IDEAS home Printed from https://ideas.repec.org/a/gam/jresou/v7y2018i4p73-d182502.html
   My bibliography  Save this article

Optimal Pump Scheduling for Urban Drainage under Variable Flow Conditions

Author

Listed:
  • Oreste Fecarotta

    (Department of Civil, Architectural and Environmental Engineering, University of Naples “Federico II”, 80125 Naples, Italy
    These authors contributed equally to this work.)

  • Armando Carravetta

    (Department of Civil, Architectural and Environmental Engineering, University of Naples “Federico II”, 80125 Naples, Italy
    These authors contributed equally to this work.)

  • Maria Cristina Morani

    (Department of Civil, Architectural and Environmental Engineering, University of Naples “Federico II”, 80125 Naples, Italy
    These authors contributed equally to this work.)

  • Roberta Padulano

    (Regional Models and Geo-Hydrological Impacts (REMHI), CMCC Foundation (Euro Mediterranean Center on Climate Change), Via Maiorise, 81043 Capua, Italy
    These authors contributed equally to this work.)

Abstract

The paper is focused on the optimal scheduling of a drainage pumping station, complying with variations in the pump rotational speed and a recurrent pattern for the inflow discharge. The paper is structured in several consecutive steps. In the first step, the experimental set-up is described and results of calibration tests on different pumping machines are presented to obtain equations linking significant variables (discharge, head, power, efficiency). Then, those equations are utilized to build a mixed-integer optimization model able to find the scheduling solution that minimizes required pumping energy. The model is solved with respect to a case study referred to a urban drainage system in Naples (Italy) and optimization results are analysed to provide insights on the algorithm computational performance and on the influence of pumping machine characteristics on the overall efficiency savings. With reference to the simulated scenarios, an average value of 32% energy can be saved with an optimized control. Its actual value depends on the hydraulic characteristics of the system.

