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Open AccessFeature PaperArticle

Minimizing the Effect of Substantial Perturbations in Military Water Systems for Increased Resilience and Efficiency

1
Department of Chemistry and Life Science, United States Military Academy, West Point, NY 10996, USA
2
Department of Mechanical Engineering, University of Texas at Austin, Austin, TX 78712, USA
3
Department of Chemical Engineering, University of Texas at Austin, Austin, TX 78712, USA
*
Author to whom correspondence should be addressed.
Processes 2017, 5(4), 60; https://doi.org/10.3390/pr5040060
Received: 30 August 2017 / Revised: 4 October 2017 / Accepted: 11 October 2017 / Published: 18 October 2017
A model predictive control (MPC) framework, exploiting both feedforward and feedback control loops, is employed to minimize large disturbances that occur in military water networks. Military installations’ need for resilient and efficient water supplies is often challenged by large disturbances like fires, terrorist activity, troop training rotations, and large scale leaks. This work applies the effectiveness of MPC to provide predictive capability and compensate for vast geographical differences and varying phenomena time scales using computational software and actual system dimensions and parameters. The results show that large disturbances are rapidly minimized while maintaining chlorine concentration within legal limits at the point of demand and overall water usage is minimized. The control framework also ensures pumping is minimized during peak electricity hours, so costs are kept lower than simple proportional control. Thecontrol structure implemented in this work is able to support resiliency and increased efficiency on military bases by minimizing tank holdup, effectively countering large disturbances, and efficiently managing pumping. View Full-Text
Keywords: energy; water; military; control energy; water; military; control
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James, C.M.; Webber, M.E.; Edgar, T.F. Minimizing the Effect of Substantial Perturbations in Military Water Systems for Increased Resilience and Efficiency. Processes 2017, 5, 60.

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