1

Application of EP2 in derivation of SNCWV

2323rdrd September 2009 September 2009

2

Application of EP2 data in derivation of SNCWV

DESC meeting to discuss and agree approach for using EP2 data in the derivation of SNCWV from 1st October 2010

DESC were advised 24th July that additional meeting would be necessary during September to discuss practicalities of how to use EP2 data

xoserve issued DESC members with the Transporters proposed approach for applying EP2 data

xoserve welcomed feedback in advance of DESC meeting in order to address any issues or concerns today

Two shippers have provided feedback – points raised to be covered later in the presentation

3

Summary of material issued 28Summary of material issued 28thth August : August :

‘Applying EP2 data to SNCWV’‘Applying EP2 data to SNCWV’

4

Seasonal Normal Review process

Two key decisions have to be made as part of 5 yearly Seasonal Normal Review:

Is the Composite Weather Variable (CWV) methodology fit for purpose and if so agree the appropriate number of years required to derive the CWV parameters

AGREED - March 2009: Industry accepted CWV formula was robust and number of years used should be 13 (1996/97 to 2008/09)

Produce a Seasonal Normal Composite Weather Variable (SNCWV) which is a reasonable representation of “normal” weather for an LDZ

AGREED - June 2009: Industry accepted SNCWV will be derived using EP2 data, pending implementation of UNC Mod 254

5

Seasonal NormalComposite Weather Variable (SNCWV)

The SNCWV should be a reasonable representation of “normal” weather for an LDZ for each gas day within the currently defined seasonal normal period

The current set of SNCWVs were agreed in 2005 and are based on 17 years of historical data (1987/88 to 2003/04) and cannot be used after 30th September 2010, as per UNC.

The revised SNCWVs are required for the next defined seasonal normal period, namely from 1st October 2010 until 30th September 2015

Output from EP2 project was selected by industry to be used in the calculation of the SNCWV from Oct 2010 to Sep 2015

The SNCWV is..... a daily number which represents normal weather for each future gas day calculated before gas day based on an industry agreed weather data basis a value for a day in a gas year BUT is the same for each of the 5 years (including on

leap years when they occur) i.e. value for 1st Oct 2010 is the same as 1st Oct 2011.

6

Principles for applying EP2 data to derivation of SNCWV

Key points xoserve needed to consider in applying EP2 data:

Output data from EP2 should be used in derivation of new SNCWV, however…

The SNCWV to be calculated in a manner which means it is fit for its primary purpose - modelling gas demand i.e. modelling parameters are not degraded

Maintain EP2 temperature ‘profile’ i.e. key features such as ‘buchan spells’

7

Applying EP2 output data to SNCWV calculation

Weighting for Effective Temp (l1) defined from relationship between LDZ NDM demand and CWV from 1996/97 to 2008/09EP2 data not required

EP2 Forecast Temp represents Actual Temp when calculating Effective Temp

Effective Temperature:Half of Yesterdays Effective Temp + Half of Today's Actual Temp

Pseudo Seasonal Normal Effective Temperature defined from relationship between LDZ NDM demand and CWV from 1996/97 to 2008/09 EP2 data not required

Weighting for pseudo Seasonal Normal Effective Temperature (1 – l1) defined from relationship between LDZ NDM demand and CWV from 1996/97 to 2008/09 EP2 data not required

EP2 Average Wind Speed and EP2 Forecast Temp used in Wind Chill Term

Wind Chill Formula:Average Wind Speed * Max (0,(14-Actual Temp)

Weighting for Wind Chill value (l2) defined from relationship between LDZ NDM demand and CWV from 1996/97 to 2008/09 EP2 data not required

Composite Weather = I1 * E(t) + (1-I1) * S(t) – I2 *WC(t)

Shaded boxes indicate where EP2 data output is ‘plugged’ into CWV formula Note, the various parameters (e.g. cold weather upturn) will also be applied before

finally calculating a SNCWV value for the gas day

8

EP2 Work Package 8 output:

EP2 data output was provided for each weather station in the form of:

Temperature:

(A) - Hourly smoothed average temperatures for the base period of 1971 to 2006 (36 years)

(B) - Hourly climate change temperature increments for the forecast period of 2008 to 2018 relative to the base period averages

(C) - Hourly smoothed average temperatures for the forecast period of 2008 to 2018 (expressed as the sum of items 1 and 2 above) **

Wind Speeds:

(D) - Hourly smoothed average wind speeds for the base period of 1971 to 2006 (36 years) **

There were no forecast increments for wind speeds.

