Demand Forecasting and Gas Flow DataNW GRI Transparency Workshop

Chris Logue – March 2009

2

Contents

Demand Forecasting National Grid Approach

Methodology

Accuracy

Market Significance

Real Time Gas Flow Data

National Grid Approach

Market Significance

3

4

Weather stations11 weather stations feed data to the 13 LDZs

Scotland

Northern

North EastNorthWest

WalesNorth

WalesSouth

WestMidlands

EastMidlands

Eastern

SouthWest

SouthernSouthEast

London

Glasgow

Newcastle

LeedsManchester

Nottingham

Birmingham

Cardiff

Bristol Benson

London

Southampton

5

How? - suite of models using different techniques

Profile (ARIMA)

STF (Complex regression)

Neural network

ALN (Adaptive logic network)

Inday (Simple regression)

Bayes (Complex regression)

Box 1 (Box Jenkins)

Box 2 (Box Jenkins)

Sumest (Complex regression)

Wintest (Complex regression)

D-1

D-1

D-1

D-1

D-1

D-1

D-1

D-1

D-1

Averageweighted according to

performance over last 7 days (Combination). Further adjustment made based on

recent combination error (CAM)

D

D

D

D

D

6

Forecasting NTS Direct Connected Loads

Input DataShippers

OPNs/SFNs for NTS direct connected loads, first received at D-1 12:00.

Met OfficeFor D & D-1, forecast temperatures and wind speedFor D-2 to D-7, forecast max and min temperatures

Forecast is produced for each individual siteModels Used

Pass through OPNs where availableProfile model, forecast end of day volume which is then profiled to

hourly offtake regression model, forecast individual hourly offtakeModels are trained every week

7

Demand Forecast Performance

NTS Demand Forecast Performance

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

7.00%

D-7

D-6

D-5

D-4

D-3

D-2

D-1

13:

00hr

s

D-1

16:

00hr

s

D-1

00:

00hr

s

D 1

0:00

hrs

D 1

3:00

hrs

D 1

6:00

hrs

D 2

1:00

hrs

D 0

0:00

hrs

8

Of Use to the Market?

Day ahead and within day forecasts have been provided to shippers for more than 10 years

D-1 forecast is subject of a performance incentive regime

Demand Forecast mayBe used by shippers to supplement / verify their

own forecastsSometimes be followed by price movementsIndicate requirement for a demand response

9

Conclusions

Demand Forecasting is inherently uncertain due to

uncertainties in weather and prices

Forecasting accuracy improves from 7 days ahead to within

day as more accurate information becomes available

National Grid demand forecast, although robust at present,

faces significant challenges, e.g. increase in wind generation

leading to greater uncertainty from CCGT demand

10

Real Time Flow Data

• National Grid began publishing flow data in 2006 following a lengthy consultation process

• Strong support from downstream players• Reservations from upstream players• Flow rate at every major entry point at 2 minute resolution •Updated every 12 minutes• Available as automated download

11

12

13

Data can also be displayed graphically

14

Of Use to the Market?

Gas flow data has;

• Biggest hit rate of any National Grid web page

• Been widely reported on and used by the press

• Become accepted and controversy now largely diminished