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Power Delivery & Markets Distribution Advisory Council February 13, 2007 Storm Modeling

Power Delivery & Markets Distribution Advisory Council February 13, 2007 Storm Modeling. Weather Forecast Benchmarking and Plant Damage Modeling for Public Utilities. Scott Glenn, Rich Dunk, Louis Bowers Coastal Ocean Observation Lab.

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Power Delivery & Markets Distribution Advisory Council February 13, 2007 Storm Modeling

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  1. Power Delivery & MarketsDistribution Advisory CouncilFebruary 13, 2007Storm Modeling

  2. Weather Forecast Benchmarking and Plant Damage Modeling for Public Utilities Scott Glenn, Rich Dunk, Louis Bowers Coastal Ocean Observation Lab Coastal Ocean Observation Lab http://marine.rutgers.edu/cool John Carlson, Wayne Wittman Public Service Electric & Gas Public Service Electric & Gas http://www.pseg.com Coastal Observation and Prediction Sponsors:

  3. Agenda • Executive Summary – What Have We Done So Far? • What is our weather forecast/storm management approach? • Weather Forecast Modeling • Future Plans and how EPRI can help.

  4. Executive Summary • Cooperative research project between Rutgers University and Public Service Electric & Gas • Operational meteorological forecasts and “alerts” since October 2004. • Operation of high-resolution Weather Research Forecast (RU-WRF) model since 2005. • Storm plant damage forecast model development 2005-2006. • Overall severe storm forecast validation of 82.9% from October 2004 through December 2006 out of 602 events.

  5. Tasks • RU-WRF model operation • Operational weather forecast tailored to PSE&G delivered daily via protected website by 7 AM. Highly detailed forecast for days 1 and 2. General overall synopsis for forecast days 3 through 7. • Issuance of Severe Weather “Alerts” during inclement weather conditions transmitted to PSE&G personnel via email and protected website. • Experimental plant damage forecast transmitted to PSE&G personnel via email at the initiation of severe weather alerts.

  6. Rutgers Weather Forecast Process • Forecasts issued by Senior Meteorologist and upper-level undergraduate students. • Model has state-of-the-art physics and microphysics packages, high-resolution sea surface temperatures (SST), and local mesoscale meteorological observations. • Forecasters use RU-WRF model in combination with various other forecast models, analyses, ocean products, etc. to formulate forecast.

  7. Student Teaching Teams • Rutgers forecast teams consists of Masters Level Senior Meteorologist and 3-6 upper-level undergraduate students. • Provides real-world forecast experience for college students. • A total of 23 students have participated in the project since October 2004. • Graduating students have gone on to careers in private sector, federal government, and broadcast meteorology.

  8. Modeling Introduction • WRF: Weather Research Forecast • Run 3x daily • Duration out 24 to 120 hours • Climatological “Model” • Statistical correction to WRF model data using observations. • Plant Damage Model • Prognostic equations to predict PSE&G equipment loss during severe weather events. Equations developed using historical damage reports and archived meteorological observations. Input to model is RU-WRF forecast severe storm parameters.

  9. Alert Criteria • Severe Thunderstorms Possible • Severe thunderstorms are expected within the first forecast period or are presently occurring. • Heavy Rainfall Alert • Heavy rainfall amounts or rates are expected or occurring. • Significant Wet Snowfall Accumulations • Greater than 3 inches of wet snow is expected to fall, and stick, especially on branches and power lines. Significant Dry Snowfall Accumulations • Greater than 5 inches of dry snow is expected to fall. Significant Icing Alert • Non-trivial accumulation of freezing rain is expected, or greater than 0.1 inches of sleet. • Excessive Heat Alert • Air temperatures and/or heat indices exceed 90° F for a period greater than 3 hours, or if temperatures and/or heat indices max at or above 95° F for any length of time. • Excessive Cold Alert • Air temperatures go below 15° F for a period greater than 3 hours, or if temperatures go below 10° F for any length of time. Also used when wind chills go below 0° F for any extended period of time. • Excessive Wind Alert • Sustained winds exceed 25 MPH for a period greater than 3 hours, or if wind gusts above 30 MPH at any time. • Frequent Lightning Strikes Possible • Frequent cloud-to-ground lightning is possible during the next 12 to 24 hour period.

  10. Verification • Severe weather forecasts are verified using strict criteria determined crucial by PSE&G. • Plant Damage forecasts are verified using actual plant damage data. • Model performance used to adjust model in future upgrades. Severe Weather Alert Verification Statistics Oct 2004-Dec 2006

  11. Damage • Plant Damage prognostic equations developed from PSE&G storm damage database (2003-2006). • Plant Damage data compared to available weather observations (13 locations in NJ) to develop equations. • Plant Damage forecast transmitted via email to PSE&G personnel. • Forecast verified and accuracy used to periodically update equations. SOUTHERN DIVISION ALERTS: Excessive Wind Alert COVERAGE: WIDESPREAD DAMAGE CALLS: 75 POLES: 7 WIRES: 23 TREE: 28 EXPLOSION: 0 PART POWER: 12 HIGH_LOW VOLTAGE: 5

  12. Case Study: High-Resolution Plant Damage Prediction • High-resolution modeling of local-area specific forecast problems. • Topographically enhanced wind flows, e.g. Watchung Mountains in NE NJ. • Rain/Ice/Snow Line prediction using high-resolution SST. • Worst case scenario Hurricane damage. • Rainshadow effect and localized flooding.

  13. Case Study: Tropical Storm Ernesto September 1-3, 2006 RU-WRF provided the best real-time forecast of Tropical Storm Ernesto after landfall. Used by Researchers, by Regional, State & Local Managers, by Power Companies, by Agriculture Extension. The most significant difference with operational models was improved physics. This is a common storm track for the Mid-Atlantic States.

  14. Case Study: Tropical Storm Ernesto September 1-3, 2006

  15. Limitations • There is no such thing as a perfect forecast. • Plant Damage model effectiveness tied to availability of relevant data and model verification. • Small-scale phenomena still not well simulated by weather forecast models, e.g. isolated summertime severe thunderstorms. • Rare and extreme events may not be well forecast by plant damage model equations.

  16. Next Steps • Benchmarking Study – Best Weather Practices • Unified Prediction Program - Common Alert Criteria • Development of Plant Damage Model • Collect data • Plant Damage • Weather Observations • Develop Equations • Test Model • Final Goal: A best practices forecasting approach to weather management that can be applied to any electric utility.

  17. End

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