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Optimal Location and Sizing of BESS for Performance Improvement of Distribution Systems with High DG Penetration
This work proposes an optimal location and sizing of battery energy storage system (BESS) installation for performance improvement of distribution systems with high distributed generation (DG) penetration level where the DGs comprise photovoltaics (PV) and wind turbines (WT). The installation of the...
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Published in: | International transactions on electrical energy systems 2022-06, Vol.2022, p.1-16 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | This work proposes an optimal location and sizing of battery energy storage system (BESS) installation for performance improvement of distribution systems with high distributed generation (DG) penetration level where the DGs comprise photovoltaics (PV) and wind turbines (WT). The installation of the BESS can reduce costs incurred in the systems, alleviate reverse power flow when the systems are in the high DG penetration level, and also achieve peak shaving during high demand. To find the optimal location and sizing of the BESS, three optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), and salp swarm algorithm (SSA), are applied, and their performances are compared. The considered objective function is the system costs consisting of transmission loss cost, peak power cost, and voltage deviation cost. The system performance improvement is compared in terms of transmission loss, peak demand, and voltage regulation reductions. IEEE 33- and 69-bus distribution systems with high DG penetration are tested to investigate the performance improvement of the BESS installation. The results found that the installation of the BESS could successfully decrease system cost, improve voltage profile, reduce power losses, alleviate reverse power flow, and achieve peak shaving where PSO and SSA are found to be the best competitive algorithms. So, the proposed method can be further applied to find the optimal location and sizing of the BESS to improve the performance of practical systems in the future. |
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ISSN: | 2050-7038 2050-7038 |
DOI: | 10.1155/2022/6361243 |