在新的波阻塞过器设计中应用随机分数搜索算法,以优化电力配电系统中波缓解和托管能力
Abdallah Aldosary1, Ziad M Ali2, Shady H E Abdel Aleem3
1Department of Computer Engineering, College of Engineering, Prince Sattam bin Abdulaziz University, Ar Riyadh, Saudi Arabia.
PloS one
|May 15, 2025
概括
这项研究优化了使用随机碎形搜索 (SFS) 算法对阻塞过器 (HBF) 的优化,以减少可再生能源系统中的波扭曲和功率损失. 优化过器显著提高了电源质量,并增加了可持续能源整合的托管能力.
科学领域:
- 电气工程 电气工程
- 电力系统分析 分析 分析
- 优化算法 优化算法
背景情况:
- 可再生能源 (RES) 集成对由于逆变器产生的波器造成的电力质量构成挑战.
- 波扭曲降低了系统性能,增加了损失,并有可能损坏设备.
- 有效的波减缓对于具有高可再生能源透率的稳定和高效电网至关重要.
研究的目的:
- 开发优化波阻塞过器 (HBF) 以减少波扭曲和功率损失.
- 增强和约束托管能力 (HCHC) 以增加可再生能源的整合.
- 在HBF设计中比较多目标人工蜂鸟 (MOAHA) 和多目标原子轨道搜索 (MOAOS) 算法的性能.
主要方法:
- 利用随机碎形搜索 (SFS) 算法进行HBF设计优化.
- 采用多目标优化算法 (MOAHA,MOAOS) 来平衡HCHC最大化和功耗损失最小化.
- 在三个不同的测试系统 (TS1,TS2,TS3) 中验证了拟议的HBF.
主要成果:
- 在测试系统中,SFS优化的HBF显著降低了总波电压扭曲 (THDV) 和总需求扭曲 (TDDI).
- 在TS2和TS3中,THDV降低了高达45.71%,TDDI降低了99.96%.
- 在提高HCHC方面,MOAOS表现出卓越的性能,在TS3中与文献相比增加了高达16.4%.
结论:
- 优化SFS的HBF有效地减轻了波,并最大限度地减少了发电系统中的功率损失.
- 拟议的方法提高了系统容纳可再生能源的能力.
- MOAOS是一种高效的算法,用于优化HBF设计,以提高电网稳定性和可再生能源集成.
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