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Dr. Galih Bangga

E-Mail Website1 Website2

Institute of Aerodynamics and Gas Dynamics, University of Stuttgart, 70569 Stuttgart, Germany

Dr. Martin Otto Laver Hansen

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Department of Wind Energy, Technical University of Denmark, DK2800 Lyngby, Denmark

Advances in Wind Energy Technology

Abstract submission deadline

closed (31 October 2023)

Manuscript submission deadline

closed (31 December 2024)

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101480

Topic Information

Dear Colleagues,

The popularity of wind energy has increased considerably in recent decades due to the awareness of clean energy sources and the motivation to minimize the effects of global warming. This raises challenges in the continuous and consistent development of wind turbine technology, ranging from blade design, more-efficient logistics, and maintenance to measurement and numerical tools being used for the holistic evaluation of wind turbine performance. We are inviting submissions for a Topic that addresses research, development, and industrial implementations as well as the point of view of the following fields, but not limited to them:

Large wind turbines;
Innovative wind turbine aerodynamic and structural designs;
Nonconventional wind turbine technology;
Wind turbine and wind farm control;
Grid and system integration;
The development of advanced measurement systems;
Improved numerical prediction tools for wind energy analysis;
Improved wind turbine maintenance, scheduling, lifetime assessment and health monitoring;
Multidisciplinary approaches in wind energy socio-eco-technical aspects;
Usage of data-driven approaches.

Dr. Galih Bangga
Prof. Dr. Martin Otto Laver Hansen
Topic Editors

Keywords

renewable energy
power generation
economic growth
energy potential
electrical and mechanical systems
health monitoring and lifetime assessment
signal and image processing
fault diagnosis
wind turbine modeling

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Applied Sciences applsci	2.5	5.3	2011	18.4 Days	CHF 2400
Clean Technologies cleantechnol	4.1	6.1	2019	33.5 Days	CHF 1600
Energies energies	3.0	6.2	2008	16.8 Days	CHF 2600
Journal of Marine Science and Engineering jmse	2.7	4.4	2013	16.4 Days	CHF 2600
Wind wind	-	-	2021	35.7 Days	CHF 1000

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Advances in Wind Energy Technology: 2nd Edition

Published Papers (40 papers)

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18 pages, 3648 KiB

Open AccessArticle

Pre-Filtering SCADA Data for Enhanced Machine Learning-Based Multivariate Power Estimation in Wind Turbines

by Bubin Wang, Bin Zhou, Denghao Zhu, Mingheng Zou and Haoxuan Luo

J. Mar. Sci. Eng. 2025, 13(3), 410; https://doi.org/10.3390/jmse13030410 - 22 Feb 2025

Viewed by 558

Data generated during the shutdown or start-up processes of wind turbines, particularly in complex wind conditions such as offshore environments, often accumulate in the low-wind-speed region, leading to reduced multivariate power estimation accuracy. Therefore, developing efficient filtering methods is crucial to improving data [...] Read more.

Data generated during the shutdown or start-up processes of wind turbines, particularly in complex wind conditions such as offshore environments, often accumulate in the low-wind-speed region, leading to reduced multivariate power estimation accuracy. Therefore, developing efficient filtering methods is crucial to improving data quality and model performance. This paper proposes a novel filtering method that integrates the control strategies of variable-speed, variable-pitch wind turbines, such as maximum-power point tracking (MPPT) and pitch angle control, with statistical distribution characteristics derived from supervisory control and data acquisition (SCADA). First, thresholds for pitch angle and rotor speed are determined based on SCADA data distribution, and the filtering effect is visualized. Subsequently, a sliding window technique is employed for the secondary confirmation of potential outliers, enabling further anomaly detection (AD). Finally, the performance of the power estimation model is validated using two wind turbine datasets and two machine learning algorithms, with results compared with and without filtering. The results demonstrate that the proposed filtering method significantly enhances the accuracy of multivariate power estimation, proving its effectiveness in improving data quality for wind turbines operating in diverse and complex environments. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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27 pages, 6011 KiB

Open AccessArticle

Sensitivity of Dynamic Stall Models to Dynamic Excitation on Large Flexible Wind Turbine Blades in Edgewise Vibrations

by Galih Bangga

Energies 2025, 18(3), 470; https://doi.org/10.3390/en18030470 - 21 Jan 2025

Viewed by 739

Present studies are specifically aimed at investigating the sensitivity of different dynamic stall models when exposed to various excitation frequencies. The investigations are targeted at blade edgewise vibrations. This is carried out on a modified version of the IEA 15 MW reference wind [...] Read more.

Present studies are specifically aimed at investigating the sensitivity of different dynamic stall models when exposed to various excitation frequencies. The investigations are targeted at blade edgewise vibrations. This is carried out on a modified version of the IEA 15 MW reference wind turbine employing a wind turbine design tool, DNV Bladed. State-of-the-art dynamic stall models for wind turbine applications, such as the Øye model, Beddoes–Leishman (BL) model and the newly developed IAG model, are evaluated. The beginning of the research work starts by evaluating different dynamic stall models on rigid blade section forces against known airfoil datasets. Then, the blade flexibility is considered to enable systematic evaluations of the blade flexibility influences in comparison to the rigid blade cases. It is observed that the range of the angle of attack grows depending on the excitation frequency and the adopted dynamic stall model. The critical excitation frequency range and the effects of twist distribution are then identified from the studies, which can be useful as a rough guidance when designing wind turbine blades. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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18 pages, 4755 KiB

Open AccessArticle

Parametric Analysis of Control Techniques for 15 MW Semi-Submersible Floating Wind Turbine

by Taesu Jeon, Byung-Soo Kim, Jaecheon Kim, Insu Paek and Chang-Hyuck Lim

Appl. Sci. 2025, 15(2), 519; https://doi.org/10.3390/app15020519 - 8 Jan 2025

Cited by 1 | Viewed by 930

In this study, a composite control algorithm based on classical control methods is developed to achieve all control objectives, such as power production, load reduction, and motion reduction, for the floating wind turbine. In previous studies, peak shaving and nacelle feedback were used [...] Read more.

In this study, a composite control algorithm based on classical control methods is developed to achieve all control objectives, such as power production, load reduction, and motion reduction, for the floating wind turbine. In previous studies, peak shaving and nacelle feedback were used together to reduce both platform motion and the tower-base loads of floating wind turbines. The new approach presented in this study not only addresses the platform motion and tower loads but also aims to mitigate the rotor speed fluctuations and the blade loads by additionally introducing feedforward control and individual pitch control. This expansion enhances the applicability and control performance of classical control algorithms. To achieve this, parametric simulations were conducted using OpenFAST to assess the effects of control parameter variations for each control technique. The simulation results showed that the proposed control algorithm significantly reduced the rotor speed fluctuations, tower loads, blade loads, and platform motion compared with the baseline controller. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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17 pages, 4729 KiB

Open AccessArticle

Performance Validation of Control Algorithm Considering Independent Generator Torque Control in PCS

by Dongmyoung Kim, Min-Woo Ham, Insu Paek, Wirachai Roynarin and Amphol Aphathanakorn

Appl. Sci. 2024, 14(24), 11598; https://doi.org/10.3390/app142411598 - 12 Dec 2024

Viewed by 701

This study designed and validated a power control algorithm tailored to the unique characteristics of a 100 kW wind turbine equipped with an independent generator torque control system within the Power Conversion System (PCS). Unlike conventional power control methods based on the Programmable [...] Read more.

This study designed and validated a power control algorithm tailored to the unique characteristics of a 100 kW wind turbine equipped with an independent generator torque control system within the Power Conversion System (PCS). Unlike conventional power control methods based on the Programmable Logic Controller (PLC), the independent generator torque control in the PCS estimates the generator speed based on the voltage signal and performs the generator torque control without any interference from the PLC. The conventional power control algorithm in the PLC was modified so that the PLC could perform the power control by the blade pitch control only. Furthermore, a mode transition algorithm was designed to improve the shortcomings of the mode switch previously used for transitioning between the torque and pitch control modes. To verify the performance, a simulation environment similar to actual control conditions was established using a commercial analysis program, and dynamic simulations were conducted. Additionally, for the experimental validation, the proposed control algorithm was applied to a scaled wind turbine, and wind tunnel tests were performed. The results of the simulations and wind tunnel tests confirmed the operational performance of the PCS’s torque control and the improved control transition logic. The proposed control algorithm could be specifically applied to medium-sized wind turbines employing a sensorless generator speed estimation method and independent generator torque control in the PCS. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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22 pages, 5486 KiB

Open AccessArticle

Control of Large Wind Energy Converters for Aeroacoustic Noise Mitigation with Minimal Power Reduction

by Andrea Rivarola and Adrian Gambier

Energies 2024, 17(22), 5530; https://doi.org/10.3390/en17225530 - 5 Nov 2024

Viewed by 730

The population is often opposed to wind turbines being erected near their homes, mainly because the machines are noisy, especially at night. In an effort to establish a compromise between the needs of the people and the fulfilment of energy demands, wind turbines [...] Read more.

