Reliable forecasts of consumption and generation are critical in the energy sector.
Read here how a transmission system operator used Visplore to detect model anomalies and forecast drifts 30 % earlier and improved model accuracy by 5 %, on average.
Visplore features a ready-to-use solution for diagnostics of all energy forecasts – from own models to forecast service providers.
Quickly grasp the error distribution including trends and outliers of forecast models over time.
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Use the “Prediction vs Reference” line plots to quickly inspect where forecast are off to a larger degree.
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With increasing decentralization and the expansion of renewable energy sources, the energy sector relies heavily on reliably accurate forecast models for consumption and generation. Thus, the focus of forecast monitoring and diagnostics is to swiftly detect temporary anomalies and gradual drifts across a multitude of models.
However, keeping track of an ever-expanding number of forecast models—often numbering in the thousands—in terms of quality and timeliness presents an increasing challenge. Models can quickly become outdated due to the rapid expansion of renewable energy, adding complexity to the task. It’s imperative to monitor these numerous models with minimal effort to promptly identify negative trends in forecast quality and pinpoint the underlying causes of degradation.
Visplore reduce these challenges to a minimum – and enables you to detect badly performing models and deteriorating trends much earlier.
To get started with forecast monitoring read our use case tutorial!
