调查等级顺序中心系的方法,以实现最佳的生成控制
T Varshney1, A V Waghmare2, V P Singh2
1Department of EECE, Sharda University, Greater Noida, Uttar Pradesh, India.
Scientific reports
|May 17, 2024
概括
本研究介绍了用于优化电力系统中自动发电控制 (AGC) 的排列顺序中心 (ROC) 方法. 贾亚优化算法 (JOA) 提高了PID控制器的性能,以实现稳定的电网运行.
科学领域:
- 电气工程 电气工程
- 控制系统工程 控制系统工程
- 优化技术 优化技术
背景情况:
- 多标准决策 (MCDM) 是复杂的,特别是在电力系统控制中.
- 在相互连接的电力系统中,自动发电控制 (AGC) 需要平衡多个性能目标.
研究的目的:
- 为 AGC 提出 Rank Order Centroid (ROC) 方法,用于在 MCDM 中权衡子目标函数.
- 使用ROC和优化算法设计和优化用于双区域互连电力系统 (TAIPS) 的比例整合导数 (PID) 控制器.
主要方法:
- 排列顺序中位数 (ROC) 方法用于确定频率偏差,控制错误和连线功率波动的积分时间绝对误差 (ITAE) 的权重.
- 一个PID控制器是基于权重目标函数设计的.
- 为了优化目标函数,实施了Jaya优化算法 (JOA),与TLBOA,LJA,NMSA,EHOA和DEA相比.
- 通过统计分析进行了六项案例研究,包括弗里德曼等级测试,以验证绩效.
主要成果:
- 基于JOA的PID控制器在各种负载条件下在管理频率和连线功率波动方面表现出卓越的性能.
- 使用ROC改进的控制器设计,对子目标函数进行系统加权.
- 对比分析证实了JOA与其他测试的优化算法的有效性.
结论:
- 拟议的ROC方法与JOA相结合,为设计TAIPS中AGC的强大的PID控制器提供了一种有效的方法.
- 这种方法通过优化平衡多个控制标准来提高系统的稳定性和性能.
- 这些发现为未来的智能电力系统控制研究提供了有价值的框架.
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