10 Lessons Learned From Transforming Renewable Energy With AI

Today, everything is becoming intelligent, instrumented, and interconnected. By 2025 there will be over 38 billion connected devices globally generating more than 180 trillion gigabytes of data. Nowhere is this trend more pervasive than renewable energy, especially when there are so many expectations for renewables to pave the way for a greener future. In the next decade, the US must produce 24% of its energy from renewables to meet the White House’s aggressive goal to create a net-zero emissions economy by no later than 2050.

Operators across wind, solar, and battery storage are quickly diversifying the kinds of assets in their fleets. Many operators now have all three, and while there are operational similarities between each of these asset types, optimizing the performance of a mixed fleet is challenging. In this webinar, you’ll hear the top 10 lessons learned on how AI has played a pivotal role in the day-to-day operations of 8.5 GW of wind, solar, and battery storage assets, and how your company can:

  • Improve operational efficiency with more accurate production forecasting
  • Enhance O&M practices with predictive analytics (specifically for multi-asset class fleets)
  • Boost profitability with a holistic approach to mixed asset integration
  • Learn how the Inflation Reduction Act will impact the deployment of renewables and why it is important to have AI to manage the assets.

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Author: Renewable Energy World

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