Maximizing Power Generation of a Solar PV System for a Potential Application at Musselwhite Gold Mine Site in Northwestern Ontario, Canada
Bibliographic record
Abstract
Increasing global concern for greenhouse gas emission, air pollution, fossil fuel prices, and electricity demand has generated a significant increase in research of promising renewable energy technologies for green electrical power generation. Solar photovoltaic (PV) systems are known for their capabilities to directly convert renewable solar energy into electrical energy for locations with abundant solar energy where there is a desperate need and demand for electrical power. This includes mining industries in remote locations. Solar PV systems generate more power if they are installed and operated efficiently. The inclination angle at which a PV panel is tilted from the horizontal plane is one of the most influential system parameters that affect the amount of electrical power output from the PV system and the system’s overall efficiency. Typically, the variation in the PV tilt angle determines the amount of incident solar radiation received on a PV panel to be utilized by a connected electrical load for use at a given site. In this paper, a mathematical model with numerical simulations are used to determine the total solar radiation incident on a tilted PV surface and to predict the optimum tilt angle for maximizing power generation from a solar PV system for potential application in Musselwhite Mine located in the remote northwestern region of Ontario, Canada. The total solar energy received on the optimally tilted PV surface is computed for all months in a year at the Musselwhite mine site. The results show that the monthly average optimum tilt angle of the PV system varied from a minimum value of 4o in the month of June to a maximum value of 74o in the months of January and December. It was also found that the highest maximum incident radiation of approximately 22.89 MJ/m2 for the whole year occurred in the month of April, whereas approximately 43.9% of this value (the lowest in the year) occurred in the month of December. The numerical simulation results suggest that PV systems are best be installed directly facing south at a fixed optimum tilt angle of 43o throughout the year at the Musselwhitemine site. This will improve the overall efficiency and save operating cost of the proposed PV system which in turn improves the commercial feasibility for the mining industry as an example of application.
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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 | 0.001 |
| 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".