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SMART GRID INTEROPERABILITY PANEL SUMMER 2012 FACE-TO-FACE PORTLAND, OREGON  JULY 10-12, 2012 WEATHER TASK GROUP SESSIONS AL HEFNER (NIST)

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Presentation on theme: "SMART GRID INTEROPERABILITY PANEL SUMMER 2012 FACE-TO-FACE PORTLAND, OREGON  JULY 10-12, 2012 WEATHER TASK GROUP SESSIONS AL HEFNER (NIST)"— Presentation transcript:

1 SMART GRID INTEROPERABILITY PANEL SUMMER 2012 FACE-TO-FACE PORTLAND, OREGON  JULY 10-12, 2012 WEATHER TASK GROUP SESSIONS AL HEFNER (NIST)

2 SUMMER 2012 FACE-TO-FACE PORTLAND, OREGONOutline Weather Information Model Background Weather Task Group Recommendations Planning potential SGIP Weather PAP 2

3 SUMMER 2012 FACE-TO-FACE PORTLAND, OREGON Need for SGIP Weather Data Activities Today there are multiple SDO weather data model efforts Need coordination and co-development of weather information models thorough  use cases development  cross-participation between weather data model efforts SGIP can play a constructive role to insure interoperability:  broad stakeholder participation and needs representation  inputs by Renewable/DER, utility/ISO/RTO community Vision: develop unified modeling approach and/or a well- defined weather information model development ecosystem to ensure consistency and mappings. 3

4 SUMMER 2012 FACE-TO-FACE PORTLAND, OREGON Existing SGIP Weather Data Activities SGIP PAP 17/B2G White Paper: Weather Information Model Standard for Integrating Facilities with Smart Grid - guided ASHRAE SCP201P using an extension of WXXM PAP 16 discussions of transmission wind plant and DER weather information model requirements:  SunSpec, AWEA documents related to Weather Data  Bidirectional weather information exchange: weather sensor data collected at wind/solar generator/plant forecast information for use at wind/solar generator/plant DRGS DEWG Subgroup B (UCs and Information models) identified Weather Data as Highest Priority Gap and defined goal of UC development and model consistency 4

5 SUMMER 2012 FACE-TO-FACE PORTLAND, OREGON SDO Weather Data Model Activities WXXM general standard for weather data (from aviation)  moving to the WMO to become an international standard  based on core models of Open Geospatial Consortium  SGIP could coordinate through National Weather Service ASHRAE SCP201P weather model based on WXXM with minor extensions e.g. solar irradiance, focused on loads IEC TC57 Joint TG (WG10, WG17, JWG25) on weather UCs  IEC 61850, include weather information from meteorological towers at power plants, substations, DER  “Adding Forecasts to the IEC ,” Giebel and Gehrke  what data is collected, where does it go, what is it used for 5

6 SUMMER 2012 FACE-TO-FACE PORTLAND, OREGON Example Weather Data Activities EPRI looking at  CIM for utility enterprise and IEC for collecting data  UCs for forecasting generation, dispatch, and bidding Cal ISO asked if hour-ahead generation forecasts can be improved from 20% error using upstream met. tower data Sothern California Edison, Solar Power Forecasting Argonne National Labs, Wind Power Forecasting DOE SunShot FOA on forecasting at sub-hourly, hourly, day www1.eere.energy.gov/solar/sunshot/financial_opps_detail.html?sol_id=511 6

7 SUMMER 2012 FACE-TO-FACE PORTLAND, OREGONOutline Weather Information Model Background Weather Task Group Recommendations Planning potential SGIP Weather PAP 7

8 SUMMER 2012 FACE-TO-FACE PORTLAND, OREGON Weather TaskGroup Recommendations Key experts group: weather data, renewables, buildings:  AWEA, SunSpec  NOAA, EPRI, Argon NL  WXXM/WMO, IEC, ASHRAE Concern that lack of coordination between WMO, IEC, ASHRAE might lead to Smart Grid interoperability issues SGIP Weather UC collection/development would provide guidance to standards development: WMO,IEC,ASHRAE Define a PAP proposal for future SGIP GB consideration  would give ability/visibility to pull in resources and experts 8

