Next Generation of Wind Data. Integrating SCADA concepts for improved wind assessment and operations

Transcription

1 Next Generation of Wind Data Integrating SCADA concepts for improved wind assessment and operations

2 Doug Taylor Wind Assessment and SCADA Manger John Deere Renewables

3 John Deere Renewables Developers, owners, financing partners, constructors, and operators of mid-sized wind farms Started in 2005 with community-based wind, tied to the landowners Current fleet: 730+ MW of generation capacity 420 turbines 37 farms 8 U.S. states Operating Commissioning Construction (717 MW) (16 MW) (0 MW) Operations Center

4 JDR SCADA Monitoring system JDR SCADA was custom built using the PI system Data from all wind turbines in fleet 4 WTG manufactures External access to 3 rd parties Google Earth interface

5 JDR SCADA Monitoring System Operations DB2 OSIsoft PI PI Java Web App Reporting Web Service Java Web App Forecasters Wege Wind Farm Google Earth

6 Wind Assessment and Operations TIME FOR INNOVATION

7 Wind Assessment Long Term Ref. ASOS/meso-model Site Information Site visits, GIS Loss Model Engineering AEP On-site Data Met towers Wind Regime Correlate-Predict Model WASP/WindPro GCF NCF Shear Data SODAR/LIDAR CFD Model TBD Statistical Model Excel Variability/ Seasonality Wind Modeling $$$

8 Wind Data Measurement Long Term Ref. ASOS/meso-model On-site Data Met towers Shear Data SODAR/LIDAR

9 Wind Data Measurement Long Term Ref. ASOS/meso-model On-site Data Met towers Shear Data SODAR/LIDAR

10 Wind Data Measurement Long Term Ref. ASOS/meso-model On-site Data Met towers Shear Data SODAR/LIDAR

11 Wind Regime Long Term Ref. ASOS/meso-model On-site Data Met towers Shear Data SODAR/LIDAR

12 Building better tools Convergence of technologies and industry New tools can be created by the application of PI process technologies for the more complete collection of data: High Frequency More sensors (integrated, coordinated) Historization and storage of time series More complete evaluation of recorded data Integration with other systems (SCADA, NWP)

13 Wind Data Loggers 12 Sensor Channels Current Loggers via Sat/Cell Once a Day 10 min average data

14 Next Generation Loggers Now that s a Logger! Standard Protocols PI/Echo OSI PI More 12 Sensor Channels Next Generation Loggers Open Real Time via Connect. Sat/Cell Mesh Once a Day Networks Twitter?!? Intelligent Behavior GPS High Frequency 10 min storage data / transmittal

15 Loggers Integrated with PI ZOMG!!11!! Data Loggers SODAR/LIDAR Reference OSI PI Real time Monitoring Common Format Consistent Storage Analysis Tools QA/QC

16 QA/QC of Wind data Missing Data Tower Shadow Vibratory Mode Icing Events Damaged Sensors Sensor Degradation Sensor Changes Calibration Issues Rain Events

17 Value of High Frequency Data Average vs. Actual Wind Speed (m/s) More accuracy, reduced uncertainty But not statistically different for Wind More accuracy, reduced uncertainty Resource Assessment Not statistically different than low-res data

18 Value of High Frequency Data High wind speed cut-off Low wind speed cut-off Higher resolution identifies cut-in/cut-out events that would be lost in the 10-min average data

19 Turbulence Calculations Looking at turbulence in less than 10-min average data provides more insight Data recorded at high resolution would provide the source for better analysis

20 Signature of Gusts Defining a spectral density analysis could define a signature of the turbulence.

21 Applications of Next Generation Loggers and PI Integration RIDGELINE SENSOR NET

22 Ridgeline Sensor Network Mash-up of technologies: Next-gen loggers Mesh networking OSI PI technology

23 Ridgeline Sensor Network Home Office

24 Ridgeline Sensor Network Scout towers deployed along ridge line Collecting synchronized data Reporting back to the central tower

25 Ridgeline Sensor Network Data is used to characterize wind flow over the ridgeline Validate CFD analysis Many applications beyond ridgeline

26 Community of Sensors Operations Forecasting

27 Forecasting Improvemetns Operations Forecasting

28 Future of Wind Opportunity: Improved loggers More sensors Higher frequency New applications of technology in wind Results: Refinement of analysis Reduced uncertainty

29 Thank you Copyright 2010 OSIsoft, LLC., 777 Davis St., San Leandro, CA 94577