Evaluating energy security in decentralized systems: Review and new index
Bibliographic record
Abstract
This article addresses the limitations of traditional energy security assessment frameworks, such as the World Energy Trilemma Index (WETI) and Energy Transition Index (ETI), in capturing complexities introduced by the decarbonization, decentralization, and digitalization (D3) of national energy systems. The article proposes a refined, D3-compatible index that emphasizes four core elements challenging and expanding conventional notions of energy security: supply-demand variability, distributed system management, supply chain risks, and broader system vulnerabilities. The study employs a systematic three-stage methodology: a targeted literature review, identification of overlooked measurement aspects, and development of refined indicators. The resulting framework utilizes a dashboard approach, introducing adaptive indicators within four categories: “Security of supply and demand,” “Adequacy and stability,” “Operational resilience,” and “Societal resilience.” The German energy transition serves as an illustrative case that demonstrates the practical utility of the new framework. While the index's forward-looking design is fundamentally conceptual, its adaptive structure allows immediate operationalization of selected D3-compatible indicators, as demonstrated in the case study; others lay the groundwork for future empirical applications. This approach significantly advances existing energy security assessment methods, providing policymakers and researchers with a flexible, detailed tool for strategic analysis and informed decision-making in transitioning energy systems. • Energy security indicators assess decarbonized, decentralized, digitized systems. • Review identifies measurement limitations in current energy security indices. • Dashboard framework enhances evaluation of energy security in D3 paradigm. • D3-indicators address variability, distributed control, supply chains, and systemic risks. • German case illustrates the framework's practical utility for energy transitions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.019 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".