Weather Predictions & Green Energy

The impact of weather data on green energy production

Weather is particularly significant to the operations of both onshore and offshore wind farms. Weather determines the output from the turbines. As you may expect, the more wind on a given day, the more energy output produced. Understanding the weather helps increase revenue for a wind power producer.

In 2021, Google and its DeepMind AI subsidiary combined weather with power data from 700 megawatts of wind energy that Google sources in the Central United States. They’ve used AI to predict wind, which has ultimately paid off in the weather market. Because you must schedule your assets a day ahead in most markets, Google used AI to take publicly available weather data, forecast what they thought the weather would be like the next day, and bid that wind into the day-ahead markets. The result? Over a 20 percent increase in revenue for wind farms.

AI takes a new approach to weather forecasting with neural networks that generate exceptionally fast global forecasts based on past weather data. An AI model is trained on past weather data and using this in predictions. This data is different from standard numerical weather prediction models as those create mathematical representations of physical laws. Knowing what the future weather will be is critical to human activities. Solar and wind power plants require accurate weather data to optimize energy. One strength is that AI based models can be used in various granularity, for example as long as observational data can be found, it can be trained on past monthly weather to predict monthly weather averages ahead. We believe that it is a strength to be able to offer access to different models and multiple weather data sets.

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