混合正弦共弦和斑点的Hyena基于黑猩猩优化用于PI控制器调在微电网中
Saleem Mohammad1, S D Sundarsingh Jeebaseelan2
1Department of Electrical and Electronics Engineering, Sathyabama Institute of Science & Technology, Chennai, 600119, India. saleem238@gmail.com.
Scientific reports
|October 30, 2024
概括
一个新的混合优化算法精确调整微电网控制器,以获得更好的稳定性和性能. 这种方法更有效地将可再生能源与主电网整合在一起.
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:
- 微电网对于整合各种可再生能源 (光伏,风能,燃料电池,电池) 是必不可少的.
- 对这些系统的有效控制对于稳定性和高效的能源管理至关重要.
- 比例整合 (PI) 控制器被广泛使用,但需要精确的调以获得最佳性能.
研究的目的:
- 开发和验证一种新的混合优化算法,用于在复杂的微电网系统中调整PI控制器.
- 提高微电网的动态响应,稳定性和整体性能,使用多种可再生能源.
- 为了证明拟议的调方法在传统技术上的优越性.
主要方法:
- 开发了一个基于Hyena的混合正弦和斑点黑猩猩优化算法 (混合SSC).
- 混合SSC算法用于调整微电网系统内的8个PI控制器.
- 在MATLAB/SIMULINK中通过最小化时间加权二次误差 (ITSE) 的积分来评估性能.
主要成果:
- 混合SSC算法实现了PI控制器的精确调整,显著提高了微电网的性能.
- 模拟证实了微电网系统的增强稳定性,更快的响应时间和更高的效率.
- 拟议的方法证明了可靠的运行和可再生能源的无整合.
结论:
- 混合SSC算法为现代微电网提供了有效的智能控制策略.
- 这种方法促进了复杂的能源系统的最佳性能,使用多种可再生能源.
- 该研究强调了先进的混合优化技术在电力系统工程中的重要性.
相关概念视频
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