适用于水平轴风力轮机的最佳混合型-3模糊控制器:比较研究
Adnan Qahtan Adnan1, Mohammed Khalil Hussain1, Ardashir Mohammadzadeh2
1Department of Energy Engineering, University of Baghdad, Baghdad, Iraq.
ISA transactions
|April 10, 2025
概括
本研究介绍了一种最佳的混合型-3模糊-PID控制器用于风力轮机叶片转角控制,其性能优于类型-1和类型-2模糊逻辑控制器. 新的控制器确保更稳定的发电,特别是在波动的风条件下.
科学领域:
- 可再生能源系统可再生能源系统
- 控制工程 控制工程 控制工程
- 在工程领域的人工智能.
背景情况:
- 风力轮机发电受到叶片转角 (BPA) 控制的重大影响,而这种控制受到风速波动和固有的系统不确定性所带来的挑战.
- 现有的1型和2型模糊逻辑控制器在风力轮机系统中管理高水平的不确定性方面存在局限性.
研究的目的:
- 提出和评估一种新的最佳混合型-3模糊逻辑控制器,用于增强风力轮机叶片转角控制 (PAC).
- 为了比较类型-3模糊逻辑控制器与类型-1和类型-2模糊逻辑控制器以及混合模糊-PID控制器的性能.
- 确定最佳的模糊推理系统 (FIS) 和调方法,以提高发电稳定性.
主要方法:
- 六个控制器的实现和比较:类型-1模糊逻辑控制器 (T1-FLC),间隔类型-2模糊逻辑控制器 (IT2-FLC),间隔类型-3模糊逻辑控制器 (IT3-FLC),以及它们的最佳混合模糊-PID控制器 (HT1-FPIDC,HT2-FPIDC,HT3-FPIDC) 变体.
- 对Mamdani和Sugeno模糊推理系统 (FIS) 进行BPA控制的评估.
- 使用基因算法 (GA) 和混合控制器的粒子群优化 (PSO) 优化PID参数.
主要成果:
- 与500kW水平轴风力轮机的Mamdani FIS相比,Sugeno FIS的输出发电稳定性优越.
- 基于PSO的Mamdani FIS的最佳混合型-3模糊-PID控制器 (HT3-FPIDC) 实现了比PSO (Sugeno FIS) 的最佳HT2-FLC低19.74%的绝对总和误差 (ASE) 和比PSO (Sugeno FIS) 的最佳HT1-FLC低39.03%的ASE.
- 使用PSO和Mamdani FIS提出的最佳HT3-FPIDC在额定值下产生一致输出功率的最佳结果.
结论:
- 最佳的混合型-3模糊PID控制器,特别是当与PSO调整并采用Mamdani FIS时,为风力轮机叶片俯仰角度控制提供了卓越的性能.
- 3型模糊逻辑控制器在处理不确定性方面提供了显著的优势,导致更稳定和一致的风力发电.
- 这些发现强调了先进的模糊逻辑控制策略在优化可再生能源系统方面的潜力.
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