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

Bryn Pickering and Ruchi Choudhary

Applied Energy, 2021, vol. 285, issue C, No S0306261921000313

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.

Keywords: District energy systems; Mixed integer linear optimisation; Out-of-sample testing; Resilient systems; Scenario optimisation; Two-stage stochastic programming (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (4)

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DOI: 10.1016/j.apenergy.2021.116465

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