优化混合动力系统的控制和管理,包括PV风能和电池超级电容器,使用COOT算法
Abdelkader Halmous1, Youcef Oubbati2, Mohamed Lahdeb2
1LACoSERE Laboratory University of Amar TELIDJI, Laghouat, 03000, Algeria. ab.halmous@lagh-univ.dz.
Scientific reports
|September 29, 2025
概括
这项研究通过优化混合动力电力系统来增强可再生能源的整合. 一种新的控制策略显著减少了波扭曲,并改善了从太阳能和风能来源提取能量.
科学领域:
- 电气工程 电气工程
- 可再生能源系统可再生能源系统
- 控制系统 控制系统
背景情况:
- 太阳能光伏和风力轮机等可再生能源的电网整合带来了挑战,尤其是波扭曲.
- 现有的控制策略往往难以平衡最大功率提取与电网稳定性.
研究的目的:
- 为连接到电网的混合动力电力系统开发和评估先进的控制策略.
- 为了最大限度地利用从光伏阵列和风力轮机中获得的能量,同时最大限度地减少向电网注入的总波扭曲 (THD).
主要方法:
- 实施混合储能系统 (电池和超级电容器).
- 使用COOT鸟类算法优化用于各种控制循环 (MPPT,PMSG,BESS,超级电容器,GSC) 的级联PI-PID控制器的开发.
- 在现实,动态的操作条件下与基因算法 (GA) 调整的 PI 控制器进行比较.
主要成果:
- 拟议的PI-PID控制器实现了电压和电流振荡的显著降低 (分别为30%和81%).
- 超级电容器有效地减轻了控制器产生的峰值,提高了系统的稳定性.
- 能源管理战略成功地在可变条件下最大限度地利用可再生能源.
结论:
- 与传统方法相比,COOT优化的级联PI-PID控制器为混合可再生能源系统提供了卓越的性能.
- 混合存储系统,特别是超级电容器,对于管理间歇性和提高电源质量至关重要.
- 拟议的方法确保了高效的能源利用和电网稳定性,在复杂的,现实世界的场景.
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