Optimal Siting and Sizing of Battery Energy Storage System in Distribution System in View of Resource Uncertainty
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 ca...
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| author | Gauri Mandar Karve Mangesh S. Thakare Geetanjali A. Vaidya |
| author_facet | Gauri Mandar Karve Mangesh S. Thakare Geetanjali A. Vaidya |
| author_sort | Gauri Mandar Karve |
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| description | 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. |
| format | Article |
| id | doaj-art-f4b5f087b64b45e88f3d9841ca6164b2 |
| institution | OA Journals |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
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| series | Energies |
| spelling | doaj-art-f4b5f087b64b45e88f3d9841ca6164b22025-08-20T01:49:14ZengMDPI AGEnergies1996-10732025-05-01189234010.3390/en18092340Optimal Siting and Sizing of Battery Energy Storage System in Distribution System in View of Resource UncertaintyGauri Mandar Karve0Mangesh S. Thakare1Geetanjali A. Vaidya2Electrical Engineering Department, Pune Vidhyarthi Griha’s College of Engineering and Technology and G K Pate (Wani) Institute of Management, Pune 411009, IndiaElectrical Engineering Department, Pune Vidhyarthi Griha’s College of Engineering and Technology and G K Pate (Wani) Institute of Management, Pune 411009, IndiaElectrical Consultant, SAS Powertech Pvt Ltd., Pune 411045, IndiaThe 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.https://www.mdpi.com/1996-1073/18/9/2340battery energy storage systemimproved grey wolf optimizationimproved particle swarm optimizationoptimal siting and sizingphotovoltaic systemresource uncertainty |
| spellingShingle | Gauri Mandar Karve Mangesh S. Thakare Geetanjali A. Vaidya Optimal Siting and Sizing of Battery Energy Storage System in Distribution System in View of Resource Uncertainty Energies battery energy storage system improved grey wolf optimization improved particle swarm optimization optimal siting and sizing photovoltaic system resource uncertainty |
| title | Optimal Siting and Sizing of Battery Energy Storage System in Distribution System in View of Resource Uncertainty |
| title_full | Optimal Siting and Sizing of Battery Energy Storage System in Distribution System in View of Resource Uncertainty |
| title_fullStr | Optimal Siting and Sizing of Battery Energy Storage System in Distribution System in View of Resource Uncertainty |
| title_full_unstemmed | Optimal Siting and Sizing of Battery Energy Storage System in Distribution System in View of Resource Uncertainty |
| title_short | Optimal Siting and Sizing of Battery Energy Storage System in Distribution System in View of Resource Uncertainty |
| title_sort | optimal siting and sizing of battery energy storage system in distribution system in view of resource uncertainty |
| topic | battery energy storage system improved grey wolf optimization improved particle swarm optimization optimal siting and sizing photovoltaic system resource uncertainty |
| url | https://www.mdpi.com/1996-1073/18/9/2340 |
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