Note: ** relates to data required for CWV formula

9

Features of EP2 Work Package 8 output

The forecast temperature increments are appropriate to the weather stations in current use BUT were not calculated from the base period average data

The smoothed base period average (1971 to 2006) is a means of representing the predicted climatologies

Base period average for temperature and wind speed was based on data from a variety of weather stations

EP2 forecast temperatures for the gas years in question (2010 to 2014) have been calculated by applying EP2 temperature increments appropriate for each year to the EP2 base period average

The key temperature data output from EP2 is the predicted temperature increments

10

Analysis of SNCWVs using EP2 data only and alternative method

An EP2 CWV has been calculated for the middle year (2012/13) of the five years over which the seasonal normal basis will apply using EP2 forecast temperatures and EP2 wind speed averages (referred to as avg. data stream)

A CWV has been calculated for 2012/13 using an alternative approach relating individual days’ temperatures and wind speeds when computing wind chill (referred to as “daily data”)

An EP2 temperature only profile has also been calculated for 2012/13 (referred to as EP2 temperature)

A comparison can be made of the ensuing changes to the daily average degree days value over the full gas year.

In all cases, the appropriate threshold used for degree days is that for aggregate NDM demand.

The table on the next slide shows the changes to average daily degree days (over the gas year) relative to the current 17 year SNCWV for the various CWV cases and relative to a 17 year SNT for the temperature case.

11

Analysis of SNCWVs using EP2 data only and alternative method

0.320.360.38SW

0.300.390.33SO

0.230.400.27SE

0.250.420.33NT

0.230.390.30EA

0.330.400.46WS

0.380.480.45WN

0.310.600.69WM

0.370.590.70EM

0.380.600.70NE

0.380.480.45NW

0.350.630.68NO

0.380.520.51SC

daily dataavg. data stream

EP2 CWVEP2 Temperature

Reduction in Daily Average Degree Days for 2012/13 Gas Year (ºCWV or ºC)

LDZ

0.320.360.38SW

0.300.390.33SO

0.230.400.27SE

0.250.420.33NT

0.230.390.30EA

0.330.400.46WS

0.380.480.45WN

0.310.600.69WM

0.370.590.70EM

0.380.600.70NE

0.380.480.45NW

0.350.630.68NO

0.380.520.51SC

daily dataavg. data stream

EP2 CWVEP2 Temperature

Reduction in Daily Average Degree Days for 2012/13 Gas Year (ºCWV or ºC)

LDZ

12

Results using EP2 data only and proposed approach in deriving SNCVW

EP2 temperature only “warming” is lower or very similar to the EP2 CWV using average data streams. 12 of 13 LDZs within ±0.1º

Result is surprising - wind chill should have a greater effect.

Indicates that the effect of wind chill not correctly captured when the EP2 average data streams are used to derive CWV.

Also, EP2 temperature only “warming” is actually lower than EP2 CWV with average data streams in 7 (of 13) LDZs.

CWV basis (containing a wind chill term) should be less “warm” than a temperature only basis. In 7 LDZs CWVs basis is more “warm”.

Additional effect of the lag term (effective temperature) with CWV based on average data streams - may be giving a “warmer” CWV than warranted.

EP2 CWV computed from sequential actual daily data gives (as expected) lesser “warming” than EP2 temperature only. (Compare columns 2 and 4).

Suggests that direct use of the EP2 average data streams leads to inappropriate CWV values. Leads to risk of less good gas demand models.

13

Analysis of SNCWVs using EP2 data only and alternative method – WM by month

Month Degree Days for Daily Data Based CWV

Degree Days Difference of Avg. Data Based CWV

(warmer: i.e. lower DDs)

% Difference

Oct 279.4 8.1 2.90%Nov 395.4 2.5 0.60%Dec 485.1 1.6 0.30%Jan 511 4.9 1.00%Feb 447.4 4.7 1.10%Mar 417.8 9.2 2.20%Apr 318.9 12.7 4.00%May 223.5 19.3 8.60%Jun 160.3 14.8 9.30%Jul 140.4 9.2 6.60%Aug 140.8 8.5 6.00%Sep 168.4 11.7 6.90%Full Year 3688.5 107.3 2.90%

WP LDZ EP2 CVW Profiles based on AVG DATA -v- DAILY DATA

14

CWV calculated using gas industry history only – Average and Daily approach (1971 to 2006)

WM LDZ - Calendar Year

0

2

4

6

8

10

12

14

16

18

01-Jan 01-Feb 01-Mar 01-Apr 01-May 01-Jun 01-Jul 01-Aug 01-Sep 01-Oct 01-Nov 01-Dec

CW

V

daily CWV from avg T. and avg W.

inflexions at 14.7º which is the V1

parameter of the WM CWV definition

15

Impacts of using EP2 data only in deriving SNCVW

The impacts of using EP2 temperature increments added to averaged EP2 base period history is that the CWV will not be appropriately computed i.e. the wind chill effect will be smaller thus producing warmer CWVs than necessary.

