The current approach is based on a knowledge database approach in which scenarios are first checked against a database of historical experience and previous calculations to seek a match with a previously encountered scenario. If so, experience or previous calculations will be a good indicator of whether capacity constraints could cause problems. If no such previous example is found, an assessment is conducted using full set of network calculations (SIMONE) driven by manual interventions of an expert analyst. The results of such assessments are then added to the database.

While the current forecasting approach requires a manageable computational overhead, as the number of inputs to the model increase this overhead may become unrealistic. To maximise the efficiency of the forecast process and to take cognisance of the latest statistical and forecasting management techniques a more holistic innovative solution needs to be considered. This programme aims to deliver some of these objectives by imbedding current best practice within the current processes offering improved NTS capacity management.

This programme will provide a unified set of automated NTS capacity forecasting tools, utilising the latest statistical methods and algorithms enhancing National Grid’s capacity management of the NTS with attendant benefits for all users.