Optimal Design of a Distributed Energy System Using the Functional Interval Model That Allows Reduced Carbon Emissions in Guanzhong, a Rural Area of China
Bibliographic record
Abstract
Nowadays, rural power supply in China plays an important role in restricting the economic development and improvement of residential living standards. In this study, an interval full-infinite programming rural energy model (IFIP-REM) was developed for supporting distributed energy system (DES) optimal design under uncertainties in rural areas. By affecting the upper and lower bounds of the interval by complex and variable external conditions, IFIP-REM could simulate the influence of external systems. To validate the model, a real case study of DES optimal design in Guanzhong, a rural area of China, was tested and aimed to minimize system cost and constraints of resources, energy supply reliability, and carbon emission mitigation. The data revealed generation of reasonable optimization schemes to obtain interval solutions of IFIP-REM. Compared to centralized energy system (CES), DES reduced electricity purchasing of the municipal grid by 47.5% and extended carbon emission of both upper and lower bounds to [17.13, 44.51] % and [12.42, 36.02] %, respectively. Overall, the proposed model could help managers make decisions of DES optimal design by coordinating conflicts among economic cost, system efficiency, and carbon emission mitigation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".