9 SUMMER 2012 FACE-TO-FACE PORTLAND, OREGON Tasks for potential SGIP Weather PAP 1)Outreach: NOAA, NREL, SunShot Weather FOA, ERPI, ISO/RTO, Private weather forecasters 2)Coordinate and collect Smart Grid Weather UCs and develop additional use cases where needed. a)Business practices (needed for Bidding practice for example) – what is being done and might be done; e.g., Texas (retail energy bidding), European model, b)Building/facility – renewable (weather forecasting), CHP (load forecasting) c)Generation Plants (wind, solar, wave, etc.) 3)Draft White Paper on DRGS device Weather Information Model UC requirements closely aligned/leveraging B2G White Paper 4)Coordinate appropriately with the multiple SDOs to ensure that developed weather data standards will be interoperable. 9

10 SUMMER 2012 FACE-TO-FACE PORTLAND, OREGONOutline Weather Information Model Background Weather Task Group Recommendations Planning potential SGIP Weather PAP 10

11 SUMMER 2012 FACE-TO-FACE PORTLAND, OREGON Outreach and Cross Coordination NOAA, NREL, SunShot Weather FOA, ERPI, universities ISO/RTO (TSO), Distribution utilities Private weather forecasting firms, e.g., energy&meteo and Windlogic Variable Renewable groups with forecasting activities:  AWEA, SunSpec, UVIG, 3Tier and AWS TruePower SDO’s:  WXXM/WMO – Matt Peroutka is US Representative  IEC – Frances Cleveland, Stan Klein, Gregor Giebel  ASHRAE PAPs/DEWGs: PAP16, PAP17, DRGS, B2G 11

12 SUMMER 2012 FACE-TO-FACE PORTLAND, OREGON Initial Use Case Classification (page 1) Application of Weather Data by Wind/Solar/CHP Generator Forecasting data may be used autonomously by a single turbine or wind farm in the middle of nowhere.  Wind farm determine its own maintenance schedule, taking next few day low-wind periods into account. (cleverfarm.com) CHP generator use weather data to forecast thermal load demand and determine CHP generation schedule and projected generation availability. Microclimate data and forecasting used for storage charge management and microgrid planed islanding. Historical data for Wind/Solar/CHP plant siting. 12

13 SUMMER 2012 FACE-TO-FACE PORTLAND, OREGON Initial Use Case Classification (page 2) Communication of microclimate Weather Data collected by Wind/Solar/CHP Generators to forecasters: Microclimate data collected from individual rooftop solar Wind plant individual turbine and met. tower data Forecasting and Sensor Data needs for Grid Applications: Probabilistic distribution weather forecast for generator production, market and operational requirements Outage prediction/restoration from major storms using weather sensor data including lightning Disturbance analysis using rapid weather data exchange 13

14 SUMMER 2012 FACE-TO-FACE PORTLAND, OREGON Initial Use Case Classification (page 3) Types of forecasts required for Wind Power: Basic operation: Point forecasts Operation which takes into account asymmetrical penalties on deviations from the bid: Quantile forecasts Stochastic optimization taking into account start/stop costs, heat storage, and/or ’implicit’ storage by allowing the hydro power production to be changed with wind power production: Scenarios respecting correctly calibrated quantiles and auto correlation. 14 Source: Henrik Aalborg Nielsen, ENFOR

15 SUMMER 2012 FACE-TO-FACE PORTLAND, OREGON Possible Gaps in Existing Standards WXXM is very sketchy with regard to representing uncertainty, as it is made to transport observations, not forecasts. Might be helpful to add info from individual turbines such as wind speed/direction at turbine altitudes (to better represent microclimate). Need better way to aggregate data over various time and spatial scales. Time and spatial scales vary widely:  Time scales vary between historical data for siting, market or restoration, rapid data exchange for disturbance analysis  Spatial scales vary between wind/solar generator or farm, building/campus, microgrid or distribution system, ISO/RTO 15

16 SUMMER 2012 FACE-TO-FACE PORTLAND, OREGONReferences environment-hearing-rd-high-performance-renewable-energy- development environment-hearing-rd-high-performance-renewable-energy- development Forecasting of Wind Power in IEC ed 2, Dr. Gregor Giebel, DTU Wind Energy; AddingForecastsToIEC pdf cleverfarm.com DOE SunShot FOA on forecasting at sub-hourly, hourly, day www1.eere.energy.gov/solar/sunshot/financial_opps_detail.ht ml?sol_id=511 16


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