In order to help consumers and developers have a firmer grip on the life of solar panels, the National Renewable Energy Laboratory (NREL) of the U.S. has rolled out "RdTools" testing software, capably of making precision evaluation of the degradation and endurance of solar panels quickly.

The NREL has developed the software, in collaboration with solar-panel manufacturer SunPower and data analysis firm kWh Analytics, which can detect related variables, including weather, climate change, sensor drift, and environmental pollution, and adjust the model according to the data, producing an analytical report on degradation of solar panels in a short time.

The research teams hopes that the software can help solar-panel manufacturers better understand their products. Dirk Jordan, PV researcher and engineer at the NREL, noted that after strenuous promotion, the software has been widely accepted by solar-panel manufacturers in testing the performance of their products.  

Results of RdTools analysis on degradation are shown in time sequence and year-on-year comparison. The results of RdTools analysis on a defective solar panel, as shown in the figure, show that the problems lies in defective sensor, rather than the quality of the solar panel, which causes sensor drift and results in high degradation. Photo courtesy of the NREL.

SunPower touts the performance of the software. Greg Kimball, an engineer with the company, points out that the company utilizes the software in evaluating the performance of 264 PV power stations around the world, finding that the degradation speed of its solar panels is much slower than expectation. Accordingly, the company has lengthened the warranty period for its products.

Adam Shinn, data scientist at kWh Analytics, noted that RdToolos can quantify endurance of solar panels, helping PV power investors manage financial risks.   

YoY analysis will produce data of various years, with the median figure being the most precise degradation rate and the distribution scope representing other variables. Photo courtesy of NREL.

(First photo courtesy of Open Grid Scheduler / Grid Engine Flickr CC0 1.0  , written by Daisy Chuang)