模糊控制器驱动的模式搜索优化用于DC-DC增强转换器以提高光伏MPPT性能
Maher G M Abdolrasol1, Sieh Kiong Tiong2, Pin Jern Ker3
1Institute of Sustainable Energy, Universiti Tenaga Nasional, Kajang, 43000, Malaysia. maher.abdolrasol@uniten.edu.my.
Scientific reports
|September 5, 2025
概括
这项研究使用基于模糊的模式搜索 (PS) 优化最大功率点跟踪 (MPPT) 控制器来增强太阳能转换. 与传统方法相比,它实现了更高的效率和适应不断变化的条件.
科学领域:
- 可再生能源系统
- 电力电子
- 智能控制系统
背景情况:
- 太阳能系统需要高效的最大功率点跟踪 (MPPT) 来最大限度地获得能源.
- 传统的MPPT算法在动态环境条件下面临挑战.
- 智能控制技术可以提高MPPT的性能.
研究的目的:
- 使用基于模糊的模式搜索 (PS) 优化开发和评估智能MPPT控制器.
- 在不同的辐射和温度下提高DC-DC增压转换器的能量转换效率.
- 将拟议的模糊PS MPPT控制器的性能与其他优化算法和Perturb and Observe (P&O) 方法进行比较.
主要方法:
- 用于MPPT的模糊逻辑控制器实现直流-直流提升转换器.
- 使用模式搜索 (PS) 优化的模糊成员函数 (MFs) 的优化.
- 使用粒子群优化 (PSO) 和基因算法 (GA) 进行模糊控制器调整的比较分析,使用根平均平方误差 (RMSE) 作为目标函数.
主要成果:
- 模糊PS优化在100次代后实现了最低的RMSE (0.6861),超过了模糊GA (1.257) 和模糊PSO (0.9454).
- 拟议的控制器能够有效地适应辐射和温度变化,达到最高功率74.48kW.
- 平均MPPT效率达到了99.7%,明显超过了P&O算法.
结论:
- 模糊PS优化的MPPT控制器提供卓越的跟踪性能和能量转换效率.
- 智能控制策略有效地处理太阳辐射和温度的动态变化.
- 这种方法代表了优化太阳能采集系统的重大进步.
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