The population is often opposed to wind turbines being erected near their homes, mainly because the machines are noisy, especially at night. In an effort to establish a compromise between the needs of the people and the fulfilment of energy demands, wind turbines have the ability to switch between day and night operation by reducing the rotation speed during the night, resulting in a loss of generated power. The present study investigates simple models for noise emission, propagation, and prediction, with the objective of proposing a control system configuration that continuously adjusts the rotational speed as much as necessary until it matches sound level regulations while minimising power losses. Thus, several approaches are implemented and tested with a very large reference wind turbine. The simulation results of a reference wind turbine show that the approaches provide significant improvements in sound reduction as well as in power conversion. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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14 pages, 4214 KiB

Open AccessArticle

Numerical Investigation of Burial Depth Effects on Tension of Submarine Power Cables

by Jiayi Shen, Yingjie Liang, Huabin Hong and Jiawang Chen

J. Mar. Sci. Eng. 2024, 12(11), 1972; https://doi.org/10.3390/jmse12111972 - 2 Nov 2024

Viewed by 1112

To protect submarine power cables from damage caused by anchoring and fishing, submarine power cables in shallow water areas are buried to a certain depth through a cable laying machine. However, limited attention has been paid to studying the stress behavior of submarine [...] Read more.

To protect submarine power cables from damage caused by anchoring and fishing, submarine power cables in shallow water areas are buried to a certain depth through a cable laying machine. However, limited attention has been paid to studying the stress behavior of submarine power cables while considering the effects of burial depth. In this research, static and dynamic analyses are carried out using three-dimensional numerical models performed by the OrcaFlex v11.0 to investigate the effects of burial depths on cable tension during the cable installation under various conditions. Numerical simulation results show that the peak tension of the submarine power cable increases linearly with the increase in burial depth. In addition, the burial depth can also change the tension state at the endpoint of the submarine power cable. The endpoint of the cable is in a compressed state when h < 2 m and the cable turns into a tensile state when h ≥ 2 m. Finally, genetic programming (GP) is used to analyze numerical simulation results to propose a prediction model that can be used to estimate the peak tension of the submarine power cable during cable installation under various burial depths in shallow sea areas. It should be noted that the proposed GP model is based on the analyses of numerical results; therefore, the GP model is open for further improvements as more experimental data become available. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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16 pages, 4146 KiB

Open AccessArticle

Comparison of the Wind Speed Estimation Algorithms of Wind Turbines Using a Drive Train Model and Extended Kalman Filter

by Dongmyoung Kim, Taesu Jeon, Insu Paek and Wirachai Roynarin

Appl. Sci. 2024, 14(19), 8764; https://doi.org/10.3390/app14198764 - 28 Sep 2024

Cited by 2 | Viewed by 1362

To compare and validate wind speed estimation algorithms applied to wind turbines, wind speed estimators were designed in this study, based on two methods presented in the literature, and their performance was validated using the NREL 5MW model. The first method for wind [...] Read more.

To compare and validate wind speed estimation algorithms applied to wind turbines, wind speed estimators were designed in this study, based on two methods presented in the literature, and their performance was validated using the NREL 5MW model. The first method for wind speed estimation involves a three-dimensional (3D) look-up table-based approach, constructed using drive train differential equations. The second method involves applying a continuous–discrete extended Kalman filter. To verify and compare the performance of the algorithms designed using these different methods, feed-forward control algorithms, available power estimation algorithms, and a linear quadratic regulator, based on fuzzy logic (LQRF) control algorithms, were selected and applied as verification means, using the estimated wind speed as the input. Based on the simulation results, the performance of the two methods was compared. The method using drive train differential equations demonstrated superior performance in terms of reductions in the standard deviations of rotor speed and electrical power, as well as in its prediction accuracy for the available power. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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16 pages, 3972 KiB

Open AccessArticle

Anomaly Identification of Wind Turbine Yaw System Based on Two-Stage Attention–Informer Algorithm

by Xu Shen, Haiyun Wang, Xiaofang Huang and Yang Chen

Appl. Sci. 2024, 14(19), 8746; https://doi.org/10.3390/app14198746 - 27 Sep 2024

Cited by 1 | Viewed by 1189

In response to the problems that abnormal yaw position causes during the yawing process—on the one hand leading to the accumulation of yaw position errors, affecting the accuracy of yawing to the wind or safety due to excessive cable twisting, and on the [...] Read more.

In response to the problems that abnormal yaw position causes during the yawing process—on the one hand leading to the accumulation of yaw position errors, affecting the accuracy of yawing to the wind or safety due to excessive cable twisting, and on the other hand, with the phenomena of frequent position jumps or frequent short-term position maintenance generating certain yaw errors, affecting the stability of yaw control, thus resulting in a high occurrence frequency of yaw system failures and high operation and maintenance costs—a data-driven fault diagnosis method is proposed to give early warnings for abnormal conditions of the yaw position of the wind turbine unit. Firstly, for the massive data in the SCADA (Supervisory Control and Data Acquisition) system, the ReliefF feature algorithm based on standardized interaction gain (Standardized Interaction Gain and ReliefF, SIG–ReliefF) is used for accurately identifying and screening the characteristic parameters that have a greater impact on the yaw system failure of wind turbines. The advantage of this method lies in its ability to effectively consider the correlation between features and retain the relevant features and interaction features of yaw system failures to the greatest extent. Then, an Informer yaw position prediction model is established, combined with the two-stage attention mechanism (two-stage attention and Informer, TSA–Informer), and the distribution of residuals is statistically analyzed through the sliding window method to determine the fault threshold. Finally, the validity and accuracy of the proposed method are verified through examples, and through comparison with other algorithms, it is verified that it has better abnormal early warning performance. Relevant conclusions can provide a reference for the fault diagnosis of the actual yaw system. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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20 pages, 4554 KiB

Open AccessFeature PaperArticle

Highly Stable Lattice Boltzmann Method with a 2-D Actuator Line Model for Vertical Axis Wind Turbines

by Luca Cacciali, Martin O. L. Hansen and Krzysztof Rogowski

Energies 2024, 17(19), 4847; https://doi.org/10.3390/en17194847 - 27 Sep 2024

Cited by 3 | Viewed by 1657

A 2-D Lattice Boltzmann Method, designed to ensure stability at high Reynolds numbers, is combined with an Actuator Line Model to compute the loads on a two-bladed vertical axis wind turbine. Tests on the kernel size at a high mesh resolution reveal that [...] Read more.

A 2-D Lattice Boltzmann Method, designed to ensure stability at high Reynolds numbers, is combined with an Actuator Line Model to compute the loads on a two-bladed vertical axis wind turbine. Tests on the kernel size at a high mesh resolution reveal that a size equal to half of the full chord length yields the most accurate results. The aerodynamic load solution is validated against a fully resolved Scale-Adaptive Simulation (SAS) output, demonstrating high correlation, and enabling an assessment of near wake and downstream effects. The model’s adaptability to various rotor operating conditions is confirmed through tests at high and low tip-speed ratios. Additionally, a Biot–Savart-based Vortex Model (VM) is employed for further comparison, showing good agreement with the Lattice Boltzmann output. The results indicate that the Highly Stable Lattice Boltzmann Method integrated with the Actuator Line Model enhances the accuracy of flow field resolution and effectively captures complex aerodynamic phenomena, making it a valuable tool for simulating vertical axis wind turbines. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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16 pages, 4390 KiB

Open AccessFeature PaperArticle

Wind Farm Prediction of Icing Based on SCADA Data

by Yujie Zhang, Mario Rotea and Nasser Kehtarnavaz

Energies 2024, 17(18), 4629; https://doi.org/10.3390/en17184629 - 15 Sep 2024

Cited by 1 | Viewed by 1053

In cold climates, ice formation on wind turbines causes power reduction produced by a wind farm. This paper introduces a framework to predict icing at the farm level based on our recently developed Temporal Convolutional Network prediction model for a single turbine using [...] Read more.

