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Multi-objective heuristic guide vane closure scheme optimisation of hydroturbine generating unit

机译：多目标启发式导向叶片封闭方案优化水闸发电机

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摘要

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.
机译：在极端条件下，Ructurbine生成单元（HTGU）中的导向叶片闭合方案（GVCS）优化是水电站设计和操作中最重要的问题之一。它是一种多目标约束优化问题，其中包含许多系统状态的液压和机械动态过程的协调。在这样的问题中，传统的优化目标通常包括控制HTGU的转速和抑制不同位置处的液压的波动幅度。为了提高负载抑制过程中的整体控制性能，提出了一种改进的多目标二档进化算法（TAEA），用于具有混沌运算符的GVC。基于Taea的多目标优化仔细获取多重客观功能和相关的约束处理，包括对转速峰值，速度波动，电涌油罐水平，调速调速器运动和液压振荡的限制。用所提出的优化方案和比较方法进行负载排斥条件下的真实水闸单元的仿真实验。结果表明，TAEA算法可以实现更好的整体性能，并有助于HTGU的操作稳定性。

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