一个新的TID + IDN控制器与coatis优化算法在放松管制的混合动力系统下调整
Geetanjali Dei1,2, Deepak Kumar Gupta3, Binod Kumar Sahu2
1School of Electrical Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, 751024, India.
Scientific reports
|February 9, 2025
概括
一个新的控制器结合倾斜整数导数 (TID) 和整数导数与过器 (IDN) 提供了改进的负载频率控制在混合动力系统. 通过使用Coatis优化算法 (COA) 进行优化,它提高了不同能源的稳定性和性能.
科学领域:
- 电气工程 电气工程
- 控制系统 控制系统
- 整合可再生能源的整合
背景情况:
- 在具有多种发电源的多区域电力系统中保持电力平衡是复杂的.
- 将可再生能源与传统单元相结合,为自动负载频率控制 (ALFC) 带来了稳定性挑战.
研究的目的:
- 为ALFC在一个三区域,多源,不受管制的电力系统中引入一种新的,高效的控制器.
- 在各种操作条件下对拟议控制器的性能进行评估,并将其与现有方法对比.
主要方法:
- 设计了一种平行组合的倾斜集成导数 (TID) 和集成导数与波器 (IDN) 控制器.
- 使用先进的Coatis优化算法 (COA) 来优化控制器参数.
- 分析了系统性能与储能单元 (Redox流电池) 和不同的自由市场交易,包括生产限制.
主要成果:
- 与独立的TID和IDN控制器相比,提议的TID+IDN控制器表现出更高的性能.
- 通过使用COA进行优化,控制器在短暂响应中实现了0.1233的低整数时间绝对误差 (ITAE).
- 在所有三个区域都观察到频率偏差结算时间的显著改善.
结论:
- 通过COA优化的新型TID+IDN控制器,为复杂的混合动力动力系统的负载频率控制提供了强大而有效的解决方案.
- 控制器的有效性在放松监管的市场场景,储能集成和系统参数变化下得到验证.
- 与现有的控制策略相比,这种方法显著提高了过渡稳定性和系统性能.
关键词:
科蒂斯的优化算法 (COA)改进的松鼠搜索算法 (ISSA)独立的系统运营商 (ISO)具有第一阶波效应 (IDN) 的积分衍生式.积分时间乘以绝对误差 (ITAE)负载频率控制 (LFC) 是指负载频率控制.在 PIDID 里面.粒子群集优化 (PSO) 是一种松鼠搜索算法 (SSA) 是一种搜索算法.倾斜的集成衍生控制器 (TID)更多相关视频
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