In cold climates, ice formation on wind turbines causes power reduction produced by a wind farm. This paper introduces a framework to predict icing at the farm level based on our recently developed Temporal Convolutional Network prediction model for a single turbine using SCADA data.First, a cross-validation study is carried out to evaluate the extent predictors trained on a single turbine of a wind farm can be used to predict icing on the other turbines of a wind farm. This fusion approach combines multiple turbines, thereby providing predictions at the wind farm level. This study shows that such a fusion approach improves prediction accuracy and decreases fluctuations across different prediction horizons when compared with single-turbine prediction. Two approaches are considered to conduct farm-level icing prediction: decision fusion and feature fusion. In decision fusion, icing prediction decisions from individual turbines are combined in a majority voting manner. In feature fusion, features of individual turbines are averaged first before conducting prediction. The results obtained indicate that both the decision fusion and feature fusion approaches generate farm-level icing prediction accuracies that are 7% higher with lower standard deviations or fluctuations across different prediction horizons when compared with predictions for a single turbine. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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24 pages, 5369 KiB

Open AccessArticle

Insights on the Optimization of Short- and Long-Term Maintenance Decisions for Floating Offshore Wind Using Nested Genetic Algorithms

by Mário Vieira and Dragan Djurdjanovic

Wind 2024, 4(3), 227-250; https://doi.org/10.3390/wind4030012 - 3 Sep 2024

Viewed by 1801

The present research explores the optimization of maintenance strategies for floating offshore wind (FOW) farms using nested genetic algorithms. The primary goal is to provide insights on the decision-making processes required for both immediate and strategic maintenance planning, crucial for the viability and [...] Read more.

The present research explores the optimization of maintenance strategies for floating offshore wind (FOW) farms using nested genetic algorithms. The primary goal is to provide insights on the decision-making processes required for both immediate and strategic maintenance planning, crucial for the viability and efficiency of FOW operations. A nested genetic algorithm was coupled with discrete-event simulations in order to simulate and optimize maintenance scenarios influenced by various operational and environmental parameters. The study revealed that short-term maintenance timing is significantly influenced by wind conditions, with higher electricity prices justifying on-site spare parts storage to mitigate operational disruptions, suggesting economic incentives for maintaining on-site inventory of spare parts. Long-term strategic findings emphasized the impact of planned intervals between inspections on financial outcomes, identifying optimal strategies that balance operational costs with energy production efficiency. Ultimately, this study highlights the importance of integrating sophisticated predictive models for failure detection with real-time operational data to enhance maintenance decision-making in the evolving landscape of offshore wind energy, where future farms are likely to operate farther from onshore facilities and under potentially highly varying market conditions in terms of electricity prices. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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17 pages, 8634 KiB

Open AccessArticle

Aerodynamic Performance and Coupling Gain Effect of Archimedes Spiral Wind Turbine Array

by Ke Song, Huiting Huan, Liuchuang Wei and Chunxia Liu

J. Mar. Sci. Eng. 2024, 12(7), 1062; https://doi.org/10.3390/jmse12071062 - 24 Jun 2024

Cited by 3 | Viewed by 2810

The Archimedes spiral wind turbine (ASWT), as a novel type of horizontal-axis wind turbine, is well suited for remote islands. To explore the aerodynamic performance and coupling gain effect of ASWT array, a three-dimensional numerical simulation was carried out using the computational fluid [...] Read more.

The Archimedes spiral wind turbine (ASWT), as a novel type of horizontal-axis wind turbine, is well suited for remote islands. To explore the aerodynamic performance and coupling gain effect of ASWT array, a three-dimensional numerical simulation was carried out using the computational fluid dynamics (CFD) method. The influence of arrangement, relative spacing, and rotation configuration on the performance of a double-unit array and triangular array is studied. The results demonstrate that, in parallel arrangements, the double unit achieve higher performance than an isolated ASWT within a specific range of parallel spacing. However, the effect of performance improvement gradually diminishes as the parallel spacing increases. In tandem arrangements, the upstream unit performance remains largely unaffected when tandem spacing exceeds 5 D, while the downstream unit’s performance declines notably with reducing tandem spacing. The downstream unit in reverse rotation configuration accrues more energy than its counterpart operating at the co-rotation configuration. In triangular arrangements, the reverse rotation configuration can achieve better performance due to the meshing effect between the wake of the upstream ASWT and the downstream ASWT. This configuration allows the array system to maintain a higher maximum power output within a smaller spacing. The research results can provide a basis and reference for designing the layout scheme of a multi-unit ASWT power station. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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21 pages, 11543 KiB

Open AccessArticle

A Multiscale Hybrid Wind Power Prediction Model Based on Least Squares Support Vector Regression–Regularized Extreme Learning Machine–Multi-Head Attention–Bidirectional Gated Recurrent Unit and Data Decomposition

by Yuan Sun and Shiyang Zhang

Energies 2024, 17(12), 2923; https://doi.org/10.3390/en17122923 - 14 Jun 2024

Cited by 4 | Viewed by 865

Ensuring the accuracy of wind power prediction is paramount for the reliable and stable operation of power systems. This study introduces a novel approach aimed at enhancing the precision of wind power prediction through the development of a multiscale hybrid model. This model [...] Read more.

Ensuring the accuracy of wind power prediction is paramount for the reliable and stable operation of power systems. This study introduces a novel approach aimed at enhancing the precision of wind power prediction through the development of a multiscale hybrid model. This model integrates advanced methodologies including Improved Intrinsic Mode Function with Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), permutation entropy (PE), Least Squares Support Vector Regression (LSSVR), Regularized Extreme Learning Machine (RELM), multi-head attention (MHA), and Bidirectional Gated Recurrent Unit (BiGRU). Firstly, the ICEEMDAN technique is employed to decompose the non-stationary raw wind power data into multiple relatively stable sub-modes, while concurrently utilizing PE to assess the complexity of each sub-mode. Secondly, the dataset is reconstituted into three distinct components as follows: high-frequency, mid-frequency, and low-frequency, to alleviate data complexity. Following this, the LSSVR, RELM, and MHA-BiGRU models are individually applied to predict the high-, mid-, and low-frequency components, respectively. Thirdly, the parameters of the low-frequency prediction model are optimized utilizing the Dung Beetle Optimizer (DBO) algorithm. Ultimately, the predicted results of each component are aggregated to derive the final prediction. The empirical findings illustrate the exceptional predictive performance of the multiscale hybrid model incorporating LSSVR, RELM, and MHA-BiGRU. In comparison with other benchmark models, the proposed model exhibits a reduction in Root Mean Squared Error (RMSE) values of over 10%, conclusively affirming its superior predictive accuracy. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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13 pages, 748 KiB

Open AccessArticle

Prediction of Icing on Wind Turbines Based on SCADA Data via Temporal Convolutional Network

by Yujie Zhang, Nasser Kehtarnavaz, Mario Rotea and Teja Dasari

Energies 2024, 17(9), 2175; https://doi.org/10.3390/en17092175 - 2 May 2024

Cited by 4 | Viewed by 1598

Icing on the blades of wind turbines during winter seasons causes a reduction in power and revenue losses. The prediction of icing before it occurs has the potential to enable mitigating actions to reduce ice accumulation. This paper presents a framework for the [...] Read more.

Icing on the blades of wind turbines during winter seasons causes a reduction in power and revenue losses. The prediction of icing before it occurs has the potential to enable mitigating actions to reduce ice accumulation. This paper presents a framework for the prediction of icing on wind turbines based on Supervisory Control and Data Acquisition (SCADA) data without requiring the installation of any additional icing sensors on the turbines. A Temporal Convolutional Network is considered as the model to predict icing from the SCADA data time series. All aspects of the icing prediction framework are described, including the necessary data preprocessing, the labeling of SCADA data for icing conditions, the selection of informative icing features or variables in SCADA data, and the design of a Temporal Convolutional Network as the prediction model. Two performance metrics to evaluate the prediction outcome are presented. Using SCADA data from an actual wind turbine, the model achieves an average prediction accuracy of

77.6 %

for future times of up to 48 h. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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14 pages, 1880 KiB

Open AccessArticle

Forecasting Pitch Response of Floating Offshore Wind Turbines with a Deep Learning Model

by Mohammad Barooni and Deniz Velioglu Sogut

Clean Technol. 2024, 6(2), 418-431; https://doi.org/10.3390/cleantechnol6020021 - 29 Mar 2024

Cited by 3 | Viewed by 2332

The design and optimization of floating offshore wind turbines (FOWTs) pose significant challenges, stemming from the complex interplay among aerodynamics, hydrodynamics, structural dynamics, and control systems. In this context, this study introduces an innovative method for forecasting the dynamic behavior of FOWTs under [...] Read more.

