An innovative optimization-simulation framework is applied to a case study of the Province of Quebec, Canada, to optimize the spatial distribution of green infrastructure (GI), the capacity and location of gray infrastructure, and the parameters specific to real-time control (RTC) operating rules of a sewer system for reducing combined sewer overflows (CSOs) frequency and volume. GI, gray infrastructure, and RTC are applied either individually or in integration through eight optimization scenarios which are simulated over a nine-year period of historical rainfall data. Among all scenarios, spatial optimization of GI with RTC leads to maximal CSO volume reduction (98%) and is the most cost-effective option analyzed (70$/m³ of seasonal average CSO reduction compared to 140$/m³ for the scenario involving gray infrastructure alone). However, it requires a high GI implementation level and the CSO frequency under this scenario is sensitive to varying GI design parameters. The findings suggest that the best alternative for CSO control is the integration of the optimization of green and gray infrastructures with RTC as it still provides high CSO volume reduction (95%) and remains a cost-effective solution (90$/m³ of CSO reduction), while providing robustness under cost and design uncertainties.

中文翻译：

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通过绿色和灰色基础设施设计优化实时控制，以经济有效地缓解合流下水道溢流

以加拿大魁北克省为例，采用创新的优化模拟框架，对绿色基础设施（GI）的空间分布、灰色基础设施的容量和位置以及实时控制的特定参数进行优化（ RTC) 下水道系统运行规则，用于减少合流下水道溢流 (CSO) 的频率和流量。GI、灰色基础设施和 RTC 通过八个优化场景单独或集成应用，这些场景在九年的历史降雨数据期间进行模拟。在所有场景中，使用 RTC 对 GI 进行空间优化可最大程度地减少 CSO 体积 (98%)，并且是所分析的最具成本效益的选项（季节性平均 CSO 减少70$/m ³与 140$/m ^{3 相比）}对于仅涉及灰色基础设施的场景）。但是，它需要较高的 GI 实现级别，并且这种情况下的 CSO 频率对变化的 GI 设计参数很敏感。研究结果表明，CSO 控制的最佳替代方案是将绿色和灰色基础设施的优化与 RTC 相结合，因为它仍然提供了很高的 CSO 体积减少 (95%) 并且仍然是一个具有成本效益的解决方案（90 美元/m ³ CSO减少），同时在成本和设计不确定性下提供稳健性。