Power Performance Testing: Truly Useful of Just Box Ticking. Mark Young 2 July 2012



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Transcription:

Power Performance Testing: Truly Useful of Just Box Ticking Mark Young

DNV KEMA Energy & Sustainability Part of DNV Group an independent foundation with HQ in Norway founded in 1864 with 11,000 employees globally 200+ wind energy experts 30 GW+ energy assessments globally Testing, inspections, certification, consulting Risk, performance, and quality management Research & innovation Offices in over 30 countries 2

Why is power performance testing conducted? Regulatory compliance Warranty verification - Obtain liquidated damages if performance issues are observed Turbine performance verification (asset risk management) - As-built baseline and life-cycle monitoring Characterise actual turbine performance in sitespecific conditions - To be used to update yield forecasts and/or investigate shortfalls - Valuable input to OEMs Maintain balance in OEM/owner relationship Increased certainty -> increase asset value 3

Perspectives on power performance testing OEM perspective: - Verify the power performance in conditions that are consistent with the published (type test) power curve Owner/operator perspective: - Verify the actual insitu power performance Conflict! - Consequences Range of philosophies with owner/operators 4

Power performance warranty terms: typical examples Absolute warranty terms: 95%, 97%, 98%, 100% Lesser of (95%) or (100% - Uncertainty) Flat terrain 97%, complex terrain 100% Uncertainty 98% minus uncertainties (Measured AEP/Warranted AEP)x100 (Uncertainty% - 4)/2 > 95% Typical measurement uncertainty: - 3-5% in flat terrain and 4-8% in complex terrain 5

Uncertainty effects on warranty example Three turbines, complex terrain Warranty criteria based on average results of the three tests Warranty criteria: - Measured Annual Energy/Predicted Annual Energy + uncertainty > 97% Results: - Measured Annual Energy/Predicted Annual Energy = 94% - Uncertainty = 7.5% - Result = 101.5% Warranty is met, but 6% of the expected energy is potentially missing! 6

Performance testing results from DNV KEMA database Data set encompasses: ~200 turbine tests (about half of DNV s experience) Dozens of different turbine types Flat and complex terrain ~ 50/50 Troubled turbines, good performers, measurement issues Across all seasons Global results 7

8

Variations in turbine performance Variation within turbine model Variation with site conditions Variation within single wind project Turbine issues Site conditions Reference curve measurement errors Anemometer and calibration differences

Case studies Stability Temperature/density/elevation Complex terrain and statistical (TI) effects Controls requiring optimisation New control algorithms not fully validated High shear Intermittent pitching routines Blade surface degradation Curtailments normal operation or not? In many cases, poor performers have been improved, even if turbines did not fail An expensive way to find incorrect control parameter settings! 10

Percent of Rated Power Measured power curve all valid data from PPT 120% 100% 80% Measured PC Warranted PC 60% 40% 20% 0% -20% 0 2 4 6 8 10 12 14 16 Wind Speed (m/s) 11

Percent of Rated Power Measured power curve valid data during stable conditions 120% 100% 80% Measured PC Warranted PC 60% 40% 20% 0% -20% 0 2 4 6 8 10 12 14 16 Wind Speed (m/s) 12

Residual Power (%) Density 15 10 5 0-5 -10-15 -20-25 Low Air Density -30-35 -5 0 5 10 15 20 25 30 35 Temperature Density Correction Limitations 13

Complex terrain 14

Best practices realising the most from your investment Those that measure, understand Proper mast and instrument boom design Careful test site selection Traditional test combined with nacelle-based testing - Nacelle-based test standard IEC 61400-12-2 under development Long test periods to capture inter-seasonal effects and verify Negotiate fair (risk shared) and testable warranty terms with OEMs Consider anemometer differences between testing and wind resource measurement Use of SCADA tower for test - Practical for large projects Repeat test to identify performance degradation Gain experience with rotor-area average and other newer techniques Incorporate measurement results into project performance prediction Learn from results and incorporate into turbine procurement process 15

Mark Young Head of Department, Cleaner Energy Services DNV KEMA Energy & Sustainability www.dnvkema.com Palace House 3 Cathedral Street London SE1 9DE Tel: +44 20 7716 6591 Mobile: +44 79 6972 9915 mark.young@dnvkema.com www.dnvkema.com www.dnv.com/windenergy