Launch of Winter Dry Run for SMTA experimentation

16 December 2015

December 15th is the Launch of Winter Dry Run of the SMTA experimentation.

This experimentation aims at performing a check and update of short & medium term active power adequacy diagnosis, in line with agreed ENTSO-E methodologies, for shorter timeframes than seasonal outlooks.
This adequacy review compares local adequacy inputs and grid capacities to carry cross-border exchanges.

The dry run will be carried out on a weekly basis and the first run will assess Week 51 (From Saturday 12 December to Friday 18 December).

 

First steps of the SMTA experimentation project

The first steps preparing this dry run are the results of an intensive and fruitful collaboration between Coreso, TSCNET and ENTSO-E:

  • The initial concept of the project has been based on the expertise of ENTSO-E regarding the Seasonal Outlook studies.
  • Data definition and set up are handled in cooperation with ENTSO-E.
  • The representatives of Coreso and TSCNET TSOs participating to the sub-group specified the concept to be developed for this dry run.
  • This concept, currently limited to a simple deterministic and NTC approach, has been validated by the ENTSO-E SMTA PG on 20th of October.
  • Coreso developed the IT prototype for the dry run, in close collaboration with TSCNET.
  • All participating TSOs (19) sent their Remaining Capacity (RC) forecasts on a weekly basis since October 31st.
  • The Week ahead NTCs are extracted from the ENTSO-E Transparency platform.
  • Starting with a sample delivery of RC by TSOs for Week 43, the first tests of the process have been performed from Week 45 to 50.
  • Data quality and inconsistencies are a resulting focus point for the dry run.
  • A weekly report has been developed to present the results of the Adequacy assessment together with input data quality validation.

 

Current status

At present, 19 TSOs and 3 RSCIs are involved.

 

Next steps

The dry run will be processed until end of March and be concluded by a summary report in April 2016.
In the mean time, improvements of the methodology will be prepared as integrating a probabilistic approach and a ptdf computation.