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Weather Forecasting for Load Forecasts DTN/Meteorlogix.

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Presentation on theme: "Weather Forecasting for Load Forecasts DTN/Meteorlogix."— Presentation transcript:

1 Weather Forecasting for Load Forecasts DTN/Meteorlogix

2 Outline Corporate Overview Forecast Improvement Goals The Meteorlogix Forecast System Statistical Weather Models Manual Input from Meteorologists Multiple data output Benefits Forecast Summary Forecast Preview for the 6-10 Day Period

3 DTN/Meteorlogix Corporate Overview Commercial weather leader DTN is a leading provider of proprietary business-to-business real-time information services enabling its customers to make “Smarter Decisions” Offices in Omaha, Minneapolis and Boston 110,000 subscribers across Agricultural, Energy and Weather Markets Provide weather information and services to ~700 utilities Stable organization with over 675 employees with strong technology skills and vertical market expertise. ~95 Degreed Meteorologists World’s largest commercial weather service provider, delivering weather information to the Energy industry since 1946 Industry leading technology State of the art weather forecasting system Proprietary load forecast information (Effective Degree Days) Comprehensive GIS weather support

4 Forecast Improvement Goals: Reduced Mean Absolute Errors

5 Making Better Forecasts Leverage all available resources Improvements in numerical weather models New technology Experienced forecast staff Combine these into a Forecast System Measure and quantify the results

6 Making Better Forecasts: Numerical Weather Prediction There are many models No one model is right all of the time Model skill scores continue to improve Forecast system needs to take advantage of these improvements

7 Making Better Forecasts: The DTN/Meteorlogix Forecast System Automatically create a very good first guess forecast DICast statistical forecasts Incorporate an ensemble of many weather models, and use statistical methods to optimize the forecast Integrating manual input and experience into the forecast Graphical Forecast Editing Focus only where manual input adds value Tools to monitor and manage forecasts Real-time verification and feedback Trend and bias analysis

8 Statistical Weather Forecasts An ensemble of high- resolution models, MOS, and Dynamic MOS Updated hourly, using current observations Self-learning, error- correction Proven to have lower errors than any individual forecast component

9 Statistical Forecasts: Better than any single model

10 Manual Input Graphical editing allows forecasters to see the way they think - spatially Focus on limited areas, and specific times Incorporates terrain and local effects Insures consistency

11 DTN/Meteorlogix Forecast System Output Forecast values are available anywhere in the CONUS Points Areas Multiple parameters Temperature, dew point, wind, clouds, etc. There are always 15 days of forecast data Hourly Daily

12 DTN/Meteorlogix Forecast System Benefits Timeliness Forecasts are updated every hour Quality All available forecast data is used in each forecast Makes for the best, most consistent day-in, day-out, forecast Meteorological experience is focused on adding value Extreme events Precipitation and its effects Reliability Forecast products are always current and up to date Scalability Can provide high quality forecasts even without observations

13 Forecast Summary Weather forecasts are improving The way in which weather forecasts are created is rapidly evolving New forecast processes are making more and different kinds of data available Are there ways to take advantage of new weather data in load forecasts?

14 High Impact Weather April 17, 2006 All ERCOT Locations AvgHrlyErrMaxErrMinErr Day 1 Average2.11.72.8 Day 2 Average2.31.72.7 Day 3 Average3.42.83.7 Day 4 Average3.74.23.7 Day 5 Average3.74.23.8 Day 6 Average4.75.54.2 Day 7 Average4.35.44.1

15 High Impact Weather April 17, 2006 RptDateRptDayStationAvgHrlyErrActMaxFcstMaxMaxErrActMinFcstMinMinErr 2006-04-171KABI298 060633 2006-04-171KACT297967267-5 2006-04-171KAUS39996-37365-8 2006-04-171KBRO1.49193273 0 2006-04-171KCRP1.39092271 0 2006-04-171KDFW3.110196-56967-2 2006-04-171KGLS1.78083373 0 2006-04-171KIAH0.892 07270-2 2006-04-171KINK3.199985553-2 2006-04-171KJCT2.410110056582 2006-04-171KLFK1.6919217067-3 2006-04-171KLRD1.510710673752 2006-04-171KMAF2.2939415856-2 2006-04-171KMWL3.510197-454628 2006-04-171KSAT1.399987270-2 2006-04-171KSJT3.399100155616 2006-04-171KSPS210199-256593 2006-04-171KTYR1.5929317068-2 2006-04-171KVCT2.4909227170 Day 1 Average 2.1 1.7 2.8

