Optimal Placement and Sizing of Renewable Distributed Generators for Power Loss Reduction in Microgrid using Swarm Intelligence and Bio-inspired Algorithms
DOI:
https://doi.org/10.54327/set2025/v5.i1.208Keywords:
bat algorithm, distributed generators, micro-grids, optimal placement and sizing, particle swarm optimization, renewable energy sourcesAbstract
To responsibly fulfill the world's expanding electrical energy needs, renewable energy sources are now essential. Future energy policies must include these sources—like solar and wind energy—because they lower carbon emissions and save the environment. The optimal location and sizing of renewable distributed generators (OLSRDG) in the microgrid are determined in this study by applying one of the universal bio-inspired techniques and one of the swarms’ algorithms. With lower power losses, an improved voltage profile, increased dependability, and stability, the goal is to improve energy efficiency and lessen reliance on the main grid while also enhancing the grid's overall performance and stability. The acquired results are promising and show the efficacy and resilience of the suggested technique in solving OLSRDG problems compared to recently published results. The results showed that the optimization process led to loss reduction, with the percentage of power loss reduction ranging from 45.387% to 73.89% using the PSO. While the percentage of loss reduction using the BAT ranged from 51.78% to 71.57%.
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No data or additional materials were utilized for the research described in the article.
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Copyright (c) 2025 Nabil MEZHOUD, Ahmed Bahri, Bilel Ayachi, Farouk Boukhenoufa, Lakhdar Bouras

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