一个新的智能优化模型参考自适应控制器,使用基于GA和WOA的MPPT技术用于光伏系统
Nassir Deghfel1, Abd Essalam Badoud2, Farid Merahi1
1Setif Automatic Laboratory, Electrical Engineering Department, Ferhat Abbas University Setif 1, Setif, Algeria.
Scientific reports
|March 22, 2024
概括
本研究介绍了光伏系统的最佳自适应控制器,以在快速的天气变化期间最大限度地提高功率输出. 这种新方法确保了高效的能源采集,改善了可再生能源的整合.
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
- 控制理论 控制理论
背景情况:
- 光伏 (PV) 系统对于可持续的能源发电至关重要.
- 高效的最大功率点跟踪 (MPPT) 对于光伏系统的性能至关重要,特别是在可变条件下.
- 现有的MPPT技术面临着辐射和温度等快速变化的环境因素带来的挑战.
研究的目的:
- 为在动态天气条件下运行的光伏系统开发创新和强大的MPPT方法.
- 通过应对MPPT挑战,提高光伏系统的效率和功率输出.
- 使用元启发式算法优化控制器参数以提高性能.
主要方法:
- 基于麻省理工学院规则的新型最佳模型参考适应控制器 (MRAC) 设计用于快速,无波纹的全球最大功率跟踪.
- 使用遗传算法 (GA) 和鱼优化算法 (WOA),优化了MRAC控制器的适应收益.
- 适应性神经模糊推理系统 (ANFIS) 用于生成MPPT的参考电压.
主要成果:
- 建议的最佳MRAC控制器通过MATLAB/Simulink模拟在不同温度和辐射条件下证明了有效的MPPT性能.
- 控制器成功地实现了最大功率提取,没有显著的输出.
- 对比分析显示,最佳的MRAC (GA和WOA) 优于传统的增量行为 (INC) 方法.
结论:
- 由GA和WOA优化开发的最佳MRAC控制器,在波动的环境条件下,为光伏系统中的MPPT提供了卓越的解决方案.
- 集成ANFIS用于参考电压生成进一步提高了控制器的适应性和有效性.
- 这项研究有助于更有效,更可靠地将太阳能集成到电网中.
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