水轮机
计算机科学
水力机械
涡轮机
控制理论(社会学)
最优控制
算法
控制(管理)
数学优化
数学
工程类
人工智能
机械工程
作者
Xin Xia,Jie Ji,Chaoshun Li,Xiaoming Xue,Xiaolu Wang,Chu Zhang
出处
期刊:Complexity
[Hindawi Limited]
日期:2019-01-01
卷期号:2019 (1)
被引量:11
摘要
Hydraulic turbine governing system (HTGS) is essential equipment which regulates frequency and power of the power grids. In previous studies, optimal control of HTGS is always aiming at one single operation condition. The variation of operation conditions of HTGS is seldom considered. In this paper, multiobjective optimal function is proposed for HTGS under multiple operation conditions. In order to optimize the solution to the multiobjective problems, a novel multiobjective grey wolf optimizer algorithm with searching factor (sMOGWO) is also proposed with two improvements: adding searching step to search more no‐domain solutions nearby the wolves and adjusting control parameters to keep exploration ability in later period. At first, the searching ability of the sMOGWO has been verified on several UF test problems by statistical analysis. And then, the sMOGWO is applied to optimize the solutions of the multiobjective problems of HTGS, while different algorithms are employed for comparison. The experimental results indicate that the sMOGWO is more effective algorithm and improves the control quality of the HTGS under multiple operation conditions.
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