Open AccessMulti‐objective heuristic guide vane closure scheme optimisation of hydroturbine generating unit
Author(s) -
Chen Qijuan,
Zhang Haiku,
Zheng Yang,
Jiang Wen,
Wang Weiyu,
You Shihao
Publication year - 2020
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
ISSN - 1752-1424
DOI - 10.1049/iet-rpg.2019.1186
Subject(s) - control theory (sociology) , governor , closure (psychology) , hydropower , process (computing) , hydraulic machinery , unit load , heuristic , constraint (computer aided design) , scheme (mathematics) , computer science , stability (learning theory) , load rejection , control engineering , mathematical optimization , engineering , control (management) , mathematics , mechanical engineering , turbine , mathematical analysis , electrical engineering , artificial intelligence , machine learning , economics , market economy , aerospace engineering , operating system
Guide vane closure scheme (GVCS) optimisation in hydroturbine generating unit (HTGU) under extreme conditions is one of the most important issues in hydropower plant design and operation. It is a kind of multiobjective constrained optimisation problem that contains the coordination of hydraulic and mechanical dynamic processes of many system states. In such a problem, the traditional optimisation objectives often include the control of the rotational speed of the HTGU and the suppression of the fluctuation amplitudes of the hydraulic pressure at different locations. In order to improve the overall control performances in load rejection process, an improved multi‐objective two‐archive evolutionary algorithm (TAEA) is put forward for GVCS with chaotic operators. The TAEA‐based multi‐objective optimisation carefully takes the multiple objective functions and the relevant constraint treatments including the limits on rotational speed peak, speed fluctuations, surge tank water levels, speed governor movement and hydraulic pressure oscillations into consideration. Simulation experiments of a real hydroturbine unit under load rejection condition are conducted with the proposed optimisation scheme and comparative methods. The results indicate that TAEA algorithm can achieve better overall performances and contribute to the operational stability of HTGU.