Forecaster Gas

Provide daily withdrawal estimates and monthly planning for points of delivery
Published by Accenture


  • Statistical methods
  • Advanced Analytics

Statistical methods

The application offers a full range of statistical methods, including highly, market-specific forecasting methods such as authority profiles and non-daily metered algorithms.

  • Produce an accurate forecast (short, medium and long term), to reduce physical unbalancing and related costs
  • Minimize the statistical know-how required to achieve accurate forecast
  • Import historical time series from TSO and 3rd party weather condition forecasting
  • Industrialize the process, allow business users to have strong control over it, reduce effort to focus on results and business decisions
  • Take into account Energy Market peculiarities (uses different version of TSO's allocation, NDM meters, direct customers, market detail under the DP, standard profiles, contract volumes, other TSO information can be used as drivers)
  • Advanced Analytics

  • Forecast individual time series: classical time series models, regressions, autoregression, neural networks, GAM models, free syntax models
  • Cluster points/meters in groups with similar behavior using hierarchical clustering algorithms
  • Access library of pre-configured models for the most common behaviors of gas demand
  • Select most effective model in library with back testing simulation logic
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