Optimizing the Inclination Angle of a Solar PV System for Installation in Slave Lake, Alberta, for Maximizing PV Power Generation
Bibliographic record
Abstract
Increasing fossil fuel prices, electricity demand, and global concern for greenhouse gas emissions have generated an increase in research of novel renewable energy technologies for green power generation. Renewable solar-photovoltaic (PV) systems are known fosr their ability to directly convert the solar energy into electrical energy for locations where there is a desperate need and demand for electrical power, e.g. Communities and towns in remote locations, and solar energy is available. PV systems tend to generate more power if they are operated efficiently. The inclination (tilt) angle at which a solar photovoltaic (PV) module is sloped from the horizontal plane is one of the most influencing system parameters that affects the electrical power output from the PV system. This is due to the fact that the variation in the tilt angle affects the amount of incident solar radiation received on a PV system and utilized by the load once installed at a certain site. In this work, a mathematical model is used to estimate the total solar radiation incident on an inclined surface and to determine the optimum inclination angle for maximizing power generation from a solar PV system installed in Slave Lake, Alberta, Canada. The total solar energy received on the optimally inclined PV surface is computed for all months in a year. It was found that the monthly average optimum tilt angle of the PV system varied from a minimum value of 9o in the month of June to a maximum value of 78o in the months of January and December. The yearly average monthly optimum tilt angle for the fixed PV system in Slave Lake was estimated to be at 47o. It was also found that the highest maximum incident radiation of approximately 21.30 Mj/m2 for the whole year occurred in the month of June, where as approximately 30.4% of this value (the lowest in the year) occurred in the month of December. The minimum incident solar radiation for all months in the winter season occurred at almost zero tilt angle and that the variation of the monthly average daily sunlight hours varied from 6.9 hours in December to as high as 17.1 hours in June.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".