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Energy forecasting with multiple models: what changes with FAST NOVA

In energy forecasting, each scenario may call for a different approach. FAST NOVA, the new version of MAS's metering and forecasting software, makes it possible to integrate several forecasting models and combine the results of different simulations.

FAST NOVA: more models, more possibilities. Compare multiple forecasting models and combine simulation results

FAST NOVA lets you integrate multiple forecasting models, compare their results and combine them, for more customised energy forecast management. More models, more possibilities.

Why a single forecasting model is not enough

In energy forecasting, each scenario may call for a different approach: a portfolio of residential customers behaves differently from an industrial one, and the same customer changes profile from season to season. Having more data is not enough: you need to be able to manage it simply, flexibly and independently.

What FAST NOVA introduces

  • Multiple forecasting models to be used in parallel, built-in or user-configured.
  • Comparison of results across different simulations, to choose the best approach for each segment.
  • Forecast combination, for more customised forecast management.
  • Portfolio segmentation more immediate, with greater autonomy for users.

What a more accurate consumption forecast is for

A reliable forecast reduces volume risk in fixed-price offers, improves withdrawal schedules and contains imbalance costs. FAST acquires SII metering data at the highest granularity, forecasts withdrawals down to the individual point and today monitors more than 300,000 withdrawal points.

Forecasts from FAST feed the price of offers in QUE MAS and the market schedules in ERGO Suite.

Frequently asked questions

What is FAST NOVA?

FAST NOVA is the new version of FAST, the MAS software for energy metering and forecasting: it makes managing forecasting models, simulations and portfolio segmentation more straightforward.

Why use several forecasting models?

Because different scenarios, such as customers, zones or times of year, can be better predicted by different models: comparing and combining them improves forecast reliability.

What data does FAST start from?

From SII metering data at maximum granularity, down to the single withdrawal point, combined with weather and historical data.

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