The wind chill effect is incorrectly computed (warmer than it should be) all through the year (winter and summer) but to a proportionately greater extent in the summer.

The result is that seasonal normal based ALP profiles for EUCs will be much lower that they should be in the summer and correspondingly peakier in the winter

It is important that any ‘warming’ of the SNCWV is due to the EP2 temperature increments and not the method of calculation.

16

Proposed Approach Summary

Apply EP2-WP8 temperature increments to individual years of gas industry data (36 years) to get 36 different incremented daily temperature streams for each target forecast year (e.g. 2012/13)

Windspeed data will be actual windspeeds for each of the gas industry base period days (no increments specified by EP2-WP8 for wind speed).

Compute 36 different CWVs for each future day and average to a single value.

Smooth computed CWV profile to remove excessive day-to-day variation in CWV profile BUT ensure same area under SNCWV curve and retention of similar bumps and kinks shown in the corresponding EP2-WP8 temperature profile.

17

Shipper feedback on proposed approachShipper feedback on proposed approach

18

Shipper Feedback: E.On and EDF Energy

E.On Feedback

Would like to check with Met Office that base period averages (1971 to 2006) were not used in derivation of temperature increments

Using gas industry history data removes ‘transparency’ of process Clarification sought on calculations shown on slide 34 Numbers used in examples misleading – slides 31, 37 and 38 Happy that smoothing is necessary if proposed approach is to be used

EDF Energy Feedback

Happy with “95%” of proposed approach Believe using same temperature increment across all 36 years is inappropriate Acknowledged requirement for smoothing, however asked if a moving average

approach had been considered

19

Transporters’ response to E.On Comments

Transporters’ response:

xoserve are happy that base period averages were not used to derive temperature increments. EP2-WP8 final report sections 3,4 and 5 confirm this

Further detail behind slide 34 has been provided to DESC which we hope assists in your understanding of the analysis

Monthly degree day analysis of differences between EP2 average and daily approach Example of two CWVs for WM (calculated using gas industry data only) were also

provided in order to show how ‘average’ approach results in a warmer CWV compared to ‘daily’ approach

Examples used in slides 31,37 and 38 were included in presentation primarily to show the differences between the two approaches, however in hindsight xoserve accept that the numbers used were misleading

20

Transporters’ response to EDF comments:Increments

Transporters’ response:

EP2 increments are values for each hour of the day added to hourly values of temperature

In order to derive increments for each day of 2012/13 for each of the sets of days of the 36 years (1971 to 2006) further information is required

Increments were derived first from modelling 10 UK climate districts and did not include the specific 1971-2006 average base period data

Increments were not derived from going from a baseline to a future date and so increment values appropriate from 1971 to 2012/13, from 1972 to 2012/13 etc do not exist

For each gas day (e.g. 1st April) we want to go from 36 individual gas industry history date data points to the future date (2012/13)

For simplicity and lack of additional information xoserve have proposed the increment is the same for going from each of the start points

Without additional global modelling work being done we have existing EP2 increments, gas industry daily history and EP2 averaged history as the only data available

Timescales dictate that we cannot manipulate any of the available data or indeed wait for further ‘fresh’ output from the Met Office

21

Transporters response to EDF comments:Smoothing Method

Transporters’ response:

Any smoothing method chosen should (i) retain EP2 Temperature profile and (ii) ensure the SNCWV does not incorporate any ‘warming’ or ‘cooling’ as a result of applying smoothing

xoserve considered moving averages, however this was considered not as statistically sound as the chosen method

Final smoothing method chosen – “lo-ess” method is a statistically robust method and the results from which are optimum for this purpose.

Final smoothed SNCWV profile compares well with the EP2 Temperature profile i.e. retains kinks and bumps

The smoothed and unsmoothed profiles envelope nearly identical areas (0.0002% difference) i.e smoothing has not changed the extent of annual warming

22

Demand Estimation Timetable incl. SN Review

23rd Sept ’09

DESC meeting to discuss application of EP2 approach

October ’09 to December ’09

Calculate revised CWV definitions Calculate revised SNCWVs DESC 22nd Dec ’09: Final SNCWV values presented• DESC November 10th 2009 – London

• Re-evaluation of NDM Sampling Sizes• Re-evaluation of EUC definitions & Demand Model Performance: SF & WCF• Re-evaluation of Model smoothing methodology• Review of demand attribution to EUC models newly with/without cut offs in 2008/09• Review of consultation process for annual proposals

January ’10 to Feb’10

Re-define all ALPs and DAFs on new basis (effectively re-running Spring analysis) Set of revised WAALPs available for system to start calculating AQs effective from 1 st October 2010 Jan DESC:

Re-evaluation: EUC definitions & Demand Model Performance: RV & NDM sample Strands• Approach for Spring 2010 Analysis

March ’10 onwards

WAALPs used in AQ Review