Uncertainty quantification on the effects of rain-induced erosion on annual energy production and performance of a Multi-MW wind turbine
Francesco Papi,
Francesco Balduzzi,
Giovanni Ferrara and
Alessandro Bianchini
Renewable Energy, 2021, vol. 165, issue P1, 701-715
Abstract:
Wind turbine blade erosion has risen to the attention of researchers and industry lately in an effort to keep ageing wind farms productive. Although not new, erosion-related blade damage seems to be more severe in recent, particularly off-shore, installations. With the high blade-tip speeds of modern wind turbines, installation in rainy locations can cause significant damage. While all the players in the industry agree that a reduction on Annual Energy Production (AEP) has to be expected, its magnitude remains uncertain, with wide range of variability forecasted in published research. This work proposes a probabilistic framework to assess AEP reductions, allowing for a better understanding of the key mechanism that cause turbine power loss and for a better quantification of AEP losses. The method is tested on the DTU10MW reference case. Erosion-related uncertainties are estimated based on available literature data. Lift and drag coefficients of the airfoils are derived using CFD, and the entire wind turbine is simulated aero-servo-elastically using a Blade Element Momentum code. An arbitrary Polynomial Chaos method is used to estimate the uncertainties associated to key turbine figures due to the erosion inputs. Results show how AEP reductions, while still significant, are lower than most published literature indicates.
Keywords: Uncertainty-quantification; Wind energy; Annual energy production; Erosion; Arbitrary polynomial chaos; Wind turbine∖ (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:165:y:2021:i:p1:p:701-715
DOI: 10.1016/j.renene.2020.11.071
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