Volume Correction in SIGO

Improve the quality and reliability of information used in the daily operation of Gas Dispatch by identifying anomalous values and reducing the need for manual analysis and correction.

Implement a pilot at the Gas Dispatch Centre, integrating an Artificial Intelligence model to automatically detect anomalous values while considering station types and their respective consumption profiles.

• Improved quality, consistency and reliability of information used;
• Increased operational efficiency through automated detection of anomalous values;
• Reduced manual intervention;
• Provision of correction proposals adapted to station characteristics and consumption profiles;
• Support for faster, better-informed decisions.