Applied Sciences

2024

Jump to: 2022, 2021, 2020

16 pages, 4244 KiB

Open AccessArticle

Optimizing Bladeless Wind Turbines: Morphological Analysis and Lock-In Range Variations

by Enrique González-González, David J. Yáñez, Susana Del Pozo and Susana Lagüela

Appl. Sci. 2024, 14(7), 2815; https://doi.org/10.3390/app14072815 - 27 Mar 2024

Cited by 1 | Viewed by 2562

Abstract

This study presents a comprehensive exploration centred on the morphology and surface structure of bladeless wind turbines (BWTs) aimed at optimizing their wind energy harvesting capability. Unlike conventional wind technology where vortex-induced vibration (VIV) is seen as problematic due to aeroelastic resonance, this [...] Read more.

This study presents a comprehensive exploration centred on the morphology and surface structure of bladeless wind turbines (BWTs) aimed at optimizing their wind energy harvesting capability. Unlike conventional wind technology where vortex-induced vibration (VIV) is seen as problematic due to aeroelastic resonance, this effect becomes advantageous in BWT energy harvesters, devoid of frictional contact or gears. The primary objective of this study is to develop an optimal BWT design for maximizing energy output. Specifically, this study delves into optimizing the energy performance of these VIV wind energy harvesters, investigating how the geometry (shape and roughness) influences their operating range, known as Lock-In range. The results demonstrate how variations in geometry (convergent, straight, or divergent) can shift the Lock-In range to different Reynolds numbers (Re), modelled by the equation: Re (max Lock-In) = 0.30 α + 4.06. Furthermore, this study highlights the minimal impact of roughness within the considered test conditions. Full article

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2022

Jump to: 2024, 2021, 2020

21 pages, 6018 KiB

Open AccessArticle

Detection of Wind Turbine Failures through Cross-Information between Neighbouring Turbines

by Pere Marti-Puig, Jordi Cusidó, Francisco J. Lozano, Moises Serra-Serra, Cesar F. Caiafa and Jordi Solé-Casals

Appl. Sci. 2022, 12(19), 9491; https://doi.org/10.3390/app12199491 - 22 Sep 2022

Cited by 5 | Viewed by 1827

Abstract

In this paper, the time variation of signals from several SCADA systems of geographically closed turbines are analysed and compared. When operating correctly, they show a clear pattern of joint variation. However, the presence of a failure in one of the turbines causes [...] Read more.

In this paper, the time variation of signals from several SCADA systems of geographically closed turbines are analysed and compared. When operating correctly, they show a clear pattern of joint variation. However, the presence of a failure in one of the turbines causes the signals from the faulty turbine to decouple from the pattern. From this information, SCADA data is used to determine, firstly, how to derive reference signals describing this pattern and, secondly, to compare the evolution of different turbines with respect to this joint variation. This makes it possible to determine whether the behaviour of the assembly is correct, because they maintain the well-functioning patterns, or whether they are decoupled. The presented strategy is very effective and can provide important support for decision making in turbine maintenance and, in the near future, to improve the classification of signals for training supervised normality models. In addition to being a very effective system, it is a low computational cost strategy, which can add great value to the SCADA data systems present in wind farms. Full article

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2021

Jump to: 2024, 2022, 2020

23 pages, 7311 KiB

Open AccessArticle

Proposal and Performance Study of a Novel Mooring System with Six Mooring Lines for Spar-Type Offshore Wind Turbines

by Shi Liu, Yi Yang, Chao Wang and Yuangang Tu

Appl. Sci. 2021, 11(24), 11665; https://doi.org/10.3390/app112411665 - 9 Dec 2021

Cited by 3 | Viewed by 1971

Abstract

Spar-type floating offshore wind turbines commonly vibrate excessively when under the coupling impact of wind and wave. The wind turbine vibration can be controlled by developing its mooring system. Thus, this study proposes a novel mooring system for the spar-type floating offshore wind [...] Read more.

