INTEGRATING DISPARATE DATA SOURCES TO ASSESS THE PERFORMANCE ACROSS A FLEET OF WIND TURBINE GENERATORS

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1 INTEGRATING DISPARATE DATA SOURCES TO ASSESS THE PERFORMANCE ACROSS A FLEET OF WIND TURBINE GENERATORS Bradley Johnson, Wind Plant Performance Engineer EDF Renewable Energy, San Diego, CA EWEA 2014 Operational Assessment Workshop Topic 2: Post-Construction Yield Analysis Techniques December 9-11, 2014

2 CORPORATE STRUCTURE EDF the leading electricity company in the world EDF Energies Nouvelles (EDF EN) the global renewable arm of the EDF group EDF Renewable Energy the US Subsidiary of EDF EN and headquarters of EDF EN activities in North America EDF Renewable Services the O&M branch for North America HQ: San Diego, CA EDF EN Canada the Canadian Subsidiary of EDF EN EDF EN Mexico the Mexican Subsidiary of EDF EN (Current Conditions) EWEA 2014 Operational Assessment Workshop 12/10/2014 2

3 INTEGRATED OPERATOR IN NORTH AMERICA Origination Development Transaction and Construction Generation Operations & Maintenance 5.9 GW developed 1.6 GW under construction in GW owned and operated 8.6 GW operated Focus of analytics on owned assets, although applicable for third party O&M serviced wind farms through service packages EWEA 2014 Operational Assessment Workshop 12/10/2014 3

4 ASSET SUMMARY (WIND) 2.8 GW installed capacity 24 Wind Farms 1,468 WTGs 7 different WTG manufacturers 12 different WTG Models Several more distinct configurations between models >40 permanent met towers Substations, Plant level control systems, etc. **ignoring small legacy projects, machines < 500 kw EWEA 2014 Operational Assessment Workshop 12/10/2014 4

5 CENTRALIZED REPORTING AND AGGREGATION Native OEM SCADA A 10 minute data staged Native OEM SCADA B 10 minute data staged Native OEM SCADA C 10 minute data staged Native OEM SCADA D 10 minute data staged Report A Report B Report C Report D PI / SQL / Tableau enable controlled, consistent analytics between assets Decentralized approach Project Static data Advanced calculations Centralized approach 10 minute summaries, 1/night Live Dashboards EWEA 2014 Operational Assessment Workshop 12/10/2014 5

6 Static Data Overview EWEA 2014 Operational Assessment Workshop 12/10/2014 6

7 SQL SERVER STATIC DATA Static Data As Built Coordinates Turbine Type/Configurations Contractual power curves Complete Fault descriptions Power Curve Test Results Reference Met masts IEC valid wind sectors Site calibration results (if needed) Nacelle Transfer Functions Project Energy Estimates Data needs to be linked across the business chain to ensure consistency EWEA 2014 Operational Assessment Workshop 12/10/2014 7

8 FAULT TABLES All WTGs mapped to a specific list of fault descriptions In addition to MFG fault attributes, EDF derives further attributes of the fault for reporting/analysis including.. IEC definition of availability Full Performance, Partial Performance Derated, Forced Outage, Scheduled Maintenance, Planned Corrective Actions, etc. GADS (Generating Availability Data System) NERC approved system of reporting availability/faults Links faults to technology system/sub-system o Gearbox, Blade Bearings, Converter, Pitch System, etc. EDF Internal Categorizaiton Process High level categories to classify performance and align operational losses with Energy Production Estimates EWEA 2014 Operational Assessment Workshop 12/10/2014 8

9 Example DNV/GL report PROJECT ENERGY ESTIMATES Linking of Operational Data with Energy Production Estimates (EPE) is required to determine energy gaps Generic EDF Categorization developed to map all vendor EPEs to a common convention Wake effects inherent in nacelle wind speeds, EPE wake loss data not directly compared to operational data Ideal Production (Gross Wake ) WTG Availability BoP/Grid Availability Electrical Efficiency Performance Environmental External Curtailment Misc. Downtime/Curtailment Net Production (P50) EWEA 2014 Operational Assessment Workshop 12/10/2014 9

10 NACELLE TRANSFER FUNCTIONS Every WTG additionally linked to a EDF-derived nacelle transfer function (NTF) based on previous correlations of met mast wind speeds vs nacelle wind speeds for turbines close to met masts Operational wind speeds then corrected by this ratio before deriving a theoretical possible power by a lookup to the power curve Initially measured during power performance test Periodically, Re-checked/updated with data of turbines near permanent met masts NTFs measured only derived during full performance periods Well known the relationship will change during downtime EWEA 2014 Operational Assessment Workshop 12/10/

11 VARIATION IN NACELLE TRANSFER FUNCTIONS Before After NTFs must be re-evaluated if parameters governing rotor behavior are changed Example: Yaw correction to a turbine affected ratio of met mast wind speed to nacelle wind speed by up to 7% ~20% difference Turbine down Turbine operating NTFs derived from Full Performance data not specifically valid for possible power calculations when turbine is down NTF typically increases significantly when turbine is down EWEA 2014 Operational Assessment Workshop 12/10/

