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Scenario Optimisation of Pumping Schedules in a Complex Water Supply System Considering a Cost–Risk Balancing Approach

Author

Listed:
  • Jacopo Napolitano

    (University of Cagliari)

  • Giovanni M. Sechi

    (University of Cagliari)

  • Paola Zuddas

    (University of Cagliari)

Abstract

The optimisation of water pumping plant activation schedules is a significant issue when managing emergency and costly water transfer under a drought risk. This problem needs specific optimisation tools to deal with complex multi-reservoir supply systems and to consider different alternative scenarios. The effectiveness of emergency transfers alleviating droughts requires early warning and activation; on the other hand, the high operating costs of pump stations require system managers to take a robust approach that defines activation rules. The proposed optimisation procedure combines scenario optimisation analysis with a cost-risk balancing approach. The model searches for the identification of optimal decision rules by balancing the risk of water shortages and the operating costs of pumping stations. Scenario optimisation provides ‘barycentric’ values that define the activation threshold by comparing hydrological synthetic series results. A multi-objective approach is also required in order to balance energy cost minimisation requirements and a reduction of damage needs that can be caused by water shortages. Consequently, a scenario optimisation has been developed considering the multi-objective and cost-risk balancing problem. A model application has been developed optimising water management and energy costs in a real water system with shortage risks in the South Sardinia (Italy) region.

Suggested Citation

  • Jacopo Napolitano & Giovanni M. Sechi & Paola Zuddas, 2016. "Scenario Optimisation of Pumping Schedules in a Complex Water Supply System Considering a Cost–Risk Balancing Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5231-5246, November.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:14:d:10.1007_s11269-016-1482-8
    DOI: 10.1007/s11269-016-1482-8
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    References listed on IDEAS

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    1. R. T. Rockafellar & Roger J.-B. Wets, 1991. "Scenarios and Policy Aggregation in Optimization Under Uncertainty," Mathematics of Operations Research, INFORMS, vol. 16(1), pages 119-147, February.
    2. Liu Yuan & Jianzhong Zhou & Chunlong Li & Mengfei Xie & Li Mo, 2016. "Benefit and Risk Balance Optimization for Stochastic Hydropower Scheduling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3347-3361, August.
    3. Giovanni Sechi & Paola Zuddas, 2008. "Multiperiod Hypergraph Models for Water Systems Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(3), pages 307-320, March.
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    Cited by:

    1. Tiku T. Tanyimboh, 2017. "Informational Entropy: a Failure Tolerance and Reliability Surrogate for Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 3189-3204, August.
    2. Giovanni M. Sechi & Alexei A. Gaivoronski & Jacopo Napolitano, 2019. "Optimising Pumping Activation in Multi-Reservoir Water Supply Systems under Uncertainty with Stochastic Quasi-Gradient Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(5), pages 1881-1895, March.

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