Prepayment Profile Analysis 15 October 2014 Presentation to DESC - - PowerPoint PPT Presentation

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Utilita Energy Limited Prepayment Profile Analysis 15 October 2014 Presentation to DESC Utilita Energy Limited Contents Profile analysis Impact analysis Section Page Section Page A Prepayment and band 1 profiles compared B Variance to

SLIDE 1

Utilita Energy Limited

Prepayment Profile Analysis 15 October 2014 Presentation to DESC

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Utilita Energy Limited

Section Page Section Page A Prepayment and band 1 profiles compared B Variance to actual consumption and causes

Annual Load Profile comparison 3 Variance to actual 5 Daily Adjustment Factor comparison 4 Conclusion 6

Profile analysis Impact analysis

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Section A | Utilita Energy Limited

Annual Load Profile comparison 15 October 2014

Commentary

Profiled consumption has been smoothed out over the week, with proportionately less consumption on weekends and more during the week and profiled consumption is proportionately higher in summer and lower in winter, both of which reflect know usage patterns of prepayment customers. The profile in the WN and NW LDZs has changed very little and remains very similar to the band 1 profile. 3

80% 90% 100% 110% 120% 130% 140% 150% 160% 01/10 12/10 23/10 03/11 14/11 25/11 06/12 17/12 28/12 08/01 19/01 30/01 10/02 21/02 04/03 15/03 26/03 06/04 17/04 28/04 09/05 20/05 31/05 11/06 22/06 03/07 14/07 25/07 05/08 16/08 27/08 07/09 18/09 29/09

ALP % ∆

SC NO NW NE EM WM WS WN EA NT SE SO SW

0.20
0.15
0.10
0.05

0.00 0.05 0.10 0.15 0.20 01/10 12/10 23/10 03/11 14/11 25/11 06/12 17/12 28/12 08/01 19/01 30/01 10/02 21/02 04/03 15/03 26/03 06/04 17/04 28/04 09/05 20/05 31/05 11/06 22/06 03/07 14/07 25/07 05/08 16/08 27/08 07/09 18/09 29/09

ALP absolute ∆

SC NO NW NE EM WM WS WN EA NT SE SO SW

0.0 0.5 1.0 1.5 2.0 2.5 01/10 12/10 23/10 03/11 14/11 25/11 06/12 17/12 28/12 08/01 19/01 30/01 10/02 21/02 04/03 15/03 26/03 06/04 17/04 28/04 09/05 20/05 31/05 11/06 22/06 03/07 14/07 25/07 05/08 16/08 27/08 07/09 18/09 29/09 ALP

Credit ALP

SC NO NW NE EM WM WS WN EA NT SE SO SW

PPM ALP

SC NO NW NE EM WM WS WN EA NT SE SO SW

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Section A | Utilita Energy Limited

Daily Adjustment Factor comparison 15 October 2014

Commentary

DAFs have been reduced over the whole year, especially the summer months, making the prepayment profile less sensitive to variances from the seasonal normal conditions. The DAFs indicate prepayment customers are much less sensitive to unseasonal weather in summer than in winter. The DAF in the WN and NW LDZs has changed very little and remains very similar to the band 1 profile. Combined with the similar ALPs, allocation in these LDZs will be more similar to band 1 allocation than in other LDZs. 4

40% 50% 60% 70% 80% 90% 100% 110% 01/10 12/10 23/10 03/11 14/11 25/11 06/12 17/12 28/12 08/01 19/01 30/01 10/02 21/02 04/03 15/03 26/03 06/04 17/04 28/04 09/05 20/05 31/05 11/06 22/06 03/07 14/07 25/07 05/08 16/08 27/08 07/09 18/09 29/09

DAF % ∆

SC NO NW NE EM WM WS WN EA NT SE SO SW

0.60
0.50
0.40
0.30
0.20
0.10

0.00 0.10 0.20 01/10 12/10 23/10 03/11 14/11 25/11 06/12 17/12 28/12 08/01 19/01 30/01 10/02 21/02 04/03 15/03 26/03 06/04 17/04 28/04 09/05 20/05 31/05 11/06 22/06 03/07 14/07 25/07 05/08 16/08 27/08 07/09 18/09 29/09

