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Linking socio-economic aspects to power system disruption models

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  • Jasiūnas, Justinas
  • Lund, Peter D.
  • Mikkola, Jani
  • Koskela, Liinu

Abstract

Increasing reliance on uninterrupted electricity supply against emerging threats such as climate change and cyberattacks calls for higher resilience of societies against power disruptions. A better understanding of social and economic impacts during these disruptions would be important for planning of resilience improvements. However, traditional energy system models rarely include these aspects. This paper presents an integrated framework containing a geospatial power system operation model, capable of emulating system component failures and restoration according to environmental conditions, with a link to spatial social and economic values such as population, economic activity, critical services and facilities. The framework was applied for analyzing the effects of uncontrolled and controlled power outages for two windy winter weeks in Finland. This case illustrated how controlled optimization could reduce the societal costs of such outage by shifting power shortage to regions where such costs are lower and in part by shifting the costs to other factors.

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  • Jasiūnas, Justinas & Lund, Peter D. & Mikkola, Jani & Koskela, Liinu, 2021. "Linking socio-economic aspects to power system disruption models," Energy, Elsevier, vol. 222(C).
    • Handle: RePEc:eee:energy:v:222:y:2021:i:c:s0360544221001778
    DOI: 10.1016/j.energy.2021.119928
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    2. Ghodeswar, Archana & Bhandari, Mahabir & Hedman, Bruce, 2025. "Quantifying the economic costs of power outages owing to extreme events: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 207(C).
    3. Krumm, Alexandra & Süsser, Diana & Blechinger, Philipp, 2022. "Modelling social aspects of the energy transition: What is the current representation of social factors in energy models?," Energy, Elsevier, vol. 239(PA).
    4. Yang, Yongsheng & Liu, Huan & Mostafavi, Ali & Tatano, Hirokazu, 2025. "Review on modeling the societal impact of infrastructure disruptions due to disasters," Reliability Engineering and System Safety, Elsevier, vol. 257(PB).
    5. VandenHeuvel, Daniel & Wu, Jinran & Wang, You-Gan, 2023. "Robust regression for electricity demand forecasting against cyberattacks," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1573-1592.

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