The design and optimization of floating offshore wind turbines (FOWTs) pose significant challenges, stemming from the complex interplay among aerodynamics, hydrodynamics, structural dynamics, and control systems. In this context, this study introduces an innovative method for forecasting the dynamic behavior of FOWTs under various conditions by merging Convolutional Neural Network (CNN) with a Gated Recurrent Unit (GRU) network. This model outperforms traditional numerical models by delivering precise and efficient predictions of dynamic FOWT responses. It adeptly handles computational complexities and reduces processing duration, while maintaining flexibility and effectively managing nonlinear dynamics. The model’s prowess is showcased through an analysis of a spar-type FOWT in a multivariate parallel time series dataset using the CNN–GRU structure. The outcomes are notably promising, underscoring the model’s proficiency in accurately forecasting the performance of FOWTs. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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21 pages, 2229 KiB

Open AccessArticle

Fault-Tolerant Controller Applied to a Wind System Using a Doubly Fed Induction Generator

by Onofre Morfín, Diego Delgado, Alan Campos, Miguel Murillo, Jesús I. Hernández and Pedro Esquivel

Wind 2024, 4(2), 90-110; https://doi.org/10.3390/wind4020005 - 22 Mar 2024

Cited by 1 | Viewed by 1455

Wind systems are sustainable and economical options for producing electrical energy. These systems efficiently manage the power flow by maximizing wind power and consuming reactive power from the grid. In addition, wind systems must maintain operation despite utility grid electrical failure; hence, their [...] Read more.

Wind systems are sustainable and economical options for producing electrical energy. These systems efficiently manage the power flow by maximizing wind power and consuming reactive power from the grid. In addition, wind systems must maintain operation despite utility grid electrical failure; hence, their control system must not collapse. This study proposes a fault-tolerant converter controller to ensure the efficient operation of wind system converters. The central concept behind this is that when there is an imbalance in the utility grid voltage due to a fault nearby or far away, positive and negative sequence voltages are created in the time domain. Then, two parallel controllers operate to allow the wind system to continue operating despite the failure. One controller utilizes positive sequence voltages as inputs to regulate the generator’s electromagnetic torque. This helps in maximizing the amount of wind energy. The second controller uses negative sequence voltages as inputs, which helps to cancel out the produced torque in the opposite direction, thereby preventing generator overload. Finally, the controllers proposed in this article are validated through simulations, and the results are presented. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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22 pages, 1036 KiB

Open AccessReview

Review of AI-Based Wind Prediction within Recent Three Years: 2021–2023

by Dongran Song, Xiao Tan, Qian Huang, Li Wang, Mi Dong, Jian Yang and Solomin Evgeny

Energies 2024, 17(6), 1270; https://doi.org/10.3390/en17061270 - 7 Mar 2024

Cited by 6 | Viewed by 3701

Wind prediction has consistently been in the spotlight as a crucial element in achieving efficient wind power generation and reducing operational costs. In recent years, with the rapid advancement of artificial intelligence (AI) technology, its application in the field of wind prediction has [...] Read more.

Wind prediction has consistently been in the spotlight as a crucial element in achieving efficient wind power generation and reducing operational costs. In recent years, with the rapid advancement of artificial intelligence (AI) technology, its application in the field of wind prediction has made significant strides. Focusing on the process of AI-based wind prediction modeling, this paper provides a comprehensive summary and discussion of key techniques and models in data preprocessing, feature extraction, relationship learning, and parameter optimization. Building upon this, three major challenges are identified in AI-based wind prediction: the uncertainty of wind data, the incompleteness of feature extraction, and the complexity of relationship learning. In response to these challenges, targeted suggestions are proposed for future research directions, aiming to promote the effective application of AI technology in the field of wind prediction and address the crucial issues therein. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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20 pages, 3967 KiB

Open AccessArticle

Analysis of Adaptive Individual Pitch Control Schemes for Blade Fatigue Load Reduction on a 15 MW Wind Turbine

by Manuel Lara, Sebastiaan Paul Mulders, Jan-Willem van Wingerden, Francisco Vázquez and Juan Garrido

Appl. Sci. 2024, 14(1), 183; https://doi.org/10.3390/app14010183 - 25 Dec 2023

Cited by 5 | Viewed by 2263

Individual pitch control (IPC) is a method to mitigate periodic blade loads in wind turbines, and it is typically implemented using the multi-blade coordinate (MBC) transform, which converts the blade load measurements from a rotating frame into the non-rotating tilt axis and yaw [...] Read more.

Individual pitch control (IPC) is a method to mitigate periodic blade loads in wind turbines, and it is typically implemented using the multi-blade coordinate (MBC) transform, which converts the blade load measurements from a rotating frame into the non-rotating tilt axis and yaw axis. Previous studies have shown that by including an additional tuning parameter in the MBC, the azimuth offset reduces the coupling between non-rotating axes, allowing for higher performance levels for diagonal controller structures. In these studies, the decentralized control of IPC was composed of two identical integral controllers. This work analyzes and compares the improvement that the azimuth offset can provide in different adaptive gain scheduling IPCs where the diagonal controllers can have integral or proportional action with different gains. They are applied to a 15 MW wind turbine simulated with OpenFAST v3.5 software. The controller parameter tuning is addressed as an optimization that reduces blade fatigue load based on the damage equivalent load (DEL) and is resolved through genetic algorithms. Simulations show that only using different controller gains in IPC does not provide significant improvements; however, including azimuth offset in the optimal IPC schemes with integral controllers allows for the greatest DEL reduction with a lower actuator effort. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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18 pages, 3930 KiB

Open AccessArticle

A Study on H_∞-Fuzzy Controller for a Non-Linear Wind Turbine with Uncertainty

by Taesu Jeon, Yuan Song and Insu Paek

Appl. Sci. 2023, 13(21), 11930; https://doi.org/10.3390/app132111930 - 31 Oct 2023

Cited by 1 | Viewed by 1481

In this study, an

H_{\infty}

-fuzzy controller is proposed for application in wind turbines with uncertainties and nonlinearities. The performance of the proposed controller was validated via dynamic simulations using a commercial aero-elastic code and wind tunnel experiments employing a scaled wind [...] Read more.

In this study, an

H_{\infty}

-fuzzy controller is proposed for application in wind turbines with uncertainties and nonlinearities. The performance of the proposed controller was validated via dynamic simulations using a commercial aero-elastic code and wind tunnel experiments employing a scaled wind turbine. The simulation and the experimental results were then compared with those of the conventional PI and LQR control algorithms presented in our previous study. In the simulation, the perturbation and the sensor noise were applied to reflect uncertainty and nonlinearity effects. In addition, in the wind tunnel experiment, a control system using a commercial Bachmann PLC was established with an accelerometer to estimate the fatigue load exerted by the rotor thrust. It was confirmed through experiments that the robustness and adaptation of the control system improved in the situation of pitch system failure. As a result of the experiment, the proposed

H_{\infty}

controller was able to reduce the rotor speed fluctuation by 39.9%, the power fluctuation by 32.0%, and the fatigue load by 2.4% compared with the LQR fuzzy controller, which had better performance than the conventional PI controller. In addition, it was confirmed through experiments that the robustness and adaptation of the control system were well maintained. This was even true in the situation of one-blade pitch system failure. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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21 pages, 17578 KiB

Open AccessArticle

Analysis of the Effects of Fluctuating Wind on the Aerodynamic Performance of a Vertical-Axis Wind Turbine with Variable Pitch

by Wei Zhang, Sifan Yang, Cheng Chen and Lang Li

Energies 2023, 16(20), 7130; https://doi.org/10.3390/en16207130 - 18 Oct 2023

Viewed by 1825

The wind turbine with a variable-pitch vertical axis is a novel type of small wind turbine with great development potential in the field of wind power generation. This study assessed the aerodynamic performance of a two-dimensional variable-pitch vertical-axis wind turbine (VAWT) under fluctuating [...] Read more.

The wind turbine with a variable-pitch vertical axis is a novel type of small wind turbine with great development potential in the field of wind power generation. This study assessed the aerodynamic performance of a two-dimensional variable-pitch vertical-axis wind turbine (VAWT) under fluctuating wind conditions (sinusoidal-type fluctuations with an average velocity of 6 m/s) using the finite-volume method and the

R N G k - ε

turbulence model. The effects of the fluctuating inflow amplitude (

U_{a m p}

), frequency (

f_{c}

), and mean tip speed ratio (

λ_{m e a n}

) on the power coefficient of the wind turbine are analyzed. The results show that a maximum power coefficient of 0.33 is obtained when the inflow amplitude reaches 50% of the average velocity. The power coefficient initially increases and then decreases with the increase in the fluctuating inflow frequency, reaching a maximum value of 0.32 at

f_{c} = 0.45 H z

. Furthermore, the power coefficient reaches its maximum value of 0.372 at

λ_{m e a n}

= 0.5. Proper orthogonal decomposition (POD) is used to decompose and reconstruct the flow field under both fluctuating and uniform inflow conditions. A comparison of the POD analysis between the two conditions shows that the energy distribution is more dispersed under the fluctuating inflow condition and reconstructing the flow field under fluctuating inflow conditions requires more POD modes than that under uniform inflow conditions. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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18 pages, 6988 KiB

Open AccessArticle

Differentiator-Based Output Feedback MPPT Controller for DFIG Wind Energy Conversion Systems with Minimal System Information

by Jang-Hyun Park

Energies 2023, 16(20), 7068; https://doi.org/10.3390/en16207068 - 12 Oct 2023

Cited by 3 | Viewed by 1446

This paper introduces a novel differentiator-based maximum power point tracking (MPPT) controller for a wind energy conversion system (WECS) equipped with a doubly fed induction generator (DFIG). Building upon our previous algorithms, the proposed controller reduces the need for detailed system information and [...] Read more.