Spar-type floating offshore wind turbines commonly vibrate excessively when under the coupling impact of wind and wave. The wind turbine vibration can be controlled by developing its mooring system. Thus, this study proposes a novel mooring system for the spar-type floating offshore wind turbine. The proposed mooring system has six mooring lines, which are divided into three groups, with two mooring lines in the same group being connected to the same fairlead. Subsequently, the effects of the included angle between the two mooring lines on the mooring-system’s performance are investigated. Then, these six mooring lines are connected to six independent fairleads for comparison. FAST is utilized to calculate wind turbine dynamic response. Wind turbine surge, pitch, and yaw movements are presented and analyzed in time and frequency domains to quantitatively evaluate the performances of the proposed mooring systems. Compared with the mooring system with six fairleads, the mooring system with three fairleads performed better. When the included angle was 40°, surge, pitch, and yaw movement amplitudes of the wind turbine reduced by 39.51%, 6.8%, and 12.34%, respectively, when under regular waves; they reduced by 56.08%, 25.00%, and 47.5%, respectively, when under irregular waves. Thus, the mooring system with three fairleads and 40° included angle is recommended. Full article

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14 pages, 2957 KiB

Open AccessArticle

Design Study of Multi-Rotor and Multi-Generator Wind Turbine with Lattice Tower—A Mechatronic Approach

by Urs Giger, Stefan Kleinhansl and Horst Schulte

Appl. Sci. 2021, 11(22), 11043; https://doi.org/10.3390/app112211043 - 22 Nov 2021

Cited by 7 | Viewed by 6703

Abstract

New locations for onshore technology, which have not been considered so far, must be developed to increase the total installed capacity of renewable energies, especially wind energy. For this purpose, cost-effective wind turbines, even in difficult-to-access locations, such as mountainous and high-mountainous areas, [...] Read more.

New locations for onshore technology, which have not been considered so far, must be developed to increase the total installed capacity of renewable energies, especially wind energy. For this purpose, cost-effective wind turbines, even in difficult-to-access locations, such as mountainous and high-mountainous areas, must be designed. This paper presents a novel wind turbine with a related control system that meets these requirements. The proposed turbine uses a multi-rotor configuration with five rotors arranged in a star shape configuration. Each rotor drive train combines up to 12 generators in a maintenance-friendly multi-generator concept. A suitable observer-based control for load mitigation in the full-load region is proposed for the multi-rotor and multi-generator design. Simulations are used to demonstrate the applicability and practical benefits of this concept. Full article

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20 pages, 1347 KiB

Open AccessArticle

Design Options to Improve the Dynamic Behavior and the Control of Small H-Darrieus VAWTs

by Lorenzo Battisti

Appl. Sci. 2021, 11(19), 9222; https://doi.org/10.3390/app11199222 - 3 Oct 2021

Cited by 3 | Viewed by 2349

Abstract

H-VAWTs or straight blades VAWTs are the most common turbine architecture employed for small VAWTs. The manufacture of straight, constant chord blades, coupled with the transport advantages, make this choice technologically simpler, compared to curved (eggbeater) type or curved-bent (Gorlov) type, allowing a [...] Read more.

H-VAWTs or straight blades VAWTs are the most common turbine architecture employed for small VAWTs. The manufacture of straight, constant chord blades, coupled with the transport advantages, make this choice technologically simpler, compared to curved (eggbeater) type or curved-bent (Gorlov) type, allowing a large selection of materials, and design solutions. Recently, the strategies to accomplish the task of zero-emission buildings identified wind energy exploitation in the urban environment as one of the most promising. Micro and mini wind turbines installed on buildings (BAWT—building-augmented wind turbines) are considered the candidate technology after that of photovoltaic panels; under certain conditions, these technologies can be combined to obtain the maximum natural resources exploitation in the urban environment. VAWT, compared to HAWT, would ideally perform better in the fast-changing, turbulent winds, typical of the built environment. Additionally, its 3D shape favors a better architectonic integration with the volumes of the building. Nevertheless, despite these claimed advantages, this architecture did still not come to the expected fruition and experience, which revealed that the stochastic nature of the wind resource in the built environment determines a quite challenging context, reflecting not only the structural endurance, but also the operations and the annual energy production. These site characteristics stress the detrimental effect of the high polar inertia of this architecture hampering, be it a reduction in the acceleration and deceleration capability of the rotor, the required adaptation of the rotational speed to the varying wind conditions, or compromising any form of robust control. This leads to poor aerodynamic performance and potential structural damages. This paper contributes to mitigating the issue of the high rotor polar inertia of the H-VAWT without affecting other essential design requirements (strength, performances, needs of smooth control). The work identifies the design parameters governing the rotor acceleration and deceleration and develops a rational design procedure aimed at improving the H-VAWT control and performance. Full article

