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Scenario-Based Hierarchical and Distributed MPC for Water Resources Management with Dynamical Uncertainty

Author

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  • P. Velarde

    (Universidad UTE
    University of Seville)

  • X. Tian

    (Delft University of Technology
    Nanjing University of Information Science & Technology)

  • A. D. Sadowska

    (Schlumberger Cambridge Research)

  • J. M. Maestre

    (University of Seville)

Abstract

A real-time control scheme informed by a streamflow forecast is presented for the optimal operation of water resources systems composed of multiple and spatially distributed systems, affected by hydroclimatic disturbances. The approach uses a two-layer scenario-based hierarchical and distributed model predictive controller (HD-MPC) to deal with the operational water management problem under dynamical uncertainty. The higher layer collects and coordinates forecast information, which is rendered into possible realizations of the uncertainties and sent to the local agents. The lower layer solves a distributed optimization problem related to the actual management objectives. The HD-MPC method is demonstrated through a simulation of the North Sea Canal system as a real-world case study. The results show the benefits of the proposed compared to over other types of MPC controllers.

Suggested Citation

  • P. Velarde & X. Tian & A. D. Sadowska & J. M. Maestre, 2019. "Scenario-Based Hierarchical and Distributed MPC for Water Resources Management with Dynamical Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(2), pages 677-696, January.
    • Handle: RePEc:spr:waterr:v:33:y:2019:i:2:d:10.1007_s11269-018-2130-2
    DOI: 10.1007/s11269-018-2130-2
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    References listed on IDEAS

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    1. Dilini Delgoda & Syed Saleem & Malka Halgamuge & Hector Malano, 2013. "Multiple Model Predictive Flood Control in Regulated River Systems with Uncertain Inflows," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(3), pages 765-790, February.
    2. Warren E. Walker & Marjolijn Haasnoot & Jan H. Kwakkel, 2013. "Adapt or Perish: A Review of Planning Approaches for Adaptation under Deep Uncertainty," Sustainability, MDPI, vol. 5(3), pages 1-25, March.
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    Cited by:

    1. Velarde, Pablo & Gallego, Antonio J. & Bordons, Carlos & Camacho, Eduardo F., 2023. "Scenario-based model predictive control for energy scheduling in a parabolic trough concentrating solar plant with thermal storage," Renewable Energy, Elsevier, vol. 206(C), pages 1228-1238.

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