This paper introduces a novel differentiator-based maximum power point tracking (MPPT) controller for a wind energy conversion system (WECS) equipped with a doubly fed induction generator (DFIG). Building upon our previous algorithms, the proposed controller reduces the need for detailed system information and displays enhanced robustness against parameter variations and disturbances. The innovation lies in the elimination of the need for explicit functional forms or specific parameter values in the system’s dynamics, relying solely on relative degrees and control directions. Utilizing a higher-order switching differentiator (HOSD), this paper outlines a method for overestimating the time derivatives of system outputs, thereby simplifying both the controller design and stability analysis. Compared to existing solutions, the proposed method requires minimal information, offers simpler control law structures, and follows a systematic design approach with fewer design constants. Simulation results demonstrate the efficacy of the proposed controller in both tracking maximum power and regulating reactive power to zero, suggesting a more efficient and simplified approach to MPPT control in WECS. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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24 pages, 7924 KiB

Open AccessArticle

Blade Design and Aerodynamic Performance Analysis of a 20 MW Wind Turbine for LCoE Reduction

by Kang-Ho Jang and Ki-Wahn Ryu

Energies 2023, 16(13), 5169; https://doi.org/10.3390/en16135169 - 5 Jul 2023

Cited by 6 | Viewed by 2842

The aim of this study is to develop a blade mass model that incorporates a low-induction rotor (LIR) and a low-specific power concept to reduce aerodynamic loads and lower the Levelized Cost of Energy (LCoE). This blade mass model replaces the traditional simple [...] Read more.

The aim of this study is to develop a blade mass model that incorporates a low-induction rotor (LIR) and a low-specific power concept to reduce aerodynamic loads and lower the Levelized Cost of Energy (LCoE). This blade mass model replaces the traditional simple scaling rule and incorporates the concept of LCoE reduction, presenting not only the mass distribution in the blade span direction but also the stiffness distribution. In order to achieve the desired reduction in LCoE, we developed a mathematical model that expresses blade mass as a function of the axial induction factor, which influences the aerodynamic load on the blade. We used this model to determine geometries of various low-induction rotors for 20 MW class horizontal axis wind turbine, and to identify the axial induction factor that correlates with the lowest blade mass. The chord length and twist angle in the spanwise direction of the blade were determined using PROPID’s reverse design process, based on the specified axial induction factor. Since the low-induction concept is not aerodynamically optimal, a low-specific power design approach was also adopted. This involved increasing the blade length and shifting the power curve to the left. By doing so, the AEP is increased, directly contributing to a reduction in the LCoE. Mass per unit length of the blade was presented, reflecting the distribution of airfoil type, blade geometry, and shapes of internal structures such as spars and webs. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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19 pages, 3997 KiB

Open AccessArticle

Fault Diagnosis of Wind Turbine with Alarms Based on Word Embedding and Siamese Convolutional Neural Network

by Lu Wei, Jiaqi Qu, Liliang Wang, Feng Liu, Zheng Qian and Hamidreza Zareipour

Appl. Sci. 2023, 13(13), 7580; https://doi.org/10.3390/app13137580 - 27 Jun 2023

Cited by 3 | Viewed by 1689

Alarms generated by a wind turbine alarm system indicate the need for emergency action by operators to protect the turbine from running into risky conditions. However, it can be challenging for operators to identify the fault types that trigger alarms, particularly with few [...] Read more.

Alarms generated by a wind turbine alarm system indicate the need for emergency action by operators to protect the turbine from running into risky conditions. However, it can be challenging for operators to identify the fault types that trigger alarms, particularly with few labeled fault samples. This paper proposes a novel fault diagnosis method for wind turbines with alarms that collaboratively uses labeled and unlabeled alarms to improve diagnosis accuracy. First, the proposed method distinguishes different alarm sequences using a designed Siamese convolutional neural network with an embedding layer (S-ECNN) model. Then, the fault category of an unknown alarm sequence is diagnosed based on similarity scores. Specifically, the Skip-gram model is used to mine potential relationships among alarms in unlabeled alarm sequences, and pretrained alarm vectors are obtained. In the S-ECNN model, the pretrained alarm vectors are further optimized and trained using labeled alarm sequences. The similarity scores are calculated based on the distance between the extracted discriminative features of alarm sequences. The effectiveness of the proposed method is validated using actual alarm data from a wind farm. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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23 pages, 51167 KiB

Open AccessArticle

Enhancing Savonius Vertical Axis Wind Turbine Performance: A Comprehensive Approach with Numerical Analysis and Experimental Investigations

by Kumail Abdulkareem Hadi Al-Gburi, Firas Basim Ismail Alnaimi, Balasem Abdulameer Jabbar Al-quraishi, Ee Sann Tan and Ali Kamil Kareem

Energies 2023, 16(10), 4204; https://doi.org/10.3390/en16104204 - 19 May 2023

Cited by 16 | Viewed by 6076

Small-scale vertical-axis wind power generation technologies such as Savonius wind turbines are gaining popularity in suburban and urban settings. Although vertical-axis wind turbines (VAWTs) may not be as efficient as their horizontal-axis counterparts, they often present better opportunities for integration within [...] Read more.

Small-scale vertical-axis wind power generation technologies such as Savonius wind turbines are gaining popularity in suburban and urban settings. Although vertical-axis wind turbines (VAWTs) may not be as efficient as their horizontal-axis counterparts, they often present better opportunities for integration within building structures. The main issue stems from the suboptimal aerodynamic design of Savonius turbine blades, resulting in lower efficiency and power output. To address this, modern turbine designs focus on optimizing various geometric aspects of the turbine to improve aerodynamic performance, efficiency, and overall effectiveness. This study developed a unique optimization method, incorporating a new blade geometry with guide gap flow for Savonius wind turbine blade design. The aerodynamic characteristics of the Savonius wind turbine blade were extensively analyzed using 3D ANSYS CFX software. The optimization process emphasized the power coefficient as the objective function while considering blade profiles, overlap ratio, and blade number as crucial design parameters. This objective was accomplished using the design of experiments (DOE) method with the Minitab statistical software. The research findings revealed that the novel turbine design “OR0.109BS2BN2” outperformed the reference turbine with a 22.8% higher power coefficient. Furthermore, the results indicated a trade-off between the flow (swirling flow) through the gap guide flow and the impact blockage ratio, which resulted from the reduced channel width caused by the extended blade tip length. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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25 pages, 2302 KiB

Open AccessFeature PaperArticle

Development and Validation of the IAG Dynamic Stall Model in State-Space Representation for Wind Turbine Airfoils

by Galih Bangga, Steven Parkinson and William Collier

Energies 2023, 16(10), 3994; https://doi.org/10.3390/en16103994 - 9 May 2023

Cited by 9 | Viewed by 3584

Considering the dynamic stall effects in engineering calculations is essential for correcting the aerodynamic loads acting on wind turbines, both during power production and stand-still cases, and impacts significantly the turbine aeroelastic stability. The employed dynamic stall model needs to be accurate and [...] Read more.

Considering the dynamic stall effects in engineering calculations is essential for correcting the aerodynamic loads acting on wind turbines, both during power production and stand-still cases, and impacts significantly the turbine aeroelastic stability. The employed dynamic stall model needs to be accurate and robust for a wide range of airfoils and range of angle of attack. The present studies are intended to demonstrate the performance of a recently implemented “IAG dynamic stall” model in a wind turbine design tool Bladed. The model is transformed from the indicial type of formulation into a state-space representation. The new model is validated against measurement data and other dynamic stall models in Bladed for various flow conditions and airfoils. It is demonstrated that the new model is able to reproduce the measured dynamic polar accurately without airfoil specific parameter calibration and has a superior performance compared to the incompressible Beddoes–Leishman model and the Øye model in Bladed. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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29 pages, 6737 KiB

Open AccessFeature PaperArticle

From Hydrometeor Size Distribution Measurements to Projections of Wind Turbine Blade Leading-Edge Erosion

by Fred Letson and Sara C. Pryor

Energies 2023, 16(9), 3906; https://doi.org/10.3390/en16093906 - 5 May 2023

Cited by 12 | Viewed by 2170

Wind turbine blade leading-edge erosion (LEE) is a cause of increased operation and maintenance costs and decreased annual energy production. Thus, detailed, site-specific quantification of likely erosion conditions are critically needed to inform wind plant owner/operator decisions regarding mitigation strategies. Estimating the damage [...] Read more.

