Wastewater reuse and energy saving require a more decentralized urban wastewater system? Evidence from multi-objective optimal design at the city scale

重新使用 能源消耗 帕累托原理 环境经济学 环境工程 工程类 计算机科学 运营管理 废物管理 经济 电气工程
作者
Dazhen Zhang,Xin Dong,Siyu Zeng,Xu Wang,Daoxiao Gong,Mo Li
出处
期刊:Water Research [Elsevier BV]
卷期号:235: 119923-119923 被引量:16
标识
DOI:10.1016/j.watres.2023.119923
摘要

Decentralization is recognized as an emerging solution for a more sustainable urban wastewater system (UWS) for the future. However, the debate of centralization vs. decentralization at the system's planning stage remains unresolved, mainly due to the complexity of the system's spatial structure and the multiple design objectives, such as water reuse and energy conservation. This paper presents the Sustainable Urban Wastewater System Generator (SUWStor) as a tool to address this issue. Integrating a graph representation of the system structure and the ant colony algorithm, SUWStor can produce Pareto optimal solutions for system design under three objectives: minimizing the capital cost, minimizing the operational energy consumption, and maximizing the water reuse capacity. The model is used for system design in a 100-square-km new city, the Xiong'an New District in China. Compared to the solution based on human experience, the model can reduce the system's capital cost by 7% and the operational energy in the pipe network by 26%, while maintaining the water reuse capacity at 100%. With this model, the relation between the optimal system layout and the choice over different design objectives can be discussed for any given area. In our case study, the optimal capacity of WWTPs for the lowest-cost solution is 48,000 m3 per day, leading to a total number of WWTPs of 5. As the water reuse level increases to maximum, the optimal capacity reduces to 15,000 m3 per day, where the number of WWTPs is 16. The model is also able to perform significantly better than the locally optimized results, in which only the WWTP locations are fixed at their optimal values. This demonstrates the importance of a global optimization model in designing the integrated UWS.
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