Reviewing Municipal Energy System Planning in a Bibliometric Analysis: Evolution of the Research Field between 1991 and 2019
Bibliographic record
Abstract
In the context of the energy transition, energy system planning is becoming increasingly relevant for decentralized systems. Motivated by the strong increase of publications on municipal energy system planning (MESP), these studies are subjected to a bibliometric analysis in this paper. The 1235 articles, which are based on the Web of Science database, are examined using the R-tool bibliometrix. The study shows that China is the most important contributor with 225 articles, followed by the USA (205) and Germany (120). Most cross-country collaborations were conducted between China and Canada, focusing mainly on uncertainties in MESP. Among the institutions, the North China Electric Power University is responsible for most articles (42). The core journals on MESP are Energy, Applied Energy, Energy Policy, Energies and Renewable Energy, which published 37% of the 1235 articles. Publications on MESP focus on renewable energies, optimization and hybrid energy systems. Furthermore, district heating seems to be a core topic in MESP and is addressed in three of the top five most cited articles. The demonstration of global research trends in MESP can support researchers in identifying the relevant issues regarding this expanding and transforming research area.
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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 | 0.014 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.131 | 0.299 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".