用于集成最优压力管理与自清洗控制的动态自适应网络
Dynamically adaptive networks for integrating optimal pressure management and self-cleaning controls
AI总结：
本文针对动态自适应配水网络中相互冲突的压力管理（AZP）与自清洗能力（SCC）问题，提出一种联合优化阀门位置与运行设置的双目标控制设计方法，利用加权和标量化与凸启发式算法近似Pareto前沿，并验证了分层设计策略与自适应控制方案的有效性。
摘要：
本文研究了在动态自适应配水网络中集成最优压力管理与自清洗控制的问题。我们回顾了现有的单目标阀门布置与控制问题，旨在最小化平均区域压力（AZP）并最大化自清洗能力（SCC）。由于AZP和SCC是相互冲突的目标，我们构建了一个双目标控制设计问题，联合优化压力控制阀和自动冲洗阀的位置与运行设置。我们使用加权和标量化方法近似Pareto前沿，该方法利用先前开发的凸启发式算法来求解参数化单目标问题序列。得到的Pareto前沿表明，在AZP性能上做出最小权衡的情况下，SCC可以获得显著改善。此外，我们证明分层设计策略能够为两个目标产生高质量解。该分层设计首先考虑为实现主要AZP目标而布置压力控制阀，随后布置自动冲洗阀以增强SCC条件。另外，我们研究了一种自适应控制方案，用于在AZP和SCC控制之间动态切换。我们在具有互连和分支拓扑的案例网络上展示了这些控制挑战。
英文摘要：
This paper investigates the problem of integrating optimal pressure management and self-cleaning controls in dynamically adaptive water distribution networks. We review existing single-objective valve placement and control problems for minimizing average zone pressure (AZP) and maximizing self-cleaning capacity (SCC). Since AZP and SCC are conflicting objectives, we formulate a bi-objective design-for-control problem where locations and operational settings of pressure control and automatic flushing valves are jointly optimized. We approximate Pareto fronts using the weighted sum scalarization method, which uses a previously developed convex heuristic to solve the sequence of parametrized single-objective problems. The resulting Pareto fronts suggest that significant improvements in SCC can be achieved for minimal trade-offs in AZP performance. Moreover, we demonstrate that a hierarchical design strategy is capable of yielding good quality solutions to both objectives. This hierarchical design considers pressure control valves first placed for the primary AZP objective, followed by automatic flushing valves placed to augment SCC conditions. In addition, we investigate an adaptive control scheme for dynamically transitioning between AZP and SCC controls. We demonstrate these control challenges on case networks with both interconnected and branched topology.
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