Gross error detection in mass and energy balance safeguards data integrity by identifying anomalies and inconsistencies. This proactive approach improves the accuracy of energy network models, helping to keep operations safe, efficient, and economically viable.
Detecting such errors early is crucial to preventing misguided decisions and potential operational crises.
ENetOPT applies both global tests and measurement tests to pinpoint suspicious measurements. The standard deviation required for each measurement is derived automatically from historical data.