Optimized solar datasets: Increasing value through the solar pv lifecycle


The use cases for solar data are evolving. Where once developers, independent engineers, universities, and financing institutions used data largely for project prospecting, research, and financing, data today is  being used by professionals in operations and maintenance, EPC, asset management, market trading, and “green” investment funding.

And datasets are used for performance benchmarking, long term resource and energy assessment, ground-tuning analysis, variability assessment, and energy trading.

Those were highlights of a recent pv magazine-hosted webinar featuring Mark Grammatico of Clean Power Research and Armando Solis of Lightsource bp.  The two highlighted the types of data that are available to solar developers, compared the pros and cons of free data versus commercial data, and demonstrated how solar data can be deployed across the project lifecycle. 

Solar data has transitioned from a simple, imprecise tool that often lacked validation to one that is complex, comprehensive and forward-looking. The solar industry’s own evolution is leading solar dataset providers to offer a full suite of meteorological variables to estimate long-term performance, optimize real-time performance, and provide forecasting for future performance. 

Grammatico offered five factors to be considered when selecting a solar dataset. First, is the solar data validated and widely accepted? Second, are the data’s rates of uncertainty known and acceptable? Does the solar data have an extensive historical record to back current data? Are the measurements spatially precise? And, was the data built specifically for solar applications? 

He suggested that users conduct due diligence in selecting data sources and said while many valid free solar data resources available, commercially available datasets can offer a higher level of precision and insight. 

One advantage of commercial datasets like those backed by Clean Power Research and Lightsource bp is the power of real-time data. These reports rely on input data that is comprised of both ground-based instrumentation and satellite data, and a correlation study between the two sources.  

This real-time information enables asset owners to consistently analyze and identify which projects are under-performing over the long term. It allows for the creation of performance thresholds that leverage digital technology to alert users when intervention is needed. Real-time data can also provide clear and comparable metrics across all projects that allow operations and maintenance users to make informed decisions. 

The presenters offered white papers and case studies demonstrating data in action. The archived webinar is available here.

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