Energy visibility of a modeled photovoltaic/diesel generator set connected to the grid
Bibliographic record
Abstract
Abstract The paper presents a technical and economic analysis for two energy systems (conventional and renewable) with grid connection. The investigation was carried out using an experimental measurement for the desired load and weather data (solar irradiance and ambient temperature), were 5.1 kWh the daily energy consumption as measured and 4.6 kWh/m2/day the annual average of the solar irradiance. The simulation process was done by using MATLAB and HOMER software at a 1 min time step resolution. The economic optimization objective presented for two energy system scenarios (i) photovoltaic/grid and (ii) diesel/grid, takes into account the economic aspects and component prices based on the Iraqi market and regulations. The diesel generator, very popular in rural areas, is designed to work during the same period as the photovoltaic system (only during day hours). The yearly operating hours were recorded at 4380 h/year, and energy generation was approx. 2349 kWh/year while fuel consumption was 1826 L/year. The results showed that the photovoltaic system in scenario (i) can generate about 7895 kWh, and for the diesel generator in scenario (ii), it can generate approximately 2346 kWh. Furthermore, for scenario (i) the levelized net present cost is $1079 and the cost of energy is about $0.035/kWh, while for scenario (ii) the levelized net present cost is $12,287 and the cost of energy is $0.598/kWh. The use of solar energy is highly recommended compared to diesel generators due to the lowest cost and delivery of energy to the grid. Furthermore, it can capture carbon dioxide by about 5295 kg/year.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".