Optimal Placement and Sizing of Battery Energy Storage Systems Based on Quantitative Evaluation of Power System Frequency Control Effectiveness

This study presents a quantitative evaluation method for determining the optimal location and required capacity of Battery Energy Storage Systems (BESS) which is expected to be continuously installed in the power systems with a high penetration level of the renewable energy resources. For doing this, a new index, the Frequency Control Effectiveness Index(FCEI), is proposed to assess the frequency control performance of the power system by comparing the frequency distortion magnitude with the performance criteria, providing a normalized measure of the control performance. Contribution of BESS on the frequency control can be evaluated by calculating FCEI according to its installation location and system operating conditions. Additionally, a system-level index (SYS_FCEI) is introduced to comprehensively quantify the frequency control performance of various operating conditions of the power systems. By using SYS_FCEI, the optimal location and required capacity for installing BESS can be determined considering the distribution of installation locations. The proposed method was validated through intensive study cases employing Korean power system database developed in accordance with the Basic Plan for Electricity Supply and Demand.

Authors

Publication Details

Journal
The Transactions of The Korean Institute of Electrical Engineers
Published
2026-03-13
DOI
https://doi.org/10.5370/kiee.2026.75.3.500
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimal Placement and Sizing of Battery Energy Storage Systems Based on Quantitative Evaluation of Power System Frequency Control Effectiveness

Yu-Hoon Song, Kyung-Soo Kook, Tae-Seung Lee, Jiwon Choi
The Transactions of The Korean Institute of Electrical Engineers
Power Systems and Renewable Energy
article

Optimal Placement and Sizing of Battery Energy Storage Systems Based on Quantitative Evaluation of Power System Frequency Control Effectiveness

Yu-Hoon Song, Kyung-Soo Kook, Tae-Seung Lee, Jiwon Choi
article en

Abstract

This study presents a quantitative evaluation method for determining the optimal location and required capacity of Battery Energy Storage Systems (BESS) which is expected to be continuously installed in the power systems with a high penetration level of the renewable energy resources. For doing this, a new index, the Frequency Control Effectiveness Index(FCEI), is proposed to assess the frequency control performance of the power system by comparing the frequency distortion magnitude with the performance criteria, providing a normalized measure of the control performance. Contribution of BESS on the frequency control can be evaluated by calculating FCEI according to its installation location and system operating conditions. Additionally, a system-level index (SYS_FCEI) is introduced to comprehensively quantify the frequency control performance of various operating conditions of the power systems. By using SYS_FCEI, the optimal location and required capacity for installing BESS can be determined considering the distribution of installation locations. The proposed method was validated through intensive study cases employing Korean power system database developed in accordance with the Basic Plan for Electricity Supply and Demand.

The Transactions of The Korean Institute of Electrical EngineersVol. 75(3)
Affordable and clean energy
Openalex Percentile: Top 28%
Power Systems and Renewable Energy
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.