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18 pages, 4054 KiB

Open AccessArticle

Thermographic Stall Detection by Model-Inspired Evaluation of the Dynamic Temperature Behaviour

by Felix Oehme, Janick Suhr, Nicholas Balaresque, Daniel Gleichauf, Michael Sorg and Andreas Fischer

Appl. Sci. 2021, 11(18), 8442; https://doi.org/10.3390/app11188442 - 11 Sep 2021

Cited by 4 | Viewed by 1647

Abstract

Model-inspired signal processing approaches with an enhanced detectability of flow separation on thermographic images are presented. Flow separation causes performance loss, structural loads and increasing acoustic emissions on wind turbine rotor blades. However, due to the low thermal contrast between turbulent and separated [...] Read more.

Model-inspired signal processing approaches with an enhanced detectability of flow separation on thermographic images are presented. Flow separation causes performance loss, structural loads and increasing acoustic emissions on wind turbine rotor blades. However, due to the low thermal contrast between turbulent and separated flow regions, the non-invasive thermographic visualisation of flow separation is currently only possible for wind tunnel measurements, which are characterised by a high thermal contrast and a small measuring distance. The state-of-the-art signal processing approaches evaluate the surface temperature fluctuation of thermographic image series. However, understanding of the signal measurement chain with a distinct consideration of the influences on the dynamic surface temperature is incomplete. Therefore, designing model-inspired signal processing approaches which provide a high interpretability and a maximum contrast is an open task. The proposed signal processing approaches evaluate the surface response selectively, by using the amplitude information of the surface temperature response to an oscillating input signal or gradient-based for a transient input signal. The approaches are applied to wind tunnel measurements on a rotor blade profile at a near thermodynamic steady state and a transient thermodynamic behaviour at Reynolds numbers that are representative for operational wind turbines. The gradient-based evaluation shows an improved contrast for the detection of flow separation, but is only applicable to profiles with transient thermodynamic behaviour. The amplitude evaluation provides a high degree of interpretability of the processed images based on flow-dependent features and enables for an unambiguous identification of flow separation by a global amplitude minimum close to the separation point. Additionally, an increased spatial resolution for surface modifications is shown, while the contrast between flow regions is significantly decreased. Hence, the proposed approaches allow for an improved identifiability of flow separation with regard to future applications on wind turbines in operation. Full article

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17 pages, 4051 KiB

Open AccessArticle

Systematic Analysis of Wind Resources for Eolic Potential in Bangladesh

by Mariam Hussain and Seon Ki Park

Appl. Sci. 2021, 11(17), 7924; https://doi.org/10.3390/app11177924 - 27 Aug 2021

Cited by 8 | Viewed by 3099

Abstract

Energy consumption in Bangladesh increased for economic, industrial, and digitalization growth. Reductions in conventional sources such as natural gas (54%) and coal (5.6%) are calls to enhance renewable resources. This paper aims to investigate the atmospheric variables for potential wind zones and develop [...] Read more.

