通过使用混合的和搜索和矮人松鼠优化算法来提高AVR系统的性能
Omar M Hesham1, Mahmoud A Attia2, S F Mekhamer3
1Department of Electrical Power and Machines, Faculty of Engineering, Ain Shams University, Cairo, Egypt.
Scientific reports
|November 8, 2024
概括
这项研究引入了一种新的混合优化算法,结合Harmony Search和矮人蒙古斯优化,以提高自动电压调节器 (AVR) 控制器的性能. 这种新的方法提高了面临复杂负载需求的电力系统的效率和可靠性.
科学领域:
- 电气工程 电气工程
- 控制系统 控制系统
- 优化算法 优化算法
背景情况:
- 传统的自动电压调节器 (AVR) 设计面临着越来越复杂的电力系统和各种负载的挑战.
- 新的优化方法对于提高AVR效率,可靠性和适应性至关重要.
研究的目的:
- 通过优化比例-积分-导数 (PID) 和比例-积分-导数加速 (PIDA) 参数来提高AVR系统控制器的性能.
- 引入一种新的混合优化技术,将和搜索 (HS) 和矮人蒙古斯优化 (DMO) 结合起来.
主要方法:
- 开发了一个混合HS-DMO算法来调整PID和PIDA控制器参数.
- 拟议的算法通过将其性能与各种优化技术进行比较来验证.
- 通过使用时间和频率域性能指标以及动态输入信号进行了评估.
主要成果:
- 与现有方法相比,混合HS-DMO算法在PID控制器的超越和阶段边缘方面取得了显著的改进.
- 对于PIDA控制器来说,混合方法也产生了更好的超标性能.
- 在动态干扰下,控制器表现出强大的性能,超速改进率从0.3%到20%不等.
结论:
- 拟议的混合HS-DMO优化方法有效地提高了AVR PID和基于PIDA的控制器性能.
- 该研究详细分析了控制器在各种条件下的时间和频率领域的行为.
- 这种新的混合方法为提高AVR系统的适应性和效率提供了可靠的解决方案.
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