Impact of Network Configuration on Hydraulic Constraints and Cost in the Optimization of Water Distribution Networks
This study introduces a novel approach for the multi-model analysis of complex water distribution networks (WDNs). The research focuses on designing and optimizing various WDN configurations while adhering to hydraulic constraints. Several key parameters and criteria are considered to achieve an eff...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/6/3126 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | This study introduces a novel approach for the multi-model analysis of complex water distribution networks (WDNs). The research focuses on designing and optimizing various WDN configurations while adhering to hydraulic constraints. Several key parameters and criteria are considered to achieve an efficient design. Additionally, different network layouts are evaluated, including looped and non-looped systems with varying numbers of reservoirs. Next, an analytical approach is developed to optimize the proposed WDNs, taking into account pipe type, length, and diameter, as well as nodal demands, elevations, pressure losses, and water velocities. Cost analysis reveals that a single-reservoir, non-looped WDN has the lowest cost (USD 26,892), while a two-reservoir, looped WDN has the highest (USD 30,861). The design inflows vary linearly, ranging from 0.0212 to 0.205 m<sup>3</sup>/s for a 0.3 m pipe diameter and from 0.0589 to 0.5694 m<sup>3</sup>/s for a 0.5 m pipe diameter. Further, a new approach based on the Coral Reef Algorithm (CRA) is developed and implemented to improve the technical and economic viability of the designed WDNs. The CRA effectively showcases its capacity to iteratively enhance network design by reducing overall costs significantly. Notably, higher demand multipliers yield even more efficient solutions, suggesting the algorithm’s adaptability to varying demand scenarios. |
|---|---|
| ISSN: | 2076-3417 |