Energy consumption in Bangladesh increased for economic, industrial, and digitalization growth. Reductions in conventional sources such as natural gas (54%) and coal (5.6%) are calls to enhance renewable resources. This paper aims to investigate the atmospheric variables for potential wind zones and develop a statistical power-forecasting model. The study-site is Bangladesh, focusing on eight divisions across two regions. First, the southern zone includes Dhaka (Capital), Chittagong, Barishal, and Khulna. The northern regions are Rajshahi, Rangpur, Mymensingh, and Sylhet. This investigation illustrates wind (m/s) speeds at various heights (m) and analyzes the boundary layer height (BLH) from the European Center for Medium Range Weather Forecast reanalysis 5th generation (ERA5). The data is from a period of 40 years from 1979 to 2018, assessing with a climatic base of 20 years (1979 to 2000). The climatological analysis comprises trends, time series, anomalies, and linear correlations. The results for the wind speed (BLH) indicate that the weakest (lower) and strongest (higher) regions are Sylhet and Barishal, respectively. Based on power-curve relationships, a simple power predictive model (SPPM) is developed using global wind atlas (GWA) data (sample: 1100) to estimate the power density (W/m²) and found an accuracy of 0.918 and 0.892 for Exponential (EXP) and Polynomial (PN) with mean absolute percentage errors (MAPE) of 22.92 and 21.8%, respectively. For validation, SPPM also forecasts power incorporating historical observations for Chittagong and obtains correlations of 0.970 and 0.974 for EXP and PN with a MAPE of 10.26 and 7.69% individually. Furthermore, calculations for annual energy production reveal an average megawattage of 1748 and 1070 in the southern and northern regions, with an MAPE of 15.71 and 5.85% for EXP and PN models, except Sylhet. The SPPM’s predictability can be improved with observed wind speeds and turbine types. The research wishes to apply SPPM for estimating energy in operational power plants. Full article

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30 pages, 2451 KiB

Open AccessFeature PaperArticle

Formulation, Validation, and Application of a Novel 3D BEM Tool for Vertical Axis Wind Turbines of General Shape and Size

by Andrea G. Sanvito, Vincenzo Dossena and Giacomo Persico

Appl. Sci. 2021, 11(13), 5874; https://doi.org/10.3390/app11135874 - 24 Jun 2021

Cited by 8 | Viewed by 3388

Abstract

Low order models based on the Blade Element Momentum (BEM) theory exhibit modeling issues in the performance prediction of Vertical Axis Wind Turbines (VAWT) compared to Computational Fluid Dynamics, despite the widespread engineering practice of such methods. The present study shows that the [...] Read more.

Low order models based on the Blade Element Momentum (BEM) theory exhibit modeling issues in the performance prediction of Vertical Axis Wind Turbines (VAWT) compared to Computational Fluid Dynamics, despite the widespread engineering practice of such methods. The present study shows that the capability of BEM codes applied to VAWTs can be greatly improved by implementing a novel three-dimensional set of high-order corrections and demonstrates this by comparing the BEM predictions against wind-tunnel experiments conducted on three small-scale VAWT models featuring different rotor design (H-shaped and Troposkein), blade profile (NACA0021 and DU-06-W200), and Reynolds number (from

0.8 \times 10^{5}

to

2.5 \times 10^{5}

). Though based on the conventional Double Multiple Stream Tube (DMST) model, the here-presented in-house BEM code incorporates several two-dimensional and three-dimensional corrections including: accurate extended polar data, flow curvature, dynamic stall, a spanwise-distributed formulation of the tip losses, a fully 3D approach in the modeling of rotors featuring general shape (such as but not only, the Troposkein one), and accounting for the passive effects of supporting struts and pole. The detailed comparison with experimental data of the same models, tested in the large-scale wind tunnel of the Politecnico di Milano, suggests the very good predictive capability of the code in terms of power exchange, torque coefficient, and loads, on both time-mean and time-resolved basis. The peculiar formulation of the code allows including in a straightforward way the usual spanwise non-uniformity of the incoming wind and the effects of skew, thus allowing predicting the turbine operation in a realistic open-field in presence of the environmental boundary layer. A systematic study on the operation of VAWTs in multiple environments, such as in coastal regions or off-shore, and highlighting the sensitivity of VAWT performance to blade profile selection, rotor shape and size, wind shear, and rotor tilt concludes the paper. Full article

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15 pages, 4635 KiB

Open AccessArticle

The Effect of Wind Energy on Microclimate: Lessons Learnt from a CFD Modelling Approach in the Case Study of Chios Island

by Nikolaos Stergiannis, George Caralis, Jeroen van Beeck and Mark C. Runacres

Appl. Sci. 2021, 11(13), 5873; https://doi.org/10.3390/app11135873 - 24 Jun 2021

Cited by 2 | Viewed by 3294

Abstract

During the last three decades, rapid growth of wind energy has led to questions regarding the possible impacts of wind farms on local weather and microclimates. Physically, the increased turbulence due to the wind turbine operation affects the mixing processes, may slightly disturb [...] Read more.

