Optimal Placement and Sizing Algorithm for BESS to Enhance the Renewable Energy Hosting Capacity of Power Systems

This paper proposes an algorithm for determining the optimal location and sizing of a battery energy storage system (BESS) to enhance the grid hosting capacity when integrating renewable energy sources. The proposed algorithm optimizes the BESS by considering both active power absorption and reactive power supply functions, utilizing the particle swarm optimization (PSO) algorithm. By incorporating voltage sensitivity analysis, the computation time and convergence to the optimal solution of the PSO were improved. To validate the effectiveness of the proposed method, simulations were conducted based on the IEEE 300-Bus system. The P-V curve analysis indicated that the integration of BESS led to a 50.8% increase in grid capacity for renewable energy sources. Furthermore, compared to conventional methods that considered only active power, the proposed approach achieved a 9.8% increase in grid capacity.

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Publication Details

Journal
The Transactions of The Korean Institute of Electrical Engineers
Published
2025-02-26
DOI
https://doi.org/10.5370/kiee.2025.74.2.221
Primary Topic
Power Systems and Renewable Energy
Type
article
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article

Optimal Placement and Sizing Algorithm for BESS to Enhance the Renewable Energy Hosting Capacity of Power Systems

Sihwan Kim, Joo-Sik Kwak, Sung‐Ho Hwang, Sungwoo Bae et al.
The Transactions of The Korean Institute of Electrical Engineers
Power Systems and Renewable Energy
article

Optimal Placement and Sizing Algorithm for BESS to Enhance the Renewable Energy Hosting Capacity of Power Systems

Sihwan Kim, Joo-Sik Kwak, Sung‐Ho Hwang, Sungwoo Bae, Changhee Lee, Donghyun Lee, Seungchan Jeon
article en

Abstract

This paper proposes an algorithm for determining the optimal location and sizing of a battery energy storage system (BESS) to enhance the grid hosting capacity when integrating renewable energy sources. The proposed algorithm optimizes the BESS by considering both active power absorption and reactive power supply functions, utilizing the particle swarm optimization (PSO) algorithm. By incorporating voltage sensitivity analysis, the computation time and convergence to the optimal solution of the PSO were improved. To validate the effectiveness of the proposed method, simulations were conducted based on the IEEE 300-Bus system. The P-V curve analysis indicated that the integration of BESS led to a 50.8% increase in grid capacity for renewable energy sources. Furthermore, compared to conventional methods that considered only active power, the proposed approach achieved a 9.8% increase in grid capacity.

The Transactions of The Korean Institute of Electrical EngineersVol. 74(2)
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Power Systems and Renewable Energy
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