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access icon free Distributed zone MPC of pressure management for water distribution network systems

  • Author(s): Dongming Liu 1, 2 ; Shaoyuan Li 1, 3 ; Yi Zheng 1, 3 ; Jing Wu 1, 3
    • View affiliations
  • Source: Volume 13, Issue 11, 23 July 2019, p. 1704 – 1717
    DOI:  10.1049/iet-cta.2018.6273 , Print ISSN 1751-8644, Online ISSN 1751-8652
© The Institution of Engineering and Technology
Received 03/11/2018, Accepted 25/04/2019, Revised 17/03/2019, Published 30/04/2019

In the pressure management of large scale water distribution network (WDN), a distributed zone model predictive control (MPC) is proposed to keep the terminal water head in thedesired pressure range for satisfying the customer's demand, avoiding frequently operating of the actuator and reducing the correlation between subsystems. To ensure the existence of feasible solutions of constrained distributed zone MPC, a new reference trajectory of the tank level is introduced as an optimised variable. With the consideration of the desired pressure range constraints on the new reference trajectory and some physical constraints on the corresponding physical variables, a distributed zone MPC is presented to minimise the weighted sum of the three terms in the proposed performance index. To achieve the convergence of distributed zone MPC optimisation problem, an augmented Lagrangian formulation is applied to the distributed coordinated strategy. The proposed distributed zone MPC is applied to the WDN in the Shinan district of Shanghai, and the effectiveness of the method is illustrated.

Inspec keywords: performance index; optimisation; water supply; predictive control

Other keywords: distributed zone MPC optimisation problem; desired pressure range constraints; thedesired pressure range; constrained distributed zone MPC; water distribution network systems; reference trajectory; distributed coordinated strategy; scale water distribution network; pressure management; terminal water head; distributed zone model predictive control

Subjects: Optimisation techniques; Natural resources and environmental control; Optimal control

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