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A Mathematical Approach to Improve Energy-Water Nexus Reliability Using a Novel Multi-stage Adjustable Fuzzy Robust Approach

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Progress in Intelligent Decision Science (IDS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1301))

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Abstract

A system of a systems approach that analyzes energy and water systems simultaneously is called energy-water nexus. Neglecting the interrelationship between energy and water drives vulnerabilities whereby limits on one resource can cause constraints on the other resource. Power plant energy production directly depends on water availability, and an outage of the power systems will affect the wastewater treatment facility processes. Therefore, it is essential to integrate energy and water planning models. As mathematical energy-water nexus problems are complex, involve many uncertain parameters, and are large-scale, we proposed a novel multi-stage adjustable Fuzzy robust approach that balances the solutions’ robustness against the budget-constraints. Scenario-based analysis indicates that the proposed approach generates flexible and robust decisions that avoid excessive costs compared to conservative methods.

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Authors and Affiliations

  1. University of Illinois at Chicago, Chicago, IL, 60607, USA

    Afshin Ghassemi & Michael J. Scott

Authors
  1. Afshin Ghassemi
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  2. Michael J. Scott
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Corresponding author

Correspondence to Afshin Ghassemi .

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Editors and Affiliations

  1. Faculty of Engineering and Natural Sciences, Bahcesehir University, Istanbul, Turkey

    Tofigh Allahviranloo

  2. Faculty of Engineering and Natural Sciences, Bahçeşehir University, Istanbul, Turkey

    Soheil Salahshour

  3. Faculty of Engineering and Natural Sciences, Bahcesehir University, Istanbul, Turkey

    Nafiz Arica

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Ghassemi, A., Scott, M.J. (2021). A Mathematical Approach to Improve Energy-Water Nexus Reliability Using a Novel Multi-stage Adjustable Fuzzy Robust Approach. In: Allahviranloo, T., Salahshour, S., Arica, N. (eds) Progress in Intelligent Decision Science. IDS 2020. Advances in Intelligent Systems and Computing, vol 1301. Springer, Cham. https://doi.org/10.1007/978-3-030-66501-2_9

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