During the last three decades, rapid growth of wind energy has led to questions regarding the possible impacts of wind farms on local weather and microclimates. Physically, the increased turbulence due to the wind turbine operation affects the mixing processes, may slightly disturb the pressure and temperature distributions downstream of wind farms and may have an impact on natural ecosystems such as the famous mastic tree population located on the island of Chios in the North Aegean Sea. This study explores the wind farms and their wake effects downstream with a particular focus on the effect on the southern part of the island where the mastic trees cultivation is located. The analysis is carried out with the use of the commercial CFD code ANSYS Fluent. Steady state computations of full 3D Navier–Stokes equations, using the k-ε turbulence closure scheme are carried out. The development of the multiple wake effects of the wind farms and their propagation downstream is examined under low and high turbulence intensities. Results clearly indicate that for both test cases there is no impact to the local microclimate and to the mastic Tree population. Full article

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22 pages, 1473 KiB

Open AccessArticle

Laminar-Turbulent Transition Localization in Thermographic Flow Visualization by Means of Principal Component Analysis

by Daniel Gleichauf, Felix Oehme, Michael Sorg and Andreas Fischer

Appl. Sci. 2021, 11(12), 5471; https://doi.org/10.3390/app11125471 - 12 Jun 2021

Cited by 9 | Viewed by 3234

Abstract

Thermographic flow visualization is a contactless, non-invasive technique to visualize the boundary layer flow on wind turbine rotor blades, to assess the aerodynamic condition and consequently the efficiency of the entire wind turbine. In applications on wind turbines in operation, the distinguishability between [...] Read more.

Thermographic flow visualization is a contactless, non-invasive technique to visualize the boundary layer flow on wind turbine rotor blades, to assess the aerodynamic condition and consequently the efficiency of the entire wind turbine. In applications on wind turbines in operation, the distinguishability between the laminar and turbulent flow regime cannot be easily increased artificially and solely depends on the energy input from the sun. State-of-the-art image processing methods are able to increase the contrast slightly but are not able to reduce systematic gradients in the image or need excessive a priori knowledge. In order to cope with a low-contrast measurement condition and to increase the distinguishability between the flow regimes, an enhanced image processing by means of the feature extraction method, principal component analysis, is introduced. The image processing is applied to an image series of thermographic flow visualizations of a steady flow situation in a wind tunnel experiment on a cylinder and DU96W180 airfoil measurement object without artificially increasing the thermal contrast between the flow regimes. The resulting feature images, based on the temporal temperature fluctuations in the images, are evaluated with regard to the global distinguishability between the laminar and turbulent flow regime as well as the achievable measurement error of an automatic localization of the local flow transition between the flow regimes. By applying the principal component analysis, systematic temperature gradients within the flow regimes as well as image artefacts such as reflections are reduced, leading to an increased contrast-to-noise ratio by a factor of 7.5. Additionally, the gradient between the laminar and turbulent flow regime is increased, leading to a minimal measurement error of the laminar-turbulent transition localization. The systematic error was reduced by 4% and the random error by 5.3% of the chord length. As a result, the principal component analysis is proven to be a valuable complementary tool to the classical image processing method in flow visualizations. After noise-reducing methods such as the temporal averaging and subsequent assessment of the spatial expansion of the boundary layer flow surface, the PCA is able to increase the laminar-turbulent flow regime distinguishability and reduce the systematic and random error of the flow transition localization in applications where no artificial increase in the contrast is possible. The enhancement of contrast increases the independence from the amount of solar energy input required for a flow evaluation, and the reduced errors of the flow transition localization enables a more precise assessment of the aerodynamic condition of the rotor blade. Full article

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9 pages, 2870 KiB

Open AccessArticle

Application of Long-Short-Term-Memory Recurrent Neural Networks to Forecast Wind Speed

by Meftah Elsaraiti and Adel Merabet

Appl. Sci. 2021, 11(5), 2387; https://doi.org/10.3390/app11052387 - 8 Mar 2021

Cited by 39 | Viewed by 3537

Abstract

Forecasting wind speed is one of the most important and challenging problems in the wind power prediction for electricity generation. Long short-term memory was used as a solution to short-term memory to address the problem of the disappearance or explosion of gradient information [...] Read more.

