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Predictive control for the operation of cascade pumping stations in water supply canal systems considering energy consumption and costs

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  • Kong, Lingzhong
  • Li, Yueqiang
  • Tang, Hongwu
  • Yuan, Saiyu
  • Yang, Qian
  • Ji, Qingfeng
  • Li, Zhipeng
  • Chen, Ruibin

Abstract

Water supply canal systems (WSCSs) have a significant environmental and energetic impact due to the large amount of energy consumed in water pumping and water losses. The safe and efficient operation of these systems is crucial. This study presents a closed-loop predictive control method for the operation of pumping stations in WSCSs, considering operation safety and energy consumption. In the proposed method, a linear prediction model derived from the hydrodynamic model is used for state prediction; data assimilation is used to correct the prediction model based on the feedback water level information; on the basis of the prediction results, the optimization control model for energy or cost saving is rolling established and solved to obtain the optimal pump control strategy. The method was tested on a virtual simulation model of a WSCS with two pumping stations under uncertain disturbances and compared to an open-loop optimal control method. The results demonstrated that the proposed method's cost- and energy-driven optimization strategies could reduce the system's operating energy and cost by 5.1 % and 5.5 %, respectively while ensuring the safe operation of the system. Compared with the result of 1.4 % energy reduction and 0.2 % cost reduction under the open-loop optimal control, the proposed method can retain a better optimization effect under uncertain disturbance and has good robustness. Furthermore, the method can be modified according to the needs of the WSCSs for pump control.

Suggested Citation

  • Kong, Lingzhong & Li, Yueqiang & Tang, Hongwu & Yuan, Saiyu & Yang, Qian & Ji, Qingfeng & Li, Zhipeng & Chen, Ruibin, 2023. "Predictive control for the operation of cascade pumping stations in water supply canal systems considering energy consumption and costs," Applied Energy, Elsevier, vol. 341(C).
    • Handle: RePEc:eee:appene:v:341:y:2023:i:c:s0306261923004671
    DOI: 10.1016/j.apenergy.2023.121103
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    References listed on IDEAS

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    1. Rong Tang & Ke Li & Wei Ding & Yuntao Wang & Huicheng Zhou & Guangtao Fu, 2020. "Reference Point Based Multi-Objective Optimization of Reservoir Operation: a Comparison of Three Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(3), pages 1005-1020, February.
    2. Yang, Zitong & Huang, Xianfeng & Fang, Guohua & Ye, Jian & Lu, ChengXuan, 2021. "Benefit evaluation of East Route Project of South to North Water Transfer based on trapezoid cloud model," Agricultural Water Management, Elsevier, vol. 254(C).
    3. Bürger, Adrian & Bohlayer, Markus & Hoffmann, Sarah & Altmann-Dieses, Angelika & Braun, Marco & Diehl, Moritz, 2020. "A whole-year simulation study on nonlinear mixed-integer model predictive control for a thermal energy supply system with multi-use components," Applied Energy, Elsevier, vol. 258(C).
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    Cited by:

    1. Gang Wang & Junke Wang & Nurayn Tiamiyu & Zufen Wang & Li Song, 2023. "Loose Belt Fault Detection and Virtual Flow Meter Development Using Identified Data-driven Energy Model for Fan Systems," Sustainability, MDPI, vol. 15(16), pages 1-27, August.

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