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Quantifying resilience in energy systems with out-of-sample testing

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  • Pickering, Bryn
  • Choudhary, Ruchi

Abstract

The need to design resilient energy systems becomes ever more apparent as we face the challenge of decarbonising through reliance on non-dispatchable technologies and sectoral integration. Increasingly, modelling efforts focus on improving system resilience, but fail to quantify the improvements. In this paper, we propose a novel workflow that allows increases in resilience to be measured quantitatively. It incorporates out-of-sample testing following optimisation, and compares the impacts of demand and power interruption uncertainty on both risk-unaware and risk-aware district energy system models. To ensure we encompass the full range of impacts caused by uncertainty, we consider nine distinct objectives encompassing differences in: investment and operation costs, CO2 emissions, and aversion to risk.

Suggested Citation

  • Pickering, Bryn & Choudhary, Ruchi, 2021. "Quantifying resilience in energy systems with out-of-sample testing," Applied Energy, Elsevier, vol. 285(C).
    • Handle: RePEc:eee:appene:v:285:y:2021:i:c:s0306261921000313
    DOI: 10.1016/j.apenergy.2021.116465
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    2. Lombardi, Francesco & Pickering, Bryn & Pfenninger, Stefan, 2023. "What is redundant and what is not? Computational trade-offs in modelling to generate alternatives for energy infrastructure deployment," Applied Energy, Elsevier, vol. 339(C).

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