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Optimizing drinking water distribution system operations

Author

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  • Vieira, Bruno S.
  • Mayerle, Sérgio F.
  • Campos, Lucila M.S.
  • Coelho, Leandro C.

Abstract

The operation of Water Distribution Systems (WDS) is often complex, especially when considering the changes in tariffs throughout the day. The cost of energy in these systems can reach 30% of total operating costs and its careful management can represent increased efficiency. The optimization of WDS scheduling operation appears as an effective method to reduce operating costs while ensuring a good service level to the population. In this paper we propose a new linear relaxation for a non-linear integer programming formulation for WDS in order to optimize its operation costs. This study makes five main contributions. First, our formulation includes new aspects related to the state of the system when the tanks are full, that were not considered before in mathematical programming models. Second, our linearization technique includes a variable number of breakpoints, resulting in significantly fewer binary variables for a given error level. Third, our relaxation reduces the search space of the solutions. Fourth, we have outperformed the best results for three benchmark instances from the literature. Lastly, we also provide a larger new real-life instance with specific conditions of energy tariffs, obtained from the WDS from the city of Florianópolis, southern Brazil, significantly outperforming the current solution employed by the utility provider.

Suggested Citation

  • Vieira, Bruno S. & Mayerle, Sérgio F. & Campos, Lucila M.S. & Coelho, Leandro C., 2020. "Optimizing drinking water distribution system operations," European Journal of Operational Research, Elsevier, vol. 280(3), pages 1035-1050.
    • Handle: RePEc:eee:ejores:v:280:y:2020:i:3:p:1035-1050
    DOI: 10.1016/j.ejor.2019.07.060
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    Citations

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    Cited by:

    1. de Oliveira, Glauber Cardoso & Bertone, Edoardo & Stewart, Rodney A., 2022. "Optimisation modelling tools and solving techniques for integrated precinct-scale energy–water system planning," Applied Energy, Elsevier, vol. 318(C).
    2. Wang, Guotao & Zhao, Wei & Qiu, Rui & Liao, Qi & Lin, Zhenjia & Wang, Chang & Zhang, Haoran, 2023. "Operational optimization of large-scale thermal constrained natural gas pipeline networks: A novel iterative decomposition approach," Energy, Elsevier, vol. 282(C).
    3. Russell Bent & Byron Tasseff & Carleton Coffrin, 2024. "I nfrastructure M odels : Composable Multi-infrastructure Optimization in Julia," INFORMS Journal on Computing, INFORMS, vol. 36(2), pages 600-615, March.
    4. de Oliveira, Glauber Cardoso & Bertone, Edoardo & Stewart, Rodney A., 2022. "Challenges, opportunities, and strategies for undertaking integrated precinct-scale energy–water system planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    5. Shao, Yu & Zhou, Xinhong & Yu, Tingchao & Zhang, Tuqiao & Chu, Shipeng, 2024. "Pump scheduling optimization in water distribution system based on mixed integer linear programming," European Journal of Operational Research, Elsevier, vol. 313(3), pages 1140-1151.

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