Suggested Citation

  • Oreste Fecarotta & Armando Carravetta & Maria Cristina Morani & Roberta Padulano, 2018. "Optimal Pump Scheduling for Urban Drainage under Variable Flow Conditions," Resources, MDPI, vol. 7(4), pages 1-20, November.
    • Handle: RePEc:gam:jresou:v:7:y:2018:i:4:p:73-:d:182502
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2079-9276/7/4/73/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2079-9276/7/4/73/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Armando Carravetta & Oreste Fecarotta & Umberto Maria Golia & Michele Rocca & Riccardo Martino & Roberta Padulano & Tullio Tucciarelli, 2016. "Optimization of Osmotic Desalination Plants for Water Supply Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(11), pages 3965-3978, September.
    2. Carravetta, A. & Fecarotta, O. & Ramos, H.M., 2018. "A new low-cost installation scheme of PATs for pico-hydropower to recover energy in residential areas," Renewable Energy, Elsevier, vol. 125(C), pages 1003-1014.
    3. Roberta Padulano & Giuseppe Giudice, 2018. "A Mixed Strategy Based on Self-Organizing Map for Water Demand Pattern Profiling of Large-Size Smart Water Grid Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(11), pages 3671-3685, September.
    4. Oreste Fecarotta & Aonghus McNabola, 2017. "Optimal Location of Pump as Turbines (PATs) in Water Distribution Networks to Recover Energy and Reduce Leakage," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(15), pages 5043-5059, December.
    5. Zhang, Zijun & Kusiak, Andrew & Zeng, Yaohui & Wei, Xiupeng, 2016. "Modeling and optimization of a wastewater pumping system with data-mining methods," Applied Energy, Elsevier, vol. 164(C), pages 303-311.
    6. Ioannis Kougias & Nicolaos Theodossiou, 2013. "Multiobjective Pump Scheduling Optimization Using Harmony Search Algorithm (HSA) and Polyphonic HSA," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(5), pages 1249-1261, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Ming & Tan, Lei & Cao, Shuliang, 2019. "Theoretical model of energy performance prediction and BEP determination for centrifugal pump as turbine," Energy, Elsevier, vol. 172(C), pages 712-732.
    2. Carravetta, A. & Fecarotta, O. & Ramos, H.M., 2018. "A new low-cost installation scheme of PATs for pico-hydropower to recover energy in residential areas," Renewable Energy, Elsevier, vol. 125(C), pages 1003-1014.
    3. Thomas Pirard & Vasileios Kitsikoudis & Sebastien Erpicum & Michel Pirotton & Pierre Archambeau & Benjamin Dewals, 2022. "Discharge Redistribution as a Key Process for Heuristic Optimization of Energy Production with Pumps as Turbines in a Water Distribution Network," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1237-1250, March.
    4. Isabel Kaufmann Almeida & Aleska Kaufmann Almeida & Jorge Luiz Steffen & Teodorico Alves Sobrinho, 2016. "Model for Estimating the Time of Concentration in Watersheds," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4083-4096, September.
    5. Johnson, Hilary A. & Simon, Kevin P. & Slocum, Alexander H., 2021. "Data analytics and pump control in a wastewater treatment plant," Applied Energy, Elsevier, vol. 299(C).
    6. Alemtsehay G. Seyoum & Tiku T. Tanyimboh, 2016. "Investigation into the Pressure-Driven Extension of the EPANET Hydraulic Simulation Model for Water Distribution Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5351-5367, November.
    7. Filipe, Jorge & Bessa, Ricardo J. & Reis, Marisa & Alves, Rita & Póvoa, Pedro, 2019. "Data-driven predictive energy optimization in a wastewater pumping station," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    8. Tao Bai & Lianzhou Wu & Jian-xia Chang & Qiang Huang, 2015. "Multi-Objective Optimal Operation Model of Cascade Reservoirs and Its Application on Water and Sediment Regulation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2751-2770, June.
    9. Seon Woo Kim & Soon Ho Kwon & Donghwi Jung, 2022. "Development of a Multiobjective Automatic Parameter-Calibration Framework for Urban Drainage Systems," Sustainability, MDPI, vol. 14(14), pages 1-16, July.
    10. Chih-Chiang Wei & Nien-Sheng Hsu & Chien-Lin Huang, 2014. "Two-Stage Pumping Control Model for Flood Mitigation in Inundated Urban Drainage Basins," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(2), pages 425-444, January.
    11. Panagiotis Karadimos & Leonidas Anthopoulos, 2023. "Machine Learning-Based Energy Consumption Estimation of Wastewater Treatment Plants in Greece," Energies, MDPI, vol. 16(21), pages 1-20, November.
    12. Zong Woo Geem & Jin-Hong Kim, 2016. "Sustainable Optimization for Wastewater Treatment System Using PSF-HS," Sustainability, MDPI, vol. 8(4), pages 1-13, March.
    13. Ioan Sarbu & Matei Mirza & Daniel Muntean, 2022. "Integration of Renewable Energy Sources into Low-Temperature District Heating Systems: A Review," Energies, MDPI, vol. 15(18), pages 1-28, September.
    14. Xiaoli Feng & Baoyun Qiu & Yongxing Wang, 2020. "Optimizing Parallel Pumping Station Operations in an Open-Channel Water Transfer System Using an Efficient Hybrid Algorithm," Energies, MDPI, vol. 13(18), pages 1-19, September.
    15. Alejandro Tapia Córdoba & Daniel Gutiérrez Reina & Pablo Millán Gata, 2019. "An Evolutionary Computational Approach for Designing Micro Hydro Power Plants," Energies, MDPI, vol. 12(5), pages 1-25, March.
    16. Hamlehdar, Maryam & Yousefi, Hossein & Noorollahi, Younes & Mohammadi, Mohammad, 2022. "Energy recovery from water distribution networks using micro hydropower: A case study in Iran," Energy, Elsevier, vol. 252(C).
    17. Ávila, Carlos Andrés Macías & Sánchez-Romero, Francisco-Javier & López-Jiménez, P. Amparo & Pérez-Sánchez, Modesto, 2021. "Optimization tool to improve the management of the leakages and recovered energy in irrigation water systems," Agricultural Water Management, Elsevier, vol. 258(C).
    18. Torregrossa, Dario & Hansen, Joachim & Hernández-Sancho, Francesc & Cornelissen, Alex & Schutz, Georges & Leopold, Ulrich, 2017. "A data-driven methodology to support pump performance analysis and energy efficiency optimization in Waste Water Treatment Plants," Applied Energy, Elsevier, vol. 208(C), pages 1430-1440.
    19. Morabito, Alessandro & Vagnoni, Elena & Di Matteo, Mariano & Hendrick, Patrick, 2021. "Numerical investigation on the volute cutwater for pumps running in turbine mode," Renewable Energy, Elsevier, vol. 175(C), pages 807-824.
    20. Manoujan, Amin Zarei & Riasi, Alireza, 2024. "Optimal selection of parallel pumps running as turbines for energy harvesting in water transmission lines considering economic parameters," Applied Energy, Elsevier, vol. 359(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jresou:v:7:y:2018:i:4:p:73-:d:182502. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.