Wind turbine blade leading-edge erosion (LEE) is a cause of increased operation and maintenance costs and decreased annual energy production. Thus, detailed, site-specific quantification of likely erosion conditions are critically needed to inform wind plant owner/operator decisions regarding mitigation strategies. Estimating the damage potential at a wind plant site requires accurate measurement of precipitation intensity, phase, droplet size distributions, wind speeds and their joint statistics. The current work quantifies the effect of disdrometer type on the characterization of LEE potential at a site in the US Southern Great Plains. using observations from three co-located disdrometers (an optical, an impact and a video disdrometer), along with hub-height wind-speed observations from a Doppler lidar and two LEE models: a kinetic energy model and the Springer model. Estimates of total kinetic energy of hydrometeor impacts over the four-year study period vary by as much as 38%, and coating lifetime derived from accumulated distance-to-failure estimates from the Springer model differ by an even greater amount, depending on disdrometer type. Damage potential at this site is concentrated in time, with 50% of impact kinetic energy occurring in 6–12 h per year, depending on which set of disdrometer observations is used. Rotor-speed curtailment during the most erosive 0.1–0.2% of 10 min periods is found to increase blade lifetimes and lead to the lowest levelized cost of energy. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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21 pages, 12528 KiB

Open AccessArticle

Assessing the Performance of Small Wind Energy Systems Using Regional Weather Data

by Wolf-Gerrit Früh

Energies 2023, 16(8), 3500; https://doi.org/10.3390/en16083500 - 17 Apr 2023

Cited by 1 | Viewed by 2952

While large renewable power generation schemes, such as wind farms, are well monitored with a wealth of data provided through a SCADA system, the only information about the behaviour of small wind turbines is often only through the metered electricity production. Given the [...] Read more.

While large renewable power generation schemes, such as wind farms, are well monitored with a wealth of data provided through a SCADA system, the only information about the behaviour of small wind turbines is often only through the metered electricity production. Given the variability of electricity output in response to the local wind or radiation condition, it is difficult to ascertain whether particular electricity production in a metering period is the result of the system operating normally or if a fault is resulting in a sub-optimal production. This paper develops two alternative methods to determine a performance score based only on electricity production and proxy wind data obtained from the nearest available weather measurement. One method based on partitioning the data, consistent with a priori expectations of turbine performance, performs well in common wind conditions but struggles to reflect the effects of different wind directions. An alternative method based on Principal Component Analysis is less intuitive but shown to be able to incorporate wind direction. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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14 pages, 1197 KiB

Open AccessArticle

Impact Assessment of Dynamic Loading Induced by the Provision of Frequency Containment Reserve on the Main Bearing Lifetime of a Wind Turbine

by Narender Singh, Dibakor Boruah, Jeroen D. M. De Kooning, Wim De Waele and Lieven Vandevelde

Energies 2023, 16(6), 2851; https://doi.org/10.3390/en16062851 - 19 Mar 2023

Cited by 3 | Viewed by 2797

The components of an operational wind turbine are continuously impacted by both static and dynamic loads. Regular inspections and maintenance are required to keep these components healthy. The main bearing of a wind turbine is one such component that experiences heavy loading forces [...] Read more.

The components of an operational wind turbine are continuously impacted by both static and dynamic loads. Regular inspections and maintenance are required to keep these components healthy. The main bearing of a wind turbine is one such component that experiences heavy loading forces during operation. These forces depend on various parameters such as wind speed, operating regime and control actions. When a wind turbine provides frequency containment reserve (FCR) to support the grid frequency, the forces acting upon the main bearing are also expected to exhibit more dynamic variations. These forces have a direct impact on the lifetime of the main bearing. With an increasing trend of wind turbines participating in the frequency ancillary services market, an analysis of these dynamic forces becomes necessary. To this end, this paper assesses the effect of FCR-based control on the main bearing lifetime of the wind turbine. Firstly, a control algorithm is implemented such that the output power of the wind turbine is regulated as a function of grid frequency and the amount of FCR. Simulations are performed for a range of FCR to study the changing behaviour of dynamical forces acting on the main bearing with respect to the amount of FCR provided. Then, based on the outputs from these simulations and using 2 years of LiDAR wind data, the lifetime of the main bearing of the wind turbine is calculated and compared for each of the cases. Finally, based on the results obtained from this study, the impact of FCR provision on the main bearing lifetime is quantified and recommendations are made, that could be taken into account in the operation strategy of a wind farm. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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29 pages, 18685 KiB

Open AccessArticle

Numerical Simulation and Experimental Verification of Wind Field Reconstruction Based on PCA and QR Pivoting

by Shi Liu and Guangchao Zhang

Appl. Sci. 2023, 13(5), 2927; https://doi.org/10.3390/app13052927 - 24 Feb 2023

Cited by 3 | Viewed by 1882

Short-term wind forecasting is critical for the dispatch, controllability and stability of a power grid. As a challenging but indispensable work, short-term wind forecasting has attracted considerable attention from researchers. In this paper, Principal Component Analysis (PCA) is applied to Computational Fluid Dynamics [...] Read more.

Short-term wind forecasting is critical for the dispatch, controllability and stability of a power grid. As a challenging but indispensable work, short-term wind forecasting has attracted considerable attention from researchers. In this paper, Principal Component Analysis (PCA) is applied to Computational Fluid Dynamics (CFD) calculation results for feature extraction and then combined with sparse sensing to achieve the rapid reconstruction of a three-dimensional wind speed field and pressure field. Before reconstruction, the relationship between the reconstruction error and the noise level, and a number of the basis vectors is systematically studied. In the simulation, the wind shear effect is introduced into the inlet boundary condition, and the reconstruction errors of the uniform inlet are 0.21% and 6.46%, respectively, while the maximum reconstruction errors including the wind shear effect are 1.21% and 6.41%, respectively, which verifies the feasibility of applying a PCA-based reconstruction algorithm to a 3D wind field reconstruction. In addition, to solve the time-consuming problem of most optimization algorithms based on a brute-force combinatorial search, an innovative optimization algorithm based on the QR pivoting is investigated to determine the sparse sensor placements. Simulation results show that when the number of sensors is equal to the number of basis vectors, the error of random placement is even 20 times of the optimal placement, which illustrates that QR pivoting is a powerful optimization algorithm. Finally, a wind tunnel experiment of velocity field reconstruction is performed, to verify the practicability of the optimized method based on QR pivoting, and the results indicate that a reasonably high accuracy 3D wind field can be obtained with only 10 sensors (the error of most points is less than 5% and the minimum error is only 0.74%). In general, the proposed algorithm incorporating PCA, sparse sensing and QR pivoting can quickly reconstruct the 3D velocity and pressure fields with reduced measurement costs, which is of great significance for the development of short-term wind forecasting methods. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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17 pages, 5120 KiB

Open AccessArticle

Design and Experimental Research on Centralized Lubrication and Waste Oil Recovery System for Wind Turbines

by Linjian Shangguan and Yuming Xu

Appl. Sci. 2023, 13(3), 1873; https://doi.org/10.3390/app13031873 - 31 Jan 2023

Cited by 3 | Viewed by 2670

Lubrication plays a key role in increasing availability of wind turbines, extending unit life and reducing operating costs. In view of the problems of valve core lag, grease hardening and difficulty in removing waste oil in a centralized lubrication system, an improved centralized [...] Read more.

Lubrication plays a key role in increasing availability of wind turbines, extending unit life and reducing operating costs. In view of the problems of valve core lag, grease hardening and difficulty in removing waste oil in a centralized lubrication system, an improved centralized lubrication system and waste oil recovery system were designed in this study. Discharge of waste grease in the bearing cavity was simulated under different vacuum conditions. It was shown that vacuum degree of bearing cavity is proportional to oil output speed of waste grease. Performance and fatigue reliability tests of the waste grease suction and drainer device test platform were conducted over 12,000 fatigue cycles. The results show that the vacuum degree error of the waste grease suction and drainer device before and after the test is less than 5%, and the power oil pressure, oil output pressure and oil output quantity of the test product are stable, indicating that the designed waste grease suction and drainer device has excellent sealing and reliability. The waste grease suction and drainer device can eliminate grease discharge resistance in the bearing cavity, facilitating discharge of waste oil and improving wind turbine operation efficiency. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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21 pages, 13598 KiB

Open AccessArticle

Load Characteristics and Extreme Response of Straight-Bladed Floating VAWT Using a Fully Coupled Model

by Wenping Luo, Weiqin Liu, Meng Yang, Shuo Chen, Xuemin Song and Weiguo Wu

J. Mar. Sci. Eng. 2023, 11(1), 185; https://doi.org/10.3390/jmse11010185 - 11 Jan 2023

Cited by 6 | Viewed by 2602

Operating Offshore Floating Vertical Axis Wind Turbines (OF-VAWT) have the potential to perform well in the deep-sea area. Some researchers gave performance prediction by developing simplified computing models. However, these models have imperfections in considering load and motion nonlinearity, especially in extreme environments. [...] Read more.

