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Limited adaptive genetic algorithm for inner-plant economical operation of hydropower station

机译：水电站厂内经济运行的有限自适应遗传算法。

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摘要

A limited adaptive genetic algorithm (LAGA) is proposed in the paper for inner-plant economical operation of a hydropower station. In the LAGA, limited solution strategy, with the feasible solution generation method for generating an initial population and the limited perturbation mutation operator, is presented to avoid hydro units operating in cavitation-vibration regions. The adaptive probabilities of crossover and mutation are introduced to improve the convergence speed of the genetic algorithm (GA). Furthermore, the performance of the limited solution strategy and the adaptive parameter controlling improvement are checked against the historical methods, and the results of simulating inner-plant economical operation of the Three Gorges hydropower station demonstrate the effectiveness of the proposed approach. First, the limited solution strategy can support the safety operations of hydro units by avoiding cavitation-vibration region operations, and it achieves a better solution, because the non-negative fitness function is achieved. Second, the adaptive parameter method is shown to have better performance than other methods, because it realizes the twin goals of maintaining diversity in the population and advancing the convergence speed of GA. Thus, the LAGA is feasible and effective in optimizing inner-plant economical operation of hydropower stations.
机译：提出了一种有限自适应遗传算法（LAGA），用于水电站厂内经济运行。在LAGA中，提出了有限解策略，以及用于生成初始种群的可行解生成方法和有限扰动突变算子，以避免水力单元在空化振动区域中运行。引入了交叉和变异的自适应概率，以提高遗传算法（GA）的收敛速度。此外，对照历史方法检查了有限解策略的性能和自适应参数控制的改进，并且对三峡水电站的厂内经济运行进行仿真的结果证明了该方法的有效性。首先，有限解决方案策略可以通过避免空化-振动区域操作来支持水电机组的安全运行，并且由于获得了非负适应性功能，因此可以实现更好的解决方案。其次，自适应参数法具有比其他方法更好的性能，因为它实现了维持种群多样性和提高遗传算法收敛速度的双重目标。因此，LAGA在优化水电站厂内经济运行中是可行和有效的。

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