混合鱼捕食和正弦共弦算法用于管理风能影响的电力传输拥堵
Susovan Dutta1, Bishaljit Paul2, Barnali Kundu1
1Department of Electrical Engineering, Guru Nanak Institute of Technology Kolkata, West Bengal, Kolkata, India.
Scientific reports
|September 5, 2025
概括
这项研究引入了一种混合优化算法 (MRFO-SCA),用于电力系统的拥堵管理,有效降低成本并通过风能集成提高系统性能.
科学领域:
- 电气工程
- 优化算法
- 可再生能源系统
背景情况:
- 电力系统的输电线路拥堵造成了巨大的成本.
- 整合风能系统等可再生能源加剧了拥堵问题.
- 现有的拥堵管理 (CM) 技术需要加强优化策略.
研究的目的:
- 为有效的电力系统拥堵管理提出混合Manta射线造优化-正弦共弦算法 (MRFO-SCA).
- 通过最佳的WES放置和发电机重新调度,最大限度地降低拥堵成本和系统损失,同时改善电压配置.
- 增强优化算法的探索和利用能力,以快速发现全球最佳.
主要方法:
- 通过将Sine Cosine算法 (SCA) 集成到Manta ray Forging Optimization (MRFO) 中,开发了一种混合MRFO-SCA算法.
- 使用总线灵敏度因子 (BSF) 优化WES的位置,以影响拥堵线路中的电流.
- 应用MRFO-SCA以优化发电机的功率调度,以减轻输电线路的拥堵.
主要成果:
- 在基准函数上,MRFO-SCA算法表现出卓越的性能.
- 在IEEE-30总线系统上验证,该方法显著降低了拥堵成本.
- 与最近的优化技术相比,降低了高达18.45%的拥堵成本.
结论:
- 提供高效准确的电力系统拥堵管理解决方案.
- 混合方法有效地集成WES,最大限度地减少系统损失,并改善总线电压.
- 在合速度和计算时间方面优于现有方法.
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