Pumping Station Design in Water Distribution Networks Considering the Optimal Flow Distribution between Sources and Capital and Operating Costs
The investment and operating costs of pumping stations in drinking water distribution networks are some of the highest public costs in urban sectors. Generally, these systems are designed based on extreme scenarios. However, in periods of normal operation, extra energy is produced, thereby generatin...
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| Vydáno v: | Water (Basel) Ročník 13; číslo 21; s. 3098 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Basel
MDPI AG
03.11.2021
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| ISSN: | 2073-4441, 2073-4441 |
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| Abstract | The investment and operating costs of pumping stations in drinking water distribution networks are some of the highest public costs in urban sectors. Generally, these systems are designed based on extreme scenarios. However, in periods of normal operation, extra energy is produced, thereby generating excess costs. To avoid this problem, this work presents a new methodology for the design of pumping stations. The proposed technique is based on the use of a setpoint curve to optimize the operating and investment costs of a station simultaneously. According to this purpose, a novel mathematical optimization model is developed. The solution output by the model includes the selection of the pumps, the dimensions of pipelines, and the optimal flow distribution among all water sources for a given network. To demonstrate the advantages of using this technique, a case study network is presented. A pseudo-genetic algorithm (PGA) is implemented to resolve the optimization model. Finally, the obtained results show that it is possible to determine the full design and operating conditions required to achieve the lowest cost in a multiple pump station network. |
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| AbstractList | The investment and operating costs of pumping stations in drinking water distribution networks are some of the highest public costs in urban sectors. Generally, these systems are designed based on extreme scenarios. However, in periods of normal operation, extra energy is produced, thereby generating excess costs. To avoid this problem, this work presents a new methodology for the design of pumping stations. The proposed technique is based on the use of a setpoint curve to optimize the operating and investment costs of a station simultaneously. According to this purpose, a novel mathematical optimization model is developed. The solution output by the model includes the selection of the pumps, the dimensions of pipelines, and the optimal flow distribution among all water sources for a given network. To demonstrate the advantages of using this technique, a case study network is presented. A pseudo-genetic algorithm (PGA) is implemented to resolve the optimization model. Finally, the obtained results show that it is possible to determine the full design and operating conditions required to achieve the lowest cost in a multiple pump station network. |
| Author | Mora-Meliá, Daniel Iglesias-Rey, Pedro L. Martínez-Solano, F. Javier Gutiérrez-Bahamondes, Jimmy H. Salgueiro, Yamisleydi |
| Author_xml | – sequence: 1 givenname: Jimmy H. orcidid: 0000-0002-7651-8709 surname: Gutiérrez-Bahamondes fullname: Gutiérrez-Bahamondes, Jimmy H. – sequence: 2 givenname: Daniel orcidid: 0000-0002-6191-7299 surname: Mora-Meliá fullname: Mora-Meliá, Daniel – sequence: 3 givenname: Pedro L. orcidid: 0000-0001-8300-3255 surname: Iglesias-Rey fullname: Iglesias-Rey, Pedro L. – sequence: 4 givenname: F. Javier orcidid: 0000-0002-8140-5960 surname: Martínez-Solano fullname: Martínez-Solano, F. Javier – sequence: 5 givenname: Yamisleydi orcidid: 0000-0002-1946-0053 surname: Salgueiro fullname: Salgueiro, Yamisleydi |
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| SubjectTerms | algorithms capital Case studies Cost control Design optimization energy Energy consumption Genetic algorithms Operating costs pumps Variables water water distribution |
| Title | Pumping Station Design in Water Distribution Networks Considering the Optimal Flow Distribution between Sources and Capital and Operating Costs |
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