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Optimal Management of Sewer Networks during Wet Weather Event by Stochastic Dynamic Programming

机译：随机动态规划在雨天下水道网络优化管理中的应用

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The paper addresses the problem of how to manage real time operations of a sewer network pumping station under rainy episodes. Whereas rules-based control laws are already implemented, the paper proposes a new optimal control model based on stochastic dynamic programming with two approaches depending on how to represent the stochastic process of the model which is the water inflow of the pumping station. The first approach models the inflow at each time step as a stochastic variable with a known probability density while the second represents the inflow as a markovian process with a known transition matrix. Simulations performed with a typical rainy episode show the benefits of stochastic dynamic programming in reducing water overflowing in cities and water rejection in natural environment.
机译：本文解决了在下雨天如何管理下水道网络泵站实时运行的问题。尽管已经实施了基于规则的控制律，但本文提出了一种基于随机动态规划的新的最优控制模型，该方法基于如何表示模型的随机过程（即泵站的入水量），采用两种方法。第一种方法将每个时间步长的流入建模为具有已知概率密度的随机变量，而第二种方法将流入表示为具有已知过渡矩阵的马尔可夫过程。在典型的多雨事件中进行的模拟显示了随机动态编程在减少城市中的水溢流和自然环境中的排水方面的优势。

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