A new model estimates solar cell output power more accurately in all weather conditions

Nov, 2021 - By SMI

A new model estimates solar cell output power more accurately in all weather conditions

The method relies on the well-known single-diode model, which provides sufficient precision without requiring excessive processing complexity. Depending on the amount of precision required, the proposed model can take into account three, four, or five different solar cell characteristics.

Solar cells have emerged as a rising star in the field of energy, with operational costs and performance comparable to those of a traditional power grid. In order for solar power projects to be financed and implemented, the decision-makers must first determine how much electricity the installed PV systems would provide. Solar cells are devices that gather solar radiation; the efficiency of their solar-to-electricity conversions is affected by a number of environmental elements such as cloud cover, temperature, and moisture.

Researchers from Shoolini University, India, in partnership with NIT, Hamirpur, India, designed a new model to forecast the production of solar cells which is more precise than current models and can assist policymakers in solar energy facilities. The researchers initially determined the values of the model parameters in a supervised testing method using a Class-A Sun Simulator in a test PV module to verify the correctness of their model under realistic circumstances. After determining the parameters and making forecasts, they investigated a solar PV module and subsequently a 1 kWp PV system erected on the terrace of NIT, Hamirpur's Centre for Energy and Environmental Engineering. The researchers then gathered data to assess their model's predictions.

The findings are promising, as the new model's predictions are much more precise than earlier ones. The researchers also noted the number of solar parameters to be included in the model in order to create the best forecasts with varying temperature and sun radiation intensity. These findings will be useful in potential solar energy research, as the model could be used to develop PV power forecasting software able to accurately predict daily, monthly, as well as yearly solar power generation, which is a key parameter for determining electricity demand and supply distribution and marketing PV systems.

According to the researchers, this work could eventually assist enhance the performance of solar cells and PV technology in huge solar power plants being built both globally and locally as part of India's National Solar Mission.

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