Operating Offshore Floating Vertical Axis Wind Turbines (OF-VAWT) have the potential to perform well in the deep-sea area. Some researchers gave performance prediction by developing simplified computing models. However, these models have imperfections in considering load and motion nonlinearity, especially in extreme environments. In this work, a numerical model is developed composed of Computational Fluid Dynamics (CFD) and Dynamic Fluid Body Interaction (DFBI) to acquire the aero-hydrodynamic load and performance of OF-VAWT in general and extreme environments. Unsteady Reynolds-Averaged Navier-Stokes (URANS), SST k-ω and Eulerian Multi-Phase (EMP) models are combined to generate a gas-liquid two-phase flow field; the Volume of Fluid (VOF) model is employed to capture free-surface and make numerical wind-wave. DFBI superposition motion technology is proposed for local motion definition and motion solution, and overset with sliding meshes is introduced to achieve the grid motion. The numerical approach is verified by the tunnel and tank experimental data from the available literature. Simulation results of general cases, such as variable wind speed, wave height and wave length, are compared to discuss the effect of environmental parameters on load and performance. Comparison shows that this straight-bladed OF-VAWT is more susceptible to wind speed. Furthermore, the aerodynamic load generated by the shut-down rotor is still significant in extreme environment, which has implications for the development of OF-VAWT controller. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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23 pages, 3687 KiB

Open AccessEditor’s ChoiceArticle

Wind-Assisted Ship Propulsion of a Series 60 Ship Using a Static Kite Sail

by Wayne Formosa, Tonio Sant, Claire De Marco Muscat-Fenech and Massimo Figari

J. Mar. Sci. Eng. 2023, 11(1), 117; https://doi.org/10.3390/jmse11010117 - 5 Jan 2023

Cited by 8 | Viewed by 3840

Following the International Maritime Organization’s goal to reduce greenhouse gas emissions, the interest in the application of wind-assisted ship propulsion (WASP) in maritime transportation is on the rise. Although a variety of WASP systems exist, the application in maritime shipping is still limited, [...] Read more.

Following the International Maritime Organization’s goal to reduce greenhouse gas emissions, the interest in the application of wind-assisted ship propulsion (WASP) in maritime transportation is on the rise. Although a variety of WASP systems exist, the application in maritime shipping is still limited, especially in the case of kite sails. This paper presents a numerical model to carry out a theoretical assessment of the influence of the kite planform area and wind speed on the aerodynamic performance of a kite sail providing propulsive assistance to a 75 m long ship having a Series 60 hull. A static kite sail is assumed, on which a tail wind generates a thrust force to pull the vessel via a tether. While the mass of the kite is neglected, that of the tether is accounted for. A model is implemented for the tensioned tether having a catenary profile. The results generally show a positive correlation between the aerodynamic forces and the kite parameters. As expected, the output parameter values corresponding to the optimal angle of attack for a range of vessel speeds are also found to increase with an increasing relative wind speed. It is concluded that a static 320 m² kite sail would be sufficient to meet the entire propulsion requirements of the vessel under consideration under appropriate wind conditions. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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18 pages, 6590 KiB

Open AccessArticle

Aerodynamic Performance and Wake Characteristics Analysis of Archimedes Spiral Wind Turbine Rotors with Different Blade Angle

by Ke Song, Huiting Huan and Yuchi Kang

Energies 2023, 16(1), 385; https://doi.org/10.3390/en16010385 - 29 Dec 2022

Cited by 13 | Viewed by 8524

Continuous improvement of wind turbines represent an effective way of achieving green energy and reducing dependence on fossil fuel. Conventional lift-type horizontal axis wind turbines, which are widely used, are designed to run under high wind speed to obtain a high efficiency. Aiming [...] Read more.

Continuous improvement of wind turbines represent an effective way of achieving green energy and reducing dependence on fossil fuel. Conventional lift-type horizontal axis wind turbines, which are widely used, are designed to run under high wind speed to obtain a high efficiency. Aiming to use the low-speed wind in urban areas, a novel turbine, which is called the Archimedes Spiral Wind Turbine (abbreviated as ASWT), was recently proposed for low-speed wind applications. In the current work, a numerical simulation on the five ASWT rotors with different blade angles was carried out, which were performed to predict the detailed aerodynamic performance and wake characteristics. The results show that the ASWT rotor with a large blade angle has a wider operating tip speed ratio range and a higher tip speed ratio point of maximum power coefficient within a certain range, and yet the ASWT rotor with the larger blade angle has a higher thrust coefficient. Additionally, the ASWT rotor with a large blade angle usually has a large power coefficient and thrust coefficient fluctuation amplitude. On the other hand, the ASWT rotor with a small blade angle permits the undisturbed free stream to pass through the rotor blades more easily than that with a large blade angle. This causes a stronger blockage effect for the ASWT rotor with a large blade angle. Moreover, the blade angle also has a great effect on the shape of the vortex structure. The blade tip vortex of the fixed-angle ASWT rotors is more stable than those of the variable-angle ASWT rotors. The hub vortex of the ASWT rotors with a large blade angle is stronger than those with a small blade angle. Meanwhile, the wake recovery for ASWT rotors with a small blade angle is evidently lower than those with a large blade angle. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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23 pages, 7660 KiB

Open AccessArticle

Experimental and Simulation Investigation of Performance of Scaled Model for a Rotor of a Savonius Wind Turbine

by Kumail Abdulkareem Hadi Al-Gburi, Balasem Abdulameer Jabbar Al-quraishi, Firas Basim Ismail Alnaimi, Ee Sann Tan and Ali Hussein Shamman Al-Safi

Energies 2022, 15(23), 8808; https://doi.org/10.3390/en15238808 - 22 Nov 2022

Cited by 7 | Viewed by 3083

Renewable energy sources are preferred for many power generation applications. Energy from the wind is one of the fastest-expanding kinds of sustainable energy, and it is essential in preventing potential energy issues in the foreseeable future. One pertinent issue is the many geometrical [...] Read more.

Renewable energy sources are preferred for many power generation applications. Energy from the wind is one of the fastest-expanding kinds of sustainable energy, and it is essential in preventing potential energy issues in the foreseeable future. One pertinent issue is the many geometrical alterations that the scientific community has suggested to enhance rotor performance features. Hence, to address the challenge of developing a model that resolves these problems, the purpose of this investigation was to determine how well a scaled-down version of a Savonius turbine performed in terms of power output using a wind tunnel. Subsequently, the effect of the blockage ratio produced in the wind tunnel during the chamber test on the scaled model was evaluated. This study discusses the influences of various modified configurations on the turbine blades’ torque and power coefficients (Cp) at various tip speed ratios (TSRs) using three-dimensional (3D) unsteady computational fluid dynamics. The findings showed that the scaled model successfully achieved tunnel blockage corrections, and the experimental results obtained can be used in order to estimate how the same turbine would perform in real conditions. Furthermore, numerically, the new models achieved improvements in Cp of 19.5%, 16.8%, and 12.2%, respectively, for the flow-guiding channel (FGC at Ⴔ = 30°), wavy area at tip and end (WTE), and wavy area on the convex blade (WCB) models in comparison to the benchmark S-ORM model and under identical wind speed conditions. This investigation can provide guidance for improvements of the aerodynamic characteristics of Savonius wind turbines. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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23 pages, 4509 KiB

Open AccessArticle

Novel Machine-Learning-Based Stall Delay Correction Model for Improving Blade Element Momentum Analysis in Wind Turbine Performance Prediction

by Ijaz Fazil Syed Ahmed Kabir, Mohan Kumar Gajendran, E. Y. K. Ng, Amirfarhang Mehdizadeh and Abdallah S. Berrouk

Wind 2022, 2(4), 636-658; https://doi.org/10.3390/wind2040034 - 6 Oct 2022

Cited by 12 | Viewed by 3293

Wind turbine blades experience excessive load due to inaccuracies in the prediction of aerodynamic loads by conventional methods during design, leading to structural failure. The blade element momentum (BEM) method is possibly the oldest and best-known design tool for evaluating the aerodynamic performance [...] Read more.

