Performance of pelican optimizer for energy losses minimization via optimal photovoltaic systems in distribution feeders.
In distribution grids, excessive energy losses not only increase operational costs but also contribute to a larger environmental footprint due to inefficient resource utilization. Ensuring optimal placement of photovoltaic (PV) energy systems is crucial for achieving maximum efficiency and reliabili...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0319298 |
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| Summary: | In distribution grids, excessive energy losses not only increase operational costs but also contribute to a larger environmental footprint due to inefficient resource utilization. Ensuring optimal placement of photovoltaic (PV) energy systems is crucial for achieving maximum efficiency and reliability in power distribution networks. This research introduces the Pelican Optimizer (PO) algorithm to optimally integrate solar PV systems to radial electrical distribution grids. The PO is a novel bio-inspired optimization algorithm that draws inspiration from pelicans' intelligence and behavior which incorporates unique methods for exploration and exploitation, improving its effectiveness in various optimization challenges. It introduces a hyper-heuristic for phase change, allowing the algorithm to dynamically adjust its strategy based on the problem's characteristics. The suggested PO aims to reduce the energy losses to the possible minimum value. The developed PO version is tested on the Ajinde 62-bus network, a practical Nigerian distribution system, and a typical IEEE grid with 69 nodes. The simulation findings demonstrate the enhanced PO version's efficacy, showing a significant decrease in losses of energy. With the Ajinde 62-node grid, the suggested PO version obtains a substantial 30.81% decrease in the total energy loss expenses in contrast to the initial scenario. Similarly, the IEEE 69-node grid achieves a significant decrease of 34.96%. Additionally, the model's findings indicate that the proposed PO version performs comparably to the Differential Evolution (DE), Particle Swarm Optimization (PSO), and Satin bowerbird optimizer (SBO) algorithms. |
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| ISSN: | 1932-6203 |