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How To Make Sense Of Solar Data

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According to the International Energy Agency (IEA), solar PV is one of the most rapidly growing technologies in the power generation scene and is poised to become the second-highest installed capacity by the year 2040, surpassing wind installations in the coming few years. For the European Union nations, solar energy will make more than 30% of renewables in total gross capacity additions by then.

Surfing such a wave of growth, it is incumbent on the solar industry to ensure that the operations and maintenance (O&M), as well as management of these assets, are well taken care of. Instrumental in achieving that goal is having a robust network of software and data analytics capabilities in place to enable optimum performance and ultimately revenue maximization.

It's easy to get lost in the vast volumes of operating solar data and not be able to extract insights that actually help improve the bottom-line. This is where advanced data analytics truly shines. However, advanced data analytics and algorithms without useful operating data won't just cut it. How will the application of artificial intelligence and machine learning truly materialize if they are only supplied with a glut of bad data points?

Data issues hinder certainty of operations forecasting and hence asset valuation. So the question remains: How can we better leverage all the available millions of data points? The answer to this question informs the content of the white paper “How to make sense of solar data?”, including a quick tip sheet, published by Solarplaza.

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