Wind turbine blades experience excessive load due to inaccuracies in the prediction of aerodynamic loads by conventional methods during design, leading to structural failure. The blade element momentum (BEM) method is possibly the oldest and best-known design tool for evaluating the aerodynamic performance of wind turbine blades due to its simplicity and short processing time. As the turbine rotates, the aerofoil lift coefficient enhances, notably in the rotor’s inboard section, relative to the value predicted by 2D experimentation or computational fluid dynamics (CFD) for the identical angle of attack; this is induced by centrifugal pumping action and the Coriolis force, thus delaying the occurrence of stall. This rotational effect is regarded as having a significant influence on the rotor blade’s aerodynamic performance, which the BEM method does not capture, as it depends on 2D aerofoil characteristics. Correction models derived from the traditional hard computing mathematical method are used in the BEM predictions to take into account stall delay. Unfortunately, it has been observed from the earlier literature that these models either utterly fail or inaccurately predict the enhancement in lift coefficient due to stall delay. Consequently, this paper proposes a novel stall delay correction model based on the soft computing technique known as symbolic regression for high-level precise aerodynamic performance prediction by the BEM process. In complement to the correction model for the lift coefficient, a preliminary correction model for the drag coefficient is also suggested. The model is engendered from the disparity in 3D and 2D aerofoil coefficients over the blade length for different wind speeds for the NREL Phase VI turbine. The proposed model’s accuracy is evaluated by validating the 3D aerofoil coefficients computed from the experimental results of a second wind turbine known as the MEXICO rotor. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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20 pages, 1713 KiB

Open AccessReview

Progress on Offshore Wind Farm Dynamic Wake Management for Energy

by Liye Zhao, Lei Xue, Zhiqian Li, Jundong Wang, Zhichao Yang and Yu Xue

J. Mar. Sci. Eng. 2022, 10(10), 1395; https://doi.org/10.3390/jmse10101395 - 30 Sep 2022

Cited by 14 | Viewed by 4704

The wake management of offshore wind farms (OWFs) mainly considers the wake effect. Wake effects commonly occur in offshore wind farms, which cause a 5–10% reduction in power production. Although there have been many studies on wake management, many methods are not accurate [...] Read more.

The wake management of offshore wind farms (OWFs) mainly considers the wake effect. Wake effects commonly occur in offshore wind farms, which cause a 5–10% reduction in power production. Although there have been many studies on wake management, many methods are not accurate enough; for instance, look-up table and static wake model control methods do not consider the time-varying wake state. Dynamic wake management is based on the real-time dynamic wake, so it can increase the energy of the OWFs effectively. For OWFs, dynamic wake control is the main method of dynamic wake management. In this paper, the existing wake model and control progress are discussed, mainly emphasizing the dynamic wake model and the dynamic wake control method, solving the gap of the review for dynamic wake management. This paper presents a digital twins (DT) framework for power and fatigue damage for the first time.. The structure of this paper is as follows: (1) the mechanism of wind farm wake interference is described and then the dynamic wake model is reviewed and summarized; (2) different control methods are analyzed and the dynamic wake management strategies for different control methods are reviewed; (3) in order to solve the problems of dynamic wake detection and real-time effective control, the technology of DT is applied to the dynamic wake control of OWFs. This new DT frame has a promising application prospect in improving power and reducing fatigue damage. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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23 pages, 4936 KiB

Open AccessArticle

Impact of Design Parameters on the Dynamic Response and Fatigue of Offshore Jacket Foundations

by Ali Marjan and Phil Hart

J. Mar. Sci. Eng. 2022, 10(9), 1320; https://doi.org/10.3390/jmse10091320 - 18 Sep 2022

Cited by 5 | Viewed by 3189

The lifetime of offshore foundations is governed by a combination of harsh environmental conditions and complex service loads. The fatigue limit state (FLS) analysis needs to be performed in the time domain to capture the complex phenomenon. This study aims to investigate different [...] Read more.

The lifetime of offshore foundations is governed by a combination of harsh environmental conditions and complex service loads. The fatigue limit state (FLS) analysis needs to be performed in the time domain to capture the complex phenomenon. This study aims to investigate different parameters and design modifications that can impact the design life of an offshore jacket foundation. An OC4 jacket foundation is designed in industrial software from DNV and reduced to a super-element model. The super-element model is connected to an NREL 5-MW wind turbine designed in Bladed. The time-series loads are used to compute the fatigue damages faced by the foundation during the service life. The impact of soil non-linearity, marine growth, scour size, the mass of the transition piece, and the grouted connection’s design on the dynamic response and fatigue damages are compared. A 30% increase in life was observed by replacing the concrete transition piece with a lightweight steel configuration. The fatigue damages were considerably greater for the inclined pile in the leg grouted connection than for the leg in the pile concept. The study provides a different perspective by analysing the effect of design parameters and design changes in the complex and computationally expensive time-series domain. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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17 pages, 3144 KiB

Open AccessArticle

A Maximum Power Point Tracking Control Method Based on Rotor Speed PDF Shape for Wind Turbines

by Xinge Zhang, Zhen Zhang, Junru Jia and Liming Zheng

Appl. Sci. 2022, 12(18), 9108; https://doi.org/10.3390/app12189108 - 10 Sep 2022

Cited by 13 | Viewed by 2953

Maximum power point tracking (MPPT) is the key to improve the conversion efficiency of wind energy. Concerning the current research on the MPPT control, based on the accurate tracking of rotor speed probability density function (PDF) shape for wind turbines, a novel MPPT [...] Read more.

Maximum power point tracking (MPPT) is the key to improve the conversion efficiency of wind energy. Concerning the current research on the MPPT control, based on the accurate tracking of rotor speed probability density function (PDF) shape for wind turbines, a novel MPPT algorithm was introduced in detail to improve the power capture and reduce mechanical damage for wind turbines. Considering the influence of wind speed distribution on the wind power generation system performance, this paper expounds a PDF shape control method of a stochastic system based on the Fokker–Planck–Kolmogorov (FPK) equation. Combining the conventional optimal torque (OT) control algorithm with the FPK equation solved by linear least-square (LLS) method, the novel MPPT control law is designed to make the PDF shape of rotor speed track the desired PDF shape as accurately as possible. The simulation verification of the novel MPPT method is carried out in the 1.5 MW wind turbine system. The results reveal that the novel MPPT method can improve the conversion efficiency of wind energy, reduce the frequent fluctuations of system variables, and significantly optimize the performance of wind power generation system. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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15 pages, 6351 KiB

Open AccessArticle

Active Disturbance Rejection Control for Wind Turbine Fatigue Load

by Xingkang Jin, Wen Tan, Yarong Zou and Zijian Wang

Energies 2022, 15(17), 6178; https://doi.org/10.3390/en15176178 - 25 Aug 2022

Cited by 6 | Viewed by 1978

With the participation of wind power in grid frequency modulation, the fatigue load of the wind turbine increases accordingly. A new control method that considers both fatigue load and output power of wind turbine (WT) is proposed in this paper. A linear active [...] Read more.

With the participation of wind power in grid frequency modulation, the fatigue load of the wind turbine increases accordingly. A new control method that considers both fatigue load and output power of wind turbine (WT) is proposed in this paper. A linear active disturbance rejection control (LADRC) is designed and applied for the pitch angle in the wind turbine load reduction control. The particle swarm optimization (PSO) algorithm is used to optimize the parameters of the wind turbine controller, and the total variation of the wind turbine shaft torque and tower bending moment is added to construct a new objective function to further reduce the fatigue load of the wind turbine. The design-optimized controller is validated on a 5 MW wind turbine in SimWindFarm. The simulation results show that the LADRC controller can accurately track the reference power of the wind turbine, reduce the pitch angle fluctuation of the wind turbine, reduce the fatigue load of the wind turbine, and improve the service life of the wind turbine. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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13 pages, 2848 KiB

Open AccessArticle

Evaluation of Wind and Wave Estimates from CMEMS Reanalysis for Brazil’s Offshore Energy Resource Assessment

by Ismael Guidson Farias de Freitas, Helber Barros Gomes, Malaquias Peña, Panagiotis Mitsopoulos, Thayna Silva Vila Nova, Kécia Maria Roberto da Silva and Alan James Peixoto Calheiros

Wind 2022, 2(3), 586-598; https://doi.org/10.3390/wind2030031 - 24 Aug 2022

Cited by 1 | Viewed by 2573

This study aims to evaluate wind speed and significant wave height data from the Copernicus Marine Environment Monitoring Service (CMEMS) reanalysis using buoy measurements for offshore energy application off the east coast of Brazil. Such analysis has become important, since reanalysis datasets can [...] Read more.

This study aims to evaluate wind speed and significant wave height data from the Copernicus Marine Environment Monitoring Service (CMEMS) reanalysis using buoy measurements for offshore energy application off the east coast of Brazil. Such analysis has become important, since reanalysis datasets can be fundamental tools in identifying regions with wind energy potential that are suitable for the installation of offshore farms. Two sets of reanalysis were used: wind speed (with spatial resolution of 0.25° and temporal resolution of 6 h) and significant wave height (with spatial resolution of 0.2° and temporal resolution of 3 h). For validation, seven MetOcean buoys were selected. In the statistical validation, Pearson’s correlation, coefficient of determination (R²), slope of the straight line, root mean square error (RMSE), mean square error (MSE), probability density function (PDF), mean and standard deviation