Optimal Siting and Sizing of Battery Energy Storage System in Distribution System in View of Resource Uncertainty

Gauri Mandar Karve (), Mangesh S. Thakare and Geetanjali A. Vaidya
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Gauri Mandar Karve: Electrical Engineering Department, Pune Vidhyarthi Griha’s College of Engineering and Technology and G K Pate (Wani) Institute of Management, Pune 411009, India
Mangesh S. Thakare: Electrical Engineering Department, Pune Vidhyarthi Griha’s College of Engineering and Technology and G K Pate (Wani) Institute of Management, Pune 411009, India
Geetanjali A. Vaidya: Electrical Consultant, SAS Powertech Pvt Ltd., Pune 411045, India

Energies, 2025, vol. 18, issue 9, 1-36

Abstract: The integration of intermittent Distributed Generations (DGs) like solar photovoltaics into Radial Distribution Systems (RDSs) reduces system losses but causes voltage and power instability issues. It has also been observed that seasonal variations affect the performance of such DGs. These issues can be resolved by placing optimum-sized Battery Energy Storage (BES) Systems into RDSs. This work proposes a new approach to the placement of optimally sized BESSs considering multiple objectives, Active Power Losses, the Power Stability Index, and the Voltage Stability Index, which are prioritized using the Weighted Sum Method. The proposed multi-objectives are investigated using the probabilistic and Polynomial Multiple Regression (PMR) approaches to account for the randomness in solar irradiance and its effect on BESS sizing and placements. To analyze system behavior, simultaneous and sequential strategies considering aggregated and distributed BESS placement are executed on IEEE 33-bus and 94-bus Portuguese RDSs by applying the Improved Grey Wolf Optimization and TOPSIS techniques. Significant loss reduction is observed in distributed BESS placement compared to aggregated BESSs. Also, the sequentially distributed BESS stabilized the RDS to a greater extent than the simultaneously distributed BESS. In view of the uncertainty, the probabilistic and PMR approaches require a larger optimal BESS size than the deterministic approach, representing practical systems. Additionally, the results are validated using Improved Particle Swarm Optimization–TOPSIS techniques.

Keywords: battery energy storage system; improved grey wolf optimization; improved particle swarm optimization; optimal siting and sizing; photovoltaic system; resource uncertainty (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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