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Demand Forecasting and Gas Flow Data NW GRI Transparency Workshop

Demand Forecasting and Gas Flow Data NW GRI Transparency Workshop. Chris Logue – March 2009. Contents. Demand Forecasting National Grid Approach Methodology Accuracy Market Significance Real Time Gas Flow Data National Grid Approach Market Significance. Scotland. Glasgow. Newcastle.

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Demand Forecasting and Gas Flow Data NW GRI Transparency Workshop

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  1. 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. Scotland Glasgow Newcastle Northern NorthEast Leeds North West Manchester East Midlands Nottingham Wales North Birmingham West Midlands Eastern London Wales South London Cardiff South East Bristol Southern Benson South West Southampton Weather stations11 weather stations feed data to the 13 LDZs

  4. D-1 D-1 D-1 D-1 D-1 D-1 D-1 D-1 D-1 D D D D D Sumest (Complex regression) Wintest (Complex regression) Bayes (Complex regression) STF (Complex regression) Inday (Simple regression) Box 2 (Box Jenkins) Box 1 (Box Jenkins) Profile (ARIMA) Neural network ALN (Adaptive logic network) Average weighted according to performance over last 7 days (Combination). Further adjustment made based on recent combination error (CAM) How? - suite of models using different techniques

  5. Forecasting NTS Direct Connected Loads • Input Data • Shippers • OPNs/SFNs for NTS direct connected loads, first received at D-1 12:00. • Met Office • For D & D-1, forecast temperatures and wind speed • For D-2 to D-7, forecast max and min temperatures • Forecast is produced for each individual site • Models Used • Pass through OPNs where available • Profile model, forecast end of day volume which is then profiled to hourly offtake • regression model, forecast individual hourly offtake • Models are trained every week

  6. NTS Demand Forecast Performance 7.00% 6.00% 5.00% 4.00% 3.00% 2.00% 1.00% 0.00% D-4 D-3 D-2 D-6 D-5 D-7 D 16:00hrs D 00:00hrs D 10:00hrs D 13:00hrs D 21:00hrs D-1 00:00hrs D-1 13:00hrs D-1 16:00hrs Demand Forecast Performance

  7. 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 may • Be used by shippers to supplement / verify their own forecasts • Sometimes be followed by price movements • Indicate requirement for a demand response

  8. 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

  9. 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

  10. Data can also be displayed graphically

  11. 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

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