Purdue researchers created an algorithm using the physics of panel degradation that can analyze solar farm data from anywhere, essentially as a portable EKG for solar farms.
Real-time diagnostics would ultimately inform better panel designs – the cost-saving “treatment” that could prolong lifespan and continue to cut electrical bills.
Degradation in humid environments, for example, comes in the form of corrosion, but high altitudes with no humidity cause degradation through the increased concentration of UV light. Like with human diseases, symptoms of corrosion or sun-beaten silicon tend to not show up on a solar panel until many years after the degradation started.
Without knowing when degradation is happening, companies tend to compensate for different weather conditions by under- or over-designing solar panels, driving up manufacturing costs.
Purdue researchers used public solar panel data to pull together parameters of how well the panels are generating electricity, such as resistance and voltage. When fed into the algorithm, a curve generates to show the power output of a solar cell.
In the long term, the researchers hope the algorithm could show how much energy a solar farm produces in 30 years by looking at the relationship between weather forecast data and projection of electric circuit parameters. Integrating the algorithm with other physics-based models could eventually predict the lifetime of a solar farm.
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News Source: https://www.purdue.edu/newsroom/releases/2018/Q3/physics-model-acts-as-an-ekg-for-solar-panel-health.html
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