Multiobjective Optimal Control for Hydraulic Turbine Governing System Based on an Improved MOGWO Algorithm

Xin Xia, Jie Ji, Chao-shun Li, Xiaoming Xue, Xiaolu Wang and Chu Zhang

Complexity, 2019, vol. 2019, 1-14

Abstract:

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.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:3745924

DOI: 10.1155/2019/3745924

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