Two Indian researchers at Thapar Institute of Engineering and Technology have developed a machine learning-based solution to predict performance ratios accurately and ascertain degradation rates of solar panels, reports India Today.

The team consisting of Parveen Bhola, a research scholar and Saurabh Bhardwaj, an associate professor at the Patiala-based deemed-to-be University, has spent the last few years researching methods to improve the economic efficiency of solar panels.

Currently, the process of physically inspecting the degradation of PV (photovoltaic) systems is time-consuming, costly, and cannot be used for the real-time analysis. However, the proposed model allows engineers to estimate the degradation regarding performance ratios in real time.

“As a result of real-time estimation, the preventative action can be taken instantly if the output is not per the expected value,” Mr Bhola said. “This information is helpful to fine-tune the solar power forecasting models. So, the output power can be forecasted with increased accuracy,” he added.

‘Renewed’ energy

According to the recently released ‘India RE 2019 Outlook’ repo, India is expected to add 15,860 megawatts (MW) of renewable energy capacity in the current year (2019), up by fifty per cent from last year and most of the uptake will come solar panels.

Also Read: Ladakh To Get World’s Largest Solar Power Plant; 5,000 MW Capacity Project To Be Completed By 2023

thapar institute

Get Swarajya in your inbox.