16 High Impact Weather April 17, 2006 RptDateRptDayStationAvgHrlyErrActMaxFcstMaxMaxErrActMinFcstMinMinErr 2006-04-172KABI2.598 060622 2006-04-172KACT2.697967267-5 2006-04-172KAUS2.49997-27367-6 2006-04-172KBRO2.59194373741 2006-04-172KCRP1.19091171 0 2006-04-172KDFW310197-46967-2 2006-04-172KGLS28083373 0 2006-04-172KIAH0.792 07271 2006-04-172KINK299100155572 2006-04-172KJCT2.810199-256582 2006-04-172KLFK1.8919327067-3 2006-04-172KLRD1.4107 073752 2006-04-172KMAF3.19396358591 2006-04-172KMWL210199-254617 2006-04-172KSAT299 07269-3 2006-04-172KSJT4.8999855616 2006-04-172KSPS3.310196-556615 2006-04-172KTYR1.5929317068-2 2006-04-172KVCT3909227170 Day 2 Average 2.3 1.7 2.7

17 High Impact Weather January 12 th & 13 th, 2007

18 High Impact Weather Model Data – Jan 13 th, 2007 Model disagreement Jan 12 th – Jan 13 th, 2007 KTYR – Tyler, TX ETA MOS GUIDANCE 1/13/2007 1200 UTC DT /JAN 13/JAN 14 /JAN 15 /JAN 16 HR 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 06 12 N/X 36 36 28 34 25 TMP 42 41 39 39 41 41 40 36 33 34 34 35 34 34 33 28 30 33 31 29 27 DPT 42 41 38 35 38 39 37 35 33 34 34 30 26 25 25 22 21 21 21 20 20 CLD OV OV OV OV OV OV OV OV OV OV OV OV OV OV OV OV OV OV OV OV OV WDR 33 34 35 01 35 02 36 35 36 34 32 34 33 35 35 34 35 34 34 34 35 WSP 06 09 08 12 09 05 05 05 04 07 11 12 15 12 15 14 16 16 12 11 09 GFS MOS GUIDANCE 1/13/2007 1200 UTC DT /JAN 13/JAN 14 /JAN 15 /JAN 16 HR 18 21 00 03 06 09 12 15 18 21 00 03 06 09 12 15 18 21 00 06 12 N/X 49 53 36 38 29 TMP 52 52 51 50 50 51 51 50 51 50 48 44 42 40 38 36 36 35 33 34 32 DPT 49 48 47 50 50 49 48 50 51 50 47 41 38 35 33 32 31 29 26 25 23 CLD OV OV OV OV OV OV OV OV OV OV OV OV OV OV OV OV OV OV OV OV OV WDR 29 31 36 36 36 01 04 08 21 31 33 36 36 35 35 35 35 35 36 36 36 WSP 06 07 06 06 07 06 06 04 10 10 08 09 12 13 14 10 13 13 12 15 10

19 High Impact Weather Observed Temperatures

20 High Impact Weather Results and Conclusions Forecasts did not handle the rapid drop in temperatures well Average hourly error of 5.0 for ERCOT locations Enhanced weather editing mode installed soon Easier editing Quicker results in products Better response to rapid temperature change

21 High Impact Weather Improvement

22 DTN/Meteorlogix Contact Information Richard Wilson Director of Energy Services DTN/Meteorlogix Phone: (781) 932-3539 Email: richard.wilson@dtn.com Jeremy Duensing Quality Assurance Manager DTN/Meteorlogix Phone: (952) 882-4554 Email: jeremy.duensing@dtn.com

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