Forecasting wind speed is one of the most important and challenging problems in the wind power prediction for electricity generation. Long short-term memory was used as a solution to short-term memory to address the problem of the disappearance or explosion of gradient information during the training process experienced by the recurrent neural network (RNN) when used to study time series. In this study, this problem is addressed by proposing a prediction model based on long short-term memory and a deep neural network developed to forecast the wind speed values of multiple time steps in the future. The weather database in Halifax, Canada was used as a source for two series of wind speeds per hour. Two different seasons spring (March 2015) and summer (July 2015) were used for training and testing the forecasting model. The results showed that the use of the proposed model can effectively improve the accuracy of wind speed prediction. Full article

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17 pages, 4865 KiB

Open AccessFeature PaperArticle

Assessment of a Spalart–Allmaras Model Coupled with Local Correlation Based Transition Approaches for Wind Turbine Airfoils

by Valerio D’Alessandro, Sergio Montelpare and Renato Ricci

Appl. Sci. 2021, 11(4), 1872; https://doi.org/10.3390/app11041872 - 20 Feb 2021

Cited by 4 | Viewed by 2595

Abstract

This paper present recent advances in the development of local correlation based laminar–to–turbulent transition modeling relying on the Spalart–Allmaras equation. Such models are extremely important for the flow regimes involved in wind energy applications. Indeed, fully turbulent flow models are not completely reliable [...] Read more.

This paper present recent advances in the development of local correlation based laminar–to–turbulent transition modeling relying on the Spalart–Allmaras equation. Such models are extremely important for the flow regimes involved in wind energy applications. Indeed, fully turbulent flow models are not completely reliable to predict the aerodynamic force coefficients. This is particularly significant for the wind turbine blade sections. In this paper, we focus our attention on two different transitional flow models for Reynolds–Averaged Navier–Stokes (RANS) equations. It is worth noting that this is a crucial aspect because standard RANS models assume a fully turbulent regime. Thus, our approaches couple the well–known

γ

– technique and

log γ

equation with the Spalart–Allmaras turbulence model in order to overcome the common drawbacks of standard techniques. The effectiveness, efficiency, and robustness of the above-mentioned methods are tested and discussed by computing several flow fields developing around airfoils operating at Reynolds numbers typical of wind turbine blade sections. Full article

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2020

Jump to: 2024, 2022, 2021

19 pages, 1833 KiB

Open AccessArticle

Floating Offshore Wind Farms in Italy beyond 2030 and beyond 2060: Preliminary Results of a Techno-Economic Assessment

by Laura Serri, Lisa Colle, Bruno Vitali and Tullia Bonomi

Appl. Sci. 2020, 10(24), 8899; https://doi.org/10.3390/app10248899 - 13 Dec 2020

Cited by 19 | Viewed by 6106

Abstract

At the end of 2019, 10.5 GW of wind capacity was installed in Italy, all onshore. The National Integrated Climate and Energy Plan sets a target of 18.4 GW of onshore wind capacity and 0.9 GW of offshore wind capacity by 2030. Significant [...] Read more.

At the end of 2019, 10.5 GW of wind capacity was installed in Italy, all onshore. The National Integrated Climate and Energy Plan sets a target of 18.4 GW of onshore wind capacity and 0.9 GW of offshore wind capacity by 2030. Significant exploitation of offshore wind resources in Italy is expected after 2030, using floating wind turbines, suitable for water depths greater than 50 m. This technology is at the demonstration phase at present. Results of a preliminary techno-economic assessment of floating wind plants in Italian marine areas in a medium (2030) and long-term (2060) scenario are presented. In 2030, a reference park with 10 MW wind turbines will be defined, and parametric costs, depending on distance from shore, were assessed. In 2060, possible wind resource variations due to climate change, and cost reductions due to large diffusion of the technology were considered in three case studies. The economic model used was the simple Levelized Cost of Energy (sLCoE). Different values of Weighted Average Cost of Capital (WACC) were considered too. The results show LCoEs comparable to the ones expected for the sector in 2030. In 2060, even in the more pessimistic scenario, wind resource decreases will be abundantly compensated by expected cost reductions. Full article

