Selection method for hybrid energy storage schemes for supply reliability improvement in distribution networks

Hybrid energy storage (HES) plays a crucial role in enhancing the reliability of distribution networks. However, the distinct charging and discharging characteristics among different energy storage technologies pose challenges to the evaluation of HES technical features. This paper focuses on addressing two main issues in HES pre-selection. Firstly, regarding the influence of the number of energy storage types on the utility value in HES pre-selection evaluation, we employ the integrated evaluation method of analytic hierarchy process (AHP)-criteria importance through intercriteria correlation (CRITIC)-technique for order preference by similarity to ideal solution (TOPSIS). We propose an improved utility value calculation method based on enhanced utility combination rules. These rules include distance, replacement, addition, and multiplication rules. By establishing these rules, we can effectively eliminate the impact of the number of energy storage types on the combination result. This enables us to accurately calculate the technical characteristics of HES schemes with varying numbers of energy storage technologies, providing a more reliable basis for scheme comparison and selection. Secondly, to eliminate the interference of utility value improvement processing on evaluation results, we introduce a secondary screening method based on TOPSIS evaluation results. This method mitigates the influence of subjective coefficients by evaluating HES schemes under different subjective coefficients and selecting optimal and sub-optimal schemes. We also establish an evaluation system with 11 indices and 10 energy storage technologies, which can efficiently evaluate up to 1785 HES schemes, significantly expanding the scope of evaluation. Finally, we develop a reliability simulation method for distribution networks based on sequential Monte Carlo. Using the IEEE-33 node as an example, we configure the optimal scheme. The results show that the evaluation process has high reliability. The proposed method not only improves the accuracy and rationality of HES pre-selection but also has important practical significance. In actual power grid operation, it can help decision-makers and utility companies to select the most suitable HES schemes more scientifically. This can effectively improve the reliability of power supply, reduce construction costs, and promote the efficient operation of distribution networks. It provides a valuable reference for the wide-scale application of HES in the power industry.

Authors

Institutions

Publication Details

Journal
Energy Informatics
Published
2025-03-14
DOI
https://doi.org/10.1186/s42162-025-00495-8
Citations
1
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
0.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Selection method for hybrid energy storage schemes for supply reliability improvement in distribution networks

Qian Li, Yuan Zhou, Yunxiao Zhang, Yuxin Fu
1 citations
Energy Informatics
Smart Grid Energy Management
0.73
article

Selection method for hybrid energy storage schemes for supply reliability improvement in distribution networks

Qian Li, Yuan Zhou, Yunxiao Zhang, Yuxin Fu
article en
1 citations

Abstract

Hybrid energy storage (HES) plays a crucial role in enhancing the reliability of distribution networks. However, the distinct charging and discharging characteristics among different energy storage technologies pose challenges to the evaluation of HES technical features. This paper focuses on addressing two main issues in HES pre-selection. Firstly, regarding the influence of the number of energy storage types on the utility value in HES pre-selection evaluation, we employ the integrated evaluation method of analytic hierarchy process (AHP)-criteria importance through intercriteria correlation (CRITIC)-technique for order preference by similarity to ideal solution (TOPSIS). We propose an improved utility value calculation method based on enhanced utility combination rules. These rules include distance, replacement, addition, and multiplication rules. By establishing these rules, we can effectively eliminate the impact of the number of energy storage types on the combination result. This enables us to accurately calculate the technical characteristics of HES schemes with varying numbers of energy storage technologies, providing a more reliable basis for scheme comparison and selection. Secondly, to eliminate the interference of utility value improvement processing on evaluation results, we introduce a secondary screening method based on TOPSIS evaluation results. This method mitigates the influence of subjective coefficients by evaluating HES schemes under different subjective coefficients and selecting optimal and sub-optimal schemes. We also establish an evaluation system with 11 indices and 10 energy storage technologies, which can efficiently evaluate up to 1785 HES schemes, significantly expanding the scope of evaluation. Finally, we develop a reliability simulation method for distribution networks based on sequential Monte Carlo. Using the IEEE-33 node as an example, we configure the optimal scheme. The results show that the evaluation process has high reliability. The proposed method not only improves the accuracy and rationality of HES pre-selection but also has important practical significance. In actual power grid operation, it can help decision-makers and utility companies to select the most suitable HES schemes more scientifically. This can effectively improve the reliability of power supply, reduce construction costs, and promote the efficient operation of distribution networks. It provides a valuable reference for the wide-scale application of HES in the power industry.

Energy InformaticsVol. 8(1)
North China Electric Power University (CN), State Grid Corporation of China (China) (CN), The First People's Hospital of Changde (CN), Shanghai Electric (China) (CN), Renmin University of China (CN)
Affordable and clean energy
Openalex Percentile: Top 31%
Smart Grid Energy Management
0.73
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.