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  • Writer's picturePeter Franklin

Automated Energy Forecasting

Automated Energy Forecasting enables finely tuned models to be built in seconds for pennies unlocking £/€/$ millions for the energy sector

Automated Energy Forecasting

If you work in the energy sector then you will no doubt be creating or using energy forecasts – be these of supply, demand, or price.

In the new world of Big Data we have access to a plethora of time series on influencers of outcome. Through a combination of data science and mathematics we now have the wherewithal to access the patterns in the data which can reveal the algorithms to predict the future.

Imagine – taking the next step where the machine can build, tune, and run forecasting models. And not do it in the weeks and months that it takes human teams – but do it in seconds.

That means that forecasting models can be built where they could not be practically or economically before. Models can be built at a much finer granularity. If it only takes seconds , and costs pennies – you can model down to every asset provided the data is available.

It also means the skilled data scientists can be deployed looking at what decisions should be made on the basis of the forecast – rather than producing the forecasts themselves. That is where the value of their input really lies.

For the energy industry this is now a reality.

Take a look at our short (under 8 minutes) video on the implications for the energy sector of the technology developed by Tangent Works, called TIM – Tangent Information Modeller.

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