulation results show that the strategy has certain feasibility and effectiveness.

Journal of Physics Conference SeriesVol. 3011(1)
Zhejiang University of Water Resource and Electric Power (CN), Zhejiang University (CN)
Openalex Percentile: Top 89%
Advanced Battery Technologies Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.