Optimal Design of Hybrid Renewable Energy System on Grid Based on Energy Consumption: A Case Study
Bibliographic record
Abstract
There is a serious need for reducing the carbon dioxide emissions due to the increase in the global warming.Besides, owing to the unavailability of clean energy sources throughout an entire the year, hybrid renewable energy systems (HRESs) are required.On other hand, the importance of optimal HRES design is to achieve a low cost with using a high green energy.Helioscope and HOMER Pro software were used to design a small grid-connected model and estimate the consumption energy for optimization.The analysis of the system showed how a grid-connected PV system with a battery backup affected on the total energy costs.In addition, the role of power supply irregularity from the national grid was highlighted by calculating the likelihood of a power outage and its impact on HRES.The results showed the internal rate of return (IRR) is 13%, and the return on investment (ROI) is around 9%.Also, the value of renewable fraction was around 63.4%.In conclusion, the proposed system was an efficient according to the energy consumption.This case study can extend to be applied in any country, especially the countries have longer summer like Iraq.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".