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Demand Profile Dates

NESO·data_release·medium·23 Apr 2024·84 words·source

Summary

NESO publishes historical and forecast profile dates used to convert Cardinal Point forecasts into half-hourly demand forecasts from 2018 to 14 days ahead. These profile dates match forecast dates based on weather, embedded generation, seasonal patterns, calendar activities and special events, with updates as weather forecasts improve closer to real time.

Why it matters

This data supports accurate electricity demand forecasting which is essential for system operation, balancing costs, and market pricing. The transparency helps market participants understand and potentially improve their own forecasting methodologies.

Key facts

  • Covers period from start of 2018
  • Forecasts up to 14 days ahead
  • Profile dates updated as weather forecasts improve
  • Considers weather, embedded generation, seasonal factors, calendar activities and special events

Areas affected

wholesale marketgeneratorssuppliersrenewablesflexibility

Related programmes

Market-wide Half-Hourly Settlement

Publisher description

This dataset contains the historical and forecast profile dates used to convert our Cardinal Point forecasts into half hourly demand forecasts between the start of 2018 up to 14 Days Ahead. The profile dates are NESO's estimate at the historic date which will most closely match the forecast date in terms of weather, embedded generation, time of year, recurring calendar activities and special events. These dates can change as we get closer to real time as our weather forecasts are updated and

Full extracted text
This dataset contains the historical and forecast profile dates used to convert our Cardinal Point forecasts into half hourly demand forecasts between the start of 2018 up to 14 Days Ahead. 

The profile dates are NESO's estimate at the historic date which will most closely match the forecast date in terms of weather, embedded generation, time of year, recurring calendar activities and special events. These dates can change as we get closer to real time as our weather forecasts are updated and certainty improves.