12 Tableau Demonstration EWEA 2014 Operational Assessment Workshop 12/10/

13 Operational Data Overview EWEA 2014 Operational Assessment Workshop 12/10/

14 AGGREGATION IN SQL High resolution historian >300,000 tags 1/ day next Met Towers Critical data summaries of ~50,000 tags Individual WTGs Individual tables for each asset type (WTGs, met towers, etc.) Site OPC Servers Plant Controllers/Management Systems, Substations, energy meters, etc. Site SCADA servers SCADA 10m summaries, High resolution fault logs EWEA 2014 Operational Assessment Workshop 12/10/

15 Technical static data Operational Data SQL DATA PROCESSING T-SQL Stored Procedure WTG table Met mast table Data Validity checks & substitution logic (min/max, repeating data, etc) Site Table (agg. Site data) BoP Table Primary, Foreign key relationships Possible Power & Energy calculations Power Curves NTFs EPEs Asset Table Fault table Site Calibrations Invoiced Production Project table Categorizaiton Algorithm EWEA 2014 Operational Assessment Workshop 12/10/

16 POSSIBLE POWER AND ENERGY Possible power calculated both from nacelle anemometry and also from reference met stations for applicable turbines (e.g. those performance tested) Warranted Power curve used with wind speeds for possible power (typically within 0.15 kg/m 3 of site density, or whatever power performance contract enumerates) 10m met wind speed V corr,met = V met,hh ρ ref ρmet 1 3 P poss = f(v corr,met ) If wind speed source is met mast If wind speed source is nacelle V corr = V nac ρ ref ρmet 1 3 V ntf = f(v corr ) 10m nacelle wind speed P poss = f(v ntf ) NTFs EWEA 2014 Operational Assessment Workshop 12/10/

17 Initial Categorization CATEGORIZATION PROCEDURE Blade pitch deviation scehme in development Yes Out of Electrical Specification Status Code (1 per 10min) Status code lookup Yes Wind & power data available θ meas θ0 P meas Pposs No No Unknown Time Breakers Open WTG Under - producing? Setpoint WTG Externally Curtailed Yes Partial Perf. Ext. Curtailment No Full Performance T amb, RH Icing Likely? Partial Perf. Icing Yes No Misc. Curtailment MFG category IEC category GADS category EDF-Re category Native MFG Availability Counters (<10m precision) System faultless? System Fault Category EWEA 2014 Operational Assessment Workshop 12/10/

18 Tableau Demonstration: Data Categorization Process EWEA 2014 Operational Assessment Workshop 12/10/

19 Tableau Demonstration: Before/After Power Curve Analysis EWEA 2014 Operational Assessment Workshop 12/10/

20 Tableau Demonstration: Operational Assessment EWEA 2014 Operational Assessment Workshop 12/10/

21 Tableau Demonstration: Lost Energy Breakdown by Faults EWEA 2014 Operational Assessment Workshop 12/10/

22 EXTRA SLIDES EWEA 2014 Operational Assessment Workshop 12/10/

23 DISPARATE DATA Defined as distinct, different or entirely dissimilar data A Sample of the data available: Wind speed, Temperature, pressure, power output, number for cycles, life time production Fault numbers, counts, descriptions & durations Pitch system type, blade pitch, RPM Gearbox make, model, serial number, gear ratio bearings types Blade length, manufacturer, serial number, set number, mass Power rating, power curves Latitude, Longitude, Elevation, tower height Maintenance and repair history, parts consumed, parts cost, work hours, technician's notes For us to accurately quantify and improve Performance and Reliability we have to link all of this data together EWEA 2014 Operational Assessment Workshop 12/10/

24 END GOALS OF PLANT ANALYTICS 1. Comprehensive Gap Analysis of plant losses with direct comparison with the Pre-construction Energy Production Estimates (EPEs) Re-evaluate budgets, future production, if needed from initial EPE 2. Comprehensive Power Curve Analysis based on Nacelle and Met Tower anemometry Find top sites, turbines eligible for power performance upgrades Detect potential controller parameter inconsistencies 3. Top Faults Causing Availability Losses & Lost Energy Quantify largest causes of downtime worth pursuing corrective actions 4. Parts & Labor Costs of O&M Link operational data with SAP data of service orders/o&m costs Focus of presentation Consistent and traceable calculation methodology across all manufacturers, SCADA systems, and sites EWEA 2014 Operational Assessment Workshop 12/10/

25 POWER CURVE TEST RESULTS All projects undergo a power performance test shortly after commissioning as defined IEC If no true IEC sectors can be defined, a site calibration is done All Results staged in SQL Nominated WTG units with reference mast Performance test results Freestream wind sectors Site calibration results per wind sector (if any) Linking this data definition with operational data enables automated performance analysis equivalent to the initial performance test to be recreated at any time EWEA 2014 Operational Assessment Workshop 12/10/

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