AI & ML Are Being Used Extensively In Renewable Energy Space

In Clean Facts, Clean News, Innovations, News, Renewable Energy, Technology

Due to the high rate of unpredictability associated with the renewable energy sector, artificial intelligence (AI) and machine learning (ML) is being used to make predictions about the demand by leveraging smart meters to foresee energy usage among users.

Further, by using machine learning on meteorological data, the outcomes can be used to predict the energy production in the future thus substantially reducing the cost.

Google’s DeepMind recently announced that it is working in this field. According to the company, by training its neural network with the widely available weather forecast, combined with turbine data, it has been able to improve the efficiency of wind energy by 20 per cent.

By doing so, the system could predict wind power output 36 hours ahead of the actual generation. further, they trained the system to make optimal hourly delivery commitments to the power grid a day in advance based on the predictions.

DNV GL – Energy is using autonomous drones with real-time artificial intelligence for carrying out effective and efficient inspections of wind turbines and solar panels. While robotics can play a vital role in remote inspection, and proving to be more beneficial in maintenance and troubleshooting.  

Recently in India, two researchers from the Thapar Institute of Engineering and Technology, designed a cost-effective and time-efficient AI to inspect solar panels.

The device uses machine learning and clustering-based computation for a speedy inspection process, thus bringing down the cost of energy production substantially by increased solar power forecasting models.

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