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Research Papers: Alternative Energy Sources

Precision Computation of Wind Turbine Power Upgrades: An Aerodynamic and Control Optimization Test Case

[+] Author and Article Information
Davide Astolfi

Department of Engineering,
University of Perugia,
Via G. Duranti 93,
Perugia, 06125, Italy
e-mail: davide.astolfi@unipg.it

Francesco Castellani

Department of Engineering,
University of Perugia,
Via G. Duranti 93,
Perugia, 06125, Italy
e-mail: francesco.castellani@unipg.it

Mario Luca Fravolini

Department of Engineering,
University of Perugia,
Via G. Duranti 93,
Perugia, 06125, Italy
e-mail: mario.fravolini@unipg.it

Silvia Cascianelli

Department of Engineering,
University of Perugia,
Via G. Duranti 93,
Perugia, 06125, Italy
e-mail: silvia.cascianelli@studenti.unipg.it

Ludovico Terzi

Renvico srl,
Via San Gregorio 34,
Milano, 20124, Italy
e-mail: ludovico.terzi@renvico.it

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received July 23, 2018; final manuscript received December 31, 2018; published online January 18, 2019. Assoc. Editor: Christopher Niezrecki.

J. Energy Resour. Technol 141(5), 051205 (Jan 18, 2019) (9 pages) Paper No: JERT-18-1567; doi: 10.1115/1.4042450 History: Received July 23, 2018; Revised December 31, 2018

Wind turbine upgrades have recently been spreading in the wind energy industry for optimizing the efficiency of the wind kinetic energy conversion. These interventions have material and labor costs; therefore, it is fundamental to estimate the production improvement realistically. Furthermore, the retrofitting of the wind turbines sited in complex environments might exacerbate the stress conditions to which those are subjected and consequently might affect the residual life. In this work, a two-step upgrade on a multimegawatt wind turbine is considered from a wind farm sited in complex terrain. First, vortex generators and passive flow control devices have been installed. Second, the management of the revolutions per minute has been optimized. In this work, a general method is formulated for assessing the wind turbine power upgrades using operational data. The method is based on the study of the residuals between the measured power output and a judicious model of the power output itself, before and after the upgrade. Therefore, properly selecting the model is fundamental. For this reason, an automatic feature selection algorithm is adopted, based on the stepwise multivariate regression. This allows identifying the most meaningful input variables for a multivariate linear model whose target is the power of the upgraded wind turbine. For the test case of interest, the adopted upgrade is estimated to increase the annual energy production to 2.6 ± 0.1%. The aerodynamic and control upgrades are estimated to be 1.8% and 0.8%, respectively, of the production improvement.

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Figures

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Fig. 1

The layout of the wind farm

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Fig. 2

The power coefficient Cp–power production curve: T7 and a sample wind turbine (T2), Daft1 dataset

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Fig. 3

The power coefficient Cp–power production curve: T7 and a sample wind turbine (T2), Dbef dataset

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Fig. 4

The power difference between T7 and T6, before and after the upgrade

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Fig. 9

The average difference between measurements and simulation (Eq. (6)), for datasets D1 and D22 and for a sample run of the model

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Fig. 8

The average difference between measurements and simulation (Eq. (6)), for datasets D1 and D21 and for a sample run of the model

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Fig. 7

The power–rotor revolutions per minute curve, for dataset Daft2. Turbines T7 and T1.

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Fig. 6

The power–rotor revolutions per minute curve, for dataset Daft1. Turbines T7 and T1.

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Fig. 5

The average difference R between power measurement y and estimation ŷ (Eq. (6)). Datasets: D1 and D2. Sample run of the model.

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Fig. 10

The average difference R between measurements and simulation (Eq. (6)), for datasets D1 and D2 and for a sample run of the model. T4 test case.

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