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19 pages, 5404 KiB

Open AccessFeature PaperArticle

Assessment of Hybrid Wind-Wave Energy Resource for the NW Coast of Iberian Peninsula in a Climate Change Context

by Americo Ribeiro, Xurxo Costoya, Maite de Castro, David Carvalho, Joao Miguel Dias, Alfredo Rocha and Moncho Gomez-Gesteira

Appl. Sci. 2020, 10(21), 7395; https://doi.org/10.3390/app10217395 - 22 Oct 2020

Cited by 23 | Viewed by 3682

Abstract

Offshore renewable energy has a high potential for ensuring the successful implementation of the European decarbonization agenda planned for the near future. Hybrid wind-wave farms can reduce installation and maintenance costs, and increase the renewable energy availability of a location by compensating for [...] Read more.

Offshore renewable energy has a high potential for ensuring the successful implementation of the European decarbonization agenda planned for the near future. Hybrid wind-wave farms can reduce installation and maintenance costs, and increase the renewable energy availability of a location by compensating for the wind’s intermittent nature with good wave conditions. In addition, wave farms can provide protection to wind farms, and the combined wind/wave farm can provide coastal protection. This work aims to assess the future hybrid wind-wave energy resource for the northwest coast of Iberian Peninsula for the near future (2026–2045), under the RCP 8.5 greenhouse gas emission scenario. This assessment was accomplished by applying a Delphi classification method to define four categories, aiming to evaluate the richness (wind and wave energy availability, downtime), the variability (temporal variation), the environmental risk (extreme events), and cost parameters (water depth and distance to coast) of the wind and wave resources. The combined index (CI), which classifies the hybrid wind-wave resource, shows that most of the NW Iberian Peninsula presents good conditions (CI > 0.6) for exploiting energy from wind and wave resources simultaneously. Additionally, there are some particularly optimal areas (CI > 0.7), such as the region near Cape Roca, and the Galician coast. Full article

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21 pages, 6954 KiB

Open AccessArticle

Contactless Localization of Premature Laminar–Turbulent Flow Transitions on Wind Turbine Rotor Blades in Operation

by Daniel Gleichauf, Michael Sorg and Andreas Fischer

Appl. Sci. 2020, 10(18), 6552; https://doi.org/10.3390/app10186552 - 19 Sep 2020

Cited by 5 | Viewed by 3235

Abstract

Thermographic flow visualization enables a noninvasive detection of the laminar–turbulent flow transition and allows a measurement of the impact of surface erosion and contamination due to insects, rain, dust, or hail by quantifying the amount of laminar flow reduction. The state-of-the-art image processing [...] Read more.

Thermographic flow visualization enables a noninvasive detection of the laminar–turbulent flow transition and allows a measurement of the impact of surface erosion and contamination due to insects, rain, dust, or hail by quantifying the amount of laminar flow reduction. The state-of-the-art image processing is designed to localize the natural flow transition as occurring on an undisturbed blade surface by use of a one-dimensional gradient evaluation. However, the occurrence of premature flow transitions leads to a high measurement uncertainty of the localized transition line or to a completely missed flow transition detection. For this reason, regions with turbulent flow are incorrectly assigned to the laminar flow region, which leads to a systematic deviation in the subsequent quantification of the spatial distribution of the boundary layer flow regimes. Therefore, a novel image processing method for the localization of the laminar–turbulent flow transition is introduced, which provides a reduced measurement uncertainty for sections with premature flow transitions. By the use of a two-dimensional image evaluation, local maximal temperature gradients are identified in order to locate the flow transition with a reduced uncertainty compared to the state-of-the-art method. The transition position can be used to quantify the reduction of the laminar flow regime surface area due to occurrences of premature flow transitions in order to measure the influence of surface contamination on the boundary layer flow. The image processing is applied to the thermographic measurement on a wind turbine of the type GE 1.5 sl in operation. In 11 blade segments with occurring premature flow transitions and a high enough contrast of the developed turbulence wedge, the introduced evaluation was able to locate the flow transition line correctly. The laminar flow reduction based on the evaluated flow transition position located with a significantly reduced systematic deviation amounts to

22 %

for the given measurement and can be used to estimate the reduction of the aerodynamic lift. Therefore, the image processing method introduced allows a more accurate estimation of the effects of real environmental conditions on the efficiency of wind turbines in operation. Full article

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