1. © British Gas Trading Limited 2011 NDM Data Sample Option C: Regression Analysis

2. © British Gas Trading Limited 2011 Data collation Raw data ranging from March 2005 to March 2011. Gas consumption at Small Supply Points (i.e., EUC 1,2,3 and 4), contained in “SMNDM_AQ_xxxx.txt” files, was aggregated by EUC, LDZ and by day. No data at LDZ WN for EUC 1. At LDZ NW, data ranging from 23 rd March 2009 to 20 th October 2009 missing. No data yet collated for Large Supply Points.

3. © British Gas Trading Limited 2011 Data Cleansing Due to overlapping time windows below, incoherent data were removed as collectively agreed on 2 nd May At LDZ NW, further data deleted due to sudden doubling in consumption (i.e., outliers). Dates range from 17 th March 2009 to 21 st October 2009. Total of 7 data points removed.

4. © British Gas Trading Limited 2011 Regression Analysis Regression Model as follows: Dummy variables (Bank Holidays, Easter, Christmas and so forth). Weather variables introduced as per DESC meeting on 4 th April (e.g. Temperature, Global Radiation, Rainfall and so forth). Time intervals used based on office hours and domestic habits. Slot 1 from 5am to 8am Slot 2 from 9am to 4pm Slot 3 from 5pm to 10pm Slot 4 from 11pm to 4am

5. © British Gas Trading Limited 2011 Regression Analysis Data normalised by AQ because of erratic level changes observed year on year. Yearly cut-off date is of 1 st April due to time span of original files and data deletion process Permutation of 14 Variables used to seek out best Regression fit.

6. © British Gas Trading Limited 2011 Conclusion MAPE of 10% overall across all LDZ’s. Over Winter months (October-April), overall MAPE is of 8%. Over Summer months (May-September), overall MAPE of 13.5%. Regression analysis suggests that, overall, these variables are significant: Mean_WindDirection Slot1_Windspeed Slot3_Windspeed Slot3_Global Radiation Slot4_Temp Bank Holidays School Holidays CWV mean_Temp mean_Rainfall

7. © British Gas Trading Limited 2011 Discussion of future work Removal of non-significant parameters and fine-tuning of regression analysis. For LDZ NW, weather parameters missing. Weather substitution algorithm to be implemented? Lagged weather effects may be introduced. Investigation of power on explanatory variables. Out-of-sample modelling upon receipt of 2011/2012 NDM Sample Data