Optimizing of hybrid renewable photovoltaic/wind turbine/super capacitor for improving self-sustainability
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The study evaluate the utilization of an ultra supercapacitor as an energy storage unit effectively increase energy self-consumption in applications using microgrid renewable energy systems. Two scenarios were evaluated in this study: (scenario A) a photovoltaic and energy storage system; and (scenario B) a photovoltaic, energy storage, and wind turbine system. The systems analysis was conducted using experimental data for weather and load with a temporal precision of 1 min. The daily average of the electrical load profile was 5.0 kWh/day, with a maximum peak of 4.5 kW, and the annual energy consumption utilized to calculate the electrical load profile was 1859 kWh/year. The research indicates that charging the ultra supercapacitor only with renewable energy sources can greatly enhance self-consumption of energy. Using only six ultra supercapacitors (300 F–2.7 V/unit), the annual percentage of self-consumption increased from 37.01 to 46.65% and the percentage of self-sufficiency increased from 27.54 to 41.69% for scenario (A), and from 38.52 to 48.75% and the percentage of energy self-sufficiency increased from 33.50 to 49.87% for scenario (B). The research shows that by including tiny, rapid-response energy storage, the yearly averaged energy self-consumption for the investigated load rises in comparison to the system without energy storage, making it an attractive candidate for batteries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it