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Optimizing Photovoltaic Generation with Machine Learning

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PUBLISHED: 09 March 2021

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The Challenge

Photovoltaic panels are oriented in an optimal position (angle to the sun) to maximize power generation. However, this position is vulnerable to violent wind gusts. 

  • To overcome this problem, the trackers switch to a defensive position when the wind is rough
  • The defense position is not optimal for generation, but ensures the integrity of the plates
  • The time in defense position should be minimized, while assuring that the risk of breakage is totally eliminated

PVH, a global company with leading technology in the photovoltaic generation sector, wanted to optimize this process.

To do so, they investigated whether their facilities could be equipped with advanced algorithms to improve the prediction of wind speed with certainty, optimizing generation times. The solution must be able to work autonomously and accurately predict future wind, a highly complex problem that requires the use of novel approaches such as machine learning.

Learn how PVH was able to optimize photovoltaic generation thanks to a Machine Learning algorithm, capable of anticipating wind gusts and allowing the rows of photovoltaic panels to move to the defense position with the appropriate anticipation.

About the customer

PVH is a leading and experienced provider of innovative trackers, structures and control solutions for utility-scale PV solar plants worldwide.

READ THE CASE STUDY