GSP Group Correction Factors data from the Trading Operations Report


The page below details highlighted GSP Group Correction Factors (GGCFs) data from the previous month. This data is acquired from BSC Agents and inputted to the Trading Operation Monitoring Analysis System (TOMAS) database.

The graphs may take a couple of seconds to load. To expand the graphs, tap the double-headed arrow in the bottom right corner of the graph.

Distribution of Half-Hour GGCFs across all GSP Groups

The chart bellow shows the distribution of GGCFs, as per the latest Settlement Run data, for each Settlement Period in the last complete season and the latest three complete years. Again it shows the effectiveness of profiling, with the ideal being a narrow distribution centred on 1.


The distribution of HH GSP GCFs, across all GSP Groups, for September 2023 remains similar to previous years with the percentage peak remaining close to 1; however, the September 2023 data is skewed more to the left when compared to the same month in previous years.  

Half-Hour Correction factors by Settlement Period volume 

The following is based on Initial Settlement (SF) Run for the latest month and is weighted across all GSP Groups.

The chart below shows, for each of the day types used in profiling, a volume weighted average, such as adjusted to reflect the relative sizes of each GSP Group (in terms of total daily energy consumption), of the GGCFs across all GSP Groups by Settlement Period.

The source data are GGCFs from the Initial Settlement (SF) Run taken over the latest month for which SF data is available. The average is taken, for each Settlement Period, over the one month interval to create plots of volume-weighted GGCFs for the periods from Monday to Friday, for Saturdays and for Sundays included in the data set. It allows comparison of profiling for different day types and shows intra-day profiling effects.

Anything between 0.9 and 1.1 is considered reasonable. Values outside this range may indicate issues with load profiling or metering data.


The weighted GGCFs breakdowns have shifted from last month for the “Monday to Friday” day types, with GCFs for several settlement periods in the middle of the day falling below the lower threshold. This will be investigated to see if an obvious error can be found in the data, with the aim of correcting this is the next settlement run. GCFs for the “Saturday” day type are all within tolerance, whereas for the “Sunday” day type GGCFs are seen above the upper threshold for two settlement periods.

Daily Average GSP Group Correction Factor by GSP Group

The chart below is based on the latest Settlement Run for the last two years.

This chart shows the daily average GGCF using the latest Settlement Run data for each GSP Group for the last two years. It shows both profiling and metering effects, as per the earlier explanation on the effects of profiling and metered volumes.


For the first half of 2023, the daily average GCFs tended to remain between the higher and lower tolerances – with the largest peaks and troughs usually occurring around bank holidays. 

Since June 2023, GCFs have been more volatile, with both the lower and upper thresholds breached on certain days. The low GCFs seen in GSP Group_P in September/October are likely caused by the known issue where metered data from a wind farm in this region is not received until later reconciliation runs, whilst the low GCFs seen more recently in GSP_K will be tracked but are expected to be corrected in the next settlement run.

The Spike seen on 9-10 September 2023 across several GSPs Groups was due to a profiling error that has now been corrected, and this should be reflected in next month’s graph. As mentioned previously, Elexon is in the process of creating tools to help track and identify causes of GCF spikes or troughs for specific settlement days, and once this is implemented the number of issues outstanding at SF should decrease.


Click on the X next to any of the icons to replace them with a short-cut link to the page you are currently on or search for a specific page.