各种优化算法用于在不同网络中高效地放置和调整光伏分布式发电的尺寸
Ahmed A Zaki Diab1,2, Fayza S Mahmoud1, Hamdy M Sultan1
1Department of Electrical Engineering, Faculty of Engineering, Minia University, Minia, Egypt.
PloS one
|April 2, 2025
概括
这项研究利用先进的算法优化了可再生分布式发电 (RDG) 在电力系统中的配置. 海洋预测算法 (MPA) 和Salp Swarm算法 (SSA) 在改善电压配置和减少功率损失方面被证明是最有效的.
科学领域:
- 电气工程 电气工程
- 电力系统 电力系统
- 整合可再生能源的整合
背景情况:
- 像光伏 (PV) 和风力轮机 (WTs) 这样的可再生分布式发电 (RDGs) 对现代配电系统至关重要.
- 优化RDGs的集成可以改善电压配置并最大限度地减少功率损失,解决分布式发电 (DG) 分配的关键挑战.
- 现有的优化技术需要全面评估,以有效地部署和大小化R & DG.
研究的目的:
- 确定射线分布式系统 (RDS) 中 RDG 的最佳位置和容量.
- 为了比较 RDG 集成的各种优化算法的性能.
- 在标准和现实世界电力系统上验证选定的算法的有效性.
主要方法:
- 两阶段的方法:节点选择的损失灵敏度因子 (LSF),然后是RDG放置和大小的优化算法.
- 评估的算法:Salp Swarm算法 (SSA),海洋预测算法 (MPA),灰狼优化器 (GWO),改进的灰狼优化器 (IGWO) 和海优化算法 (SOA).
- 在IEEE 33,69和118总线RDS上进行验证,以及来自埃及的15个总线现实世界系统.
主要成果:
- 海洋预测算法 (MPA) 和Salp Swarm算法 (SSA) 展示了卓越的性能.
- 在所有测试系统中观察到电压配置的显著改善.
- 通过RDGs的最佳集成,可以实现大幅减少功率损失.
结论:
- MPA和SSA是RDS中RDG分配的高度有效的优化技术.
- 拟议的方法成功提高了电力质量,并减少了配电系统的损失.
- 这些发现为寻求有效整合可再生能源的公用事业提供了宝贵的见解.
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