DAF absolute ∆

SC NO NW NE EM WM WS WN EA NT SE SO SW

0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 01/10 12/10 23/10 03/11 14/11 25/11 06/12 17/12 28/12 08/01 19/01 30/01 10/02 21/02 04/03 15/03 26/03 06/04 17/04 28/04 09/05 20/05 31/05 11/06 22/06 03/07 14/07 25/07 05/08 16/08 27/08 07/09 18/09 29/09 ALP

Credit DAF

SC NO NW NE EM WM WS WN EA NT SE SO SW

PPM DAF

SC NO NW NE EM WM WS WN EA NT SE SO SW

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Section B | Utilita Energy Limited

Variance to actual Std dev from mean var. MWh Band 1 PPM 1,435 773

Commentary

5 15 October 2014 Band 1 allocation is the actual wholesale allocation to Utilita. PPM allocation is the wholesale allocation using the new profiles and DAFs. Calculated consumption is the consumption by Utilita customers on each day based on meter readings. The standard deviation of the monthly prepayment profile variance suggests that the prepayment profile was more accurate than the band 1 profile in 2012/13 and less accurate than the band 1 profile in 2013/14. Differences in profile accuracy between two gas years can only be caused by weather conditions and the sensitivity to these weather conditions. GY 12/13 GY 13/14 1,831 2,316

15/03/13 25/03/13 04/04/13 14/04/13 24/04/13 04/05/13 14/05/13 24/05/13 03/06/13 13/06/13 23/06/13 03/07/13 13/07/13 23/07/13 02/08/13 12/08/13 22/08/13 01/09/13 11/09/13 21/09/13 01/10/13 11/10/13 21/10/13 31/10/13 10/11/13 20/11/13 30/11/13 10/12/13 20/12/13 30/12/13 09/01/14 19/01/14 29/01/14 08/02/14 18/02/14 28/02/14 10/03/14 20/03/14 30/03/14 09/04/14 19/04/14 29/04/14 09/05/14 19/05/14 29/05/14 08/06/14 18/06/14 28/06/14 08/07/14 18/07/14 28/07/14 07/08/14 17/08/14 27/08/14 MWh

Allocation vs. customer consumption

Band 1 allocation PPM allocation Calculated consumption

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Section B | Utilita Energy Limited

Conclusion 15 October 2014 6 Allocation variance to seasonal normal Allocation variance to actual consumption

Variance to seasonal normal against variance to actual allocation Interpretation

The graph ot the left shows the correlation between the weather corrected allocation and the variance to actual allocation. The correlation coefficient of 0.75 indicates that weather correction and allocation variance are strongly correlated. The cause of this inaccuracy relating to WCF is the daily adjustment factor, which is not negating the impact of the WCF in line with prepayment customer weather sensitivity in winter months. There remains, therefore, a significant risk of allocation being disproportionately increased during a cold winter. The standard deviation of the PPM allocation variance, at 2,316 MWh per month for the gas year 2013/14, is greater than the standard deviation of the credit allocation (1,831 MWh), suggesting it is less accurate than the credit allocation profile in this gas year (a standard deviation close to zero would indicate ALPs and DAFs are correct and any underlying variance would be the result of AQ inaccuracy). This appears to be as a result of summer allocation, which is far too high under the PPM allocation because of the reduced DAFs and warmer than seasonal normal temperatures in the summer months of 2014. The second graph shows the variability of allocation variance under both profiles during the last gas year. Greater accuracy would be indicated by a consistant variance each month. It should also be noted that the profiles and weather sensitivity has changed very little in the NW and WN LDZs. This analysis has not considered variation by LDZ, but it is not clear to Utilita why prepayment customer behaviour these two LDZs should be different to prepayment customers elsewhere and so similar to credit customers. Overall, this analysis suggests the weather sensitivity is too great in the summer and not sensitive enough in winter. This exposes prepayment suppliers to both upside and downside risk, depending on weather conditions and therefore the profile does not address the issues in allocation. Under the new profile, assuming entirely accurate industry AQs, a cold winter and a warm summer would allocate significantly more gas than consumed by customers, and a warm winter and cold summer would allocate significantly less gas than consumed by customers.

Oct-13 Nov-13 Dec-13 Jan-14 Feb-14 Mar-14 Apr-14 May-14 Jun-14 Jul-14 Aug-14

Allocation variance to actual customer consumption

MWh Var to band 1 MWh Var to PPM