Abstract
Abstract Indicator-based approaches are suitable to assess multi-dimensional problems. In order to compare a set of alternatives, one strategy is to normalize individual indicators to a common scale and aggregate them into a comprehensive score. This study proposes the Electricity Supply Resilience Index (ESRI), which is a measure of a nation’s electricity supply resilience. Starting from an initial set of individual indicators derived through a structured selection process, the ESRI is calculated for 140 countries worldwide. To account for robustness of the resulting resilience index, 38 combinations of eight normalization methods and six aggregation functions were considered. Results show a clear country ranking trend, with robust top- and low-performing countries across all combinations. However, the ranking disparity becomes large for average performing countries, especially if their indicators show high variability. Furthermore, the differences of the rankings are quantified through the Rank Difference Measure (RDM), which identifies the categorical scales and the minimum aggregator as the most different ones. Finally, the effects of different compensation levels of the aggregation functions are discussed. The findings of the present study aim to provide recommendations for policymakers on how composite indexes results depend on assumptions and chosen approaches.
Highlights
Resilience is a multi-dimensional concept that is receiving growing attention in various disciplines, with many definitions and quantification methods proposed so far (Hosseini et al, 2016; Häring et al, 2017; Sharifi and Yamagata, 2016; Ouyang, 2014; Cimellaro, 2016; Francis and Bekera, 2014; Willis and Loa, 2015; Bergström et al, 2015)
This study proposes the Electricity Supply Resilience Index (ESRI), which is a measure of a nation’s electricity supply resilience
Starting from an initial set of individual indicators derived through a structured selection process, the ESRI is calculated for 140 countries worldwide
Summary
Resilience is a multi-dimensional concept that is receiving growing attention in various disciplines, with many definitions and quantification methods proposed so far (Hosseini et al, 2016; Häring et al, 2017; Sharifi and Yamagata, 2016; Ouyang, 2014; Cimellaro, 2016; Francis and Bekera, 2014; Willis and Loa, 2015; Bergström et al, 2015). Even though there is no overall consensus, it is still widely accepted that a comprehensive resilience framework comprises both disruptive and recovery elements (Cimellaro, 2016). The resilience framework considered is the one developed by the Future Resilient Systems (FRS) program at the Singapore-ETH Centre (SEC) (Heinimann and Hatfield, 2017). This framework is generally applicable to infrastructure systems and comprises four dimensions:. (1) Resist: represents the system’s ability to withstand disturbances within acceptable degradation levels. (3) Rebuild: describes the recovery process of system’s performance back to normal. As the International Energy Agency (IEA) defines energy security as “the uninterrupted availability
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