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针对水库运用常规防洪调度进行洪水调度时,因对规则的合理性描述不足而限制了其应用的问题,根据水库不同防洪对象的精细程度要求,结合预见期内水库预报最大洪水和实时水位,拟定分级防洪预报调度规则,建立带有惩罚机制的防洪调度规则参数优化模型,并提出改进遗传算法求解该模型,即通过混沌算法、混沌变异操作与适应度差值进化改善初始种群质量、提高算法局部与全局搜索能力,实现参数控制的防洪预报调度规则。实例应用表明,综合改进遗传算法较其他遗传算法优化性能有一定提高,防洪预报调度优化规则的调度结果优于常规调度规则,为防洪调度规则的合理应用提供了一种有效方法。
When the flood control of a reservoir is carried out by using the conventional flood control dispatching, the problem of its application is limited due to the insufficient description of the rationality of the rules. According to the requirements of the different flood control objects in the reservoir and the forecast of the maximum flood and the real-time water level of the reservoir in the forecast period, The rules of flood control and forecasting are established, and the parameters optimization model of flood control regulation with penalty mechanism is established. An improved genetic algorithm is proposed to solve this model. That is to say, chaos algorithm, chaos mutation operation and evolution of fitness difference are used to improve the initial population quality and improve the local And global search capabilities, flood control and forecasting rules to achieve parameter control. The example application shows that the general improved genetic algorithm has better performance than other genetic algorithms, and the scheduling result of flood control forecasting optimization rules is better than the conventional ones, which provides an effective method for the rational application of flood control rules.