FBWM-MARCOS based planning method for grid peak-frequency regulation energy storage system

The selection of energy storage systems is crucial for effective participation in grid frequency modulation (FM) and frequency deviation (FD) planning. This study proposes a methodology integrating the Fuzzy Best-Worst Method (FBWM) and MARCOS to evaluate the applicability of energy storage technologies. Expert scoring and FBWM are employed for weight determination, with fuzzy theory mitigating uncertainties in expert judgment. MARCOS is then used to compute the overall evaluation scores. This approach provides a theoretical foundation for energy storage planning in grid regulation and holds significant engineering applicability.

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Publication Details

Published
2025-04-07
DOI
https://doi.org/10.1109/icpies65420.2025.11070067
Citations
1
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
0.53
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article

FBWM-MARCOS based planning method for grid peak-frequency regulation energy storage system

Zhiguo Yang, Wenlin Zheng
1 citations
Power Systems and Renewable Energy
0.53
article

FBWM-MARCOS based planning method for grid peak-frequency regulation energy storage system

Zhiguo Yang, Wenlin Zheng
article en
1 citations

Abstract

The selection of energy storage systems is crucial for effective participation in grid frequency modulation (FM) and frequency deviation (FD) planning. This study proposes a methodology integrating the Fuzzy Best-Worst Method (FBWM) and MARCOS to evaluate the applicability of energy storage technologies. Expert scoring and FBWM are employed for weight determination, with fuzzy theory mitigating uncertainties in expert judgment. MARCOS is then used to compute the overall evaluation scores. This approach provides a theoretical foundation for energy storage planning in grid regulation and holds significant engineering applicability.

Changsha University (CN), Changsha University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 29%
Power Systems and Renewable Energy
0.53
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