Performance of pelican optimizer for energy losses minimization via optimal photovoltaic systems in distribution feeders.

IF 2.6 3区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
PLoS ONE Pub Date : 2025-03-12 eCollection Date: 2025-01-01 DOI:10.1371/journal.pone.0319298
Zuhair Alaas, Ghareeb Moustafa, Hany Mansour
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Abstract

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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鹈鹕优化器在配电网优化光伏系统中能量损失最小化的性能。
在配电网中,过大的能源损耗不仅增加了运行成本,而且由于资源利用效率低下,造成了更大的环境足迹。确保光伏(PV)能源系统的最佳配置对于实现配电网络的最高效率和可靠性至关重要。本研究引入Pelican Optimizer (PO)算法来优化太阳能光伏系统与径向配电网的整合。PO是一种新型的仿生优化算法,它从鹈鹕的智力和行为中汲取灵感,结合了独特的勘探和开采方法,提高了其在各种优化挑战中的有效性。引入了相位变化的超启发式算法,允许算法根据问题的特征动态调整策略。建议的PO旨在将能量损失减少到可能的最小值。开发的PO版本在尼日利亚实际配电系统Ajinde 62总线网络和典型的IEEE 69节点电网上进行了测试。仿真结果证明了增强后的PO版本的有效性,显示出能量损失的显著减少。在Ajinde 62节点电网中,建议的PO版本与初始方案相比,总能量损失费用大幅降低30.81%。同样,IEEE 69节点网格也实现了34.96%的显著下降。此外,该模型的研究结果表明,所提出的PO版本的性能与差分进化(DE),粒子群优化(PSO)和缎面园丁鸟优化(SBO)算法相当。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
PLoS ONE
PLoS ONE 生物-生物学
CiteScore
6.20
自引率
5.40%
发文量
14242
审稿时长
3.7 months
期刊介绍: PLOS ONE is an international, peer-reviewed, open-access, online publication. PLOS ONE welcomes reports on primary research from any scientific discipline. It provides: * Open-access—freely accessible online, authors retain copyright * Fast publication times * Peer review by expert, practicing researchers * Post-publication tools to indicate quality and impact * Community-based dialogue on articles * Worldwide media coverage
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