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A novel optimization method for urban resilient and fair power distribution preventing critical network states

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  • Ottenburger, Sadeeb Simon
  • Çakmak, Hüseyin Kemal
  • Jakob, Wilfried
  • Blattmann, Andreas
  • Trybushnyi, Dmytro
  • Raskob, Wolfgang
  • Kühnapfel, Uwe
  • Hagenmeyer, Veit

Abstract

In decentralized and smart power systems with a high share of distributed renewable energy sources the reliability of power supply is particularly challenged. Therefore, known concepts on maintaining the security of supply have to be rethought and enhanced by the notion of resilience. Power shortages caused by dark doldrums or induced by component failures or by cyber-attacks on the one hand and new extreme power demands due to an increased usage of power consuming technologies on the other hand can lead to critical network states or even blackouts. The impact of failures of critical infrastructures on the urban security of supply in general is measureable by so-called supply indices. These supply indices in combination with efficiency and fairness metrics allow the definition of a composite resilience metric, which we utilize in our novel smart scheduling method. Assuming the existence of advanced metering infrastructures and smart meters, the presented method enables stable and urban resilient grid operation in the face of power scarcity or extreme power demands. Thereby, the new method goes far beyond demand side management, peak shaving techniques or rolling blackouts. Consequently, the proposed composite resilience metric enables the development of new power distribution policies and controls, which consider urban resilience with respect to critical services, power efficiency, and fairness. Based on an Evolutionary Algorithm and Optimal Power Flow, the new smart and urban resilient scheduling method is applied to an extension of the IEEE 33 case: simulation results are presented and it is shown that the new method outperforms known benchmark methods such as rolling blackouts.

Suggested Citation

  • Ottenburger, Sadeeb Simon & Çakmak, Hüseyin Kemal & Jakob, Wilfried & Blattmann, Andreas & Trybushnyi, Dmytro & Raskob, Wolfgang & Kühnapfel, Uwe & Hagenmeyer, Veit, 2020. "A novel optimization method for urban resilient and fair power distribution preventing critical network states," International Journal of Critical Infrastructure Protection, Elsevier, vol. 29(C).
    • Handle: RePEc:eee:ijocip:v:29:y:2020:i:c:s1874548220300184
    DOI: 10.1016/j.ijcip.2020.100354
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    References listed on IDEAS

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    1. Henry, Devanandham & Emmanuel Ramirez-Marquez, Jose, 2012. "Generic metrics and quantitative approaches for system resilience as a function of time," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 114-122.
    2. Stephen Frank & Steffen Rebennack, 2016. "An introduction to optimal power flow: Theory, formulation, and examples," IISE Transactions, Taylor & Francis Journals, vol. 48(12), pages 1172-1197, December.
    3. Enrico Zio & Giovanni Sansavini, 2011. "Component Criticality in Failure Cascade Processes of Network Systems," Risk Analysis, John Wiley & Sons, vol. 31(8), pages 1196-1210, August.
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    Cited by:

    1. Lonergan, Katherine Emma & Suter, Nicolas & Sansavini, Giovanni, 2023. "Energy systems modelling for just transitions," Energy Policy, Elsevier, vol. 183(C).
    2. Adel Mottahedi & Farhang Sereshki & Mohammad Ataei & Ali Nouri Qarahasanlou & Abbas Barabadi, 2021. "The Resilience of Critical Infrastructure Systems: A Systematic Literature Review," Energies, MDPI, vol. 14(6), pages 1-32, March.
    3. Reinhold Lehneis & Daniela Thrän, 2023. "Temporally and Spatially Resolved Simulation of the Wind Power Generation in Germany," Energies, MDPI, vol. 16(7), pages 1-16, April.

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