通过整合离散差异和连续近似来实现城市排水系统实时控制,改进了动态编程算法
Yuhan Yang1, Lei Cheng1, Xinran Luo2
1State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072, China; Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072, China; Research Institute for Water Security (RIWS), Wuhan University, Wuhan 430072, China.
Water research
|December 16, 2025
概括
一个新的算法,离散差异动态编程与连续近似 (DDDP-SA),通过优化孔控制以防止洪水,增强城市排水系统 (UDSs). 这种方法提高了储存能力,并有效地减少了综合下水道溢出 (CSO).
科学领域:
- 环境工程 环境工程
- 水资源管理 水资源管理
- 计算流体动力学的流体动力学.
背景情况:
- 城市排水系统 (UDS) 需要加强储存和排放,以控制洪水和防止污染.
- 实时孔操作对于UDS性能至关重要,但目前的方法缺乏精度和高维度.
- 优化UDS存储-排水能力需要提高孔控制精度和降低优化维度.
研究的目的:
- 开发一种新的优化算法,以提高UDS存储-排水能力.
- 为了提高孔控制精度,并减少优化维度在UDS.
- 证明新算法在减少综合下水道溢出 (CSO) 和提高UDS弹性方面的有效性.
主要方法:
- 将离散微分动态编程 (DDDP) 与连续近似 (SA) 结合起来,创建DDDP-SA算法.
- 使用连续近似来减少问题维度和DDDP以寻找最佳解决方案.
- 将DDDP-SA与被动的,基于规则的控制 (RBC) 和DPSA-TL策略进行比较,使用来自中国岳阳的数据.
主要成果:
- 与降雨事件中被动策略相比,DDDP-SA将综合下水道溢出 (CSO) 量减少了1.84%,至11.03%.
- 随着降雨强度的增加,CSO缓解效率下降,但在实时控制 (RTC) 场景中仍然优越.
- 与DPSA-TL相比,DDDP-SA提高了UDS控制精度和适应性,增加了孔使用时间和打开标准偏差4%至8%.
结论:
- DDDP-SA算法提供了一种高效的实时优化方法和在UDS中的细粒度孔操作.
- 这种方法在战略上利用管道网络的存储容量,大大提高了UDS的弹性.
- 该研究强调了先进算法的重要性,以改善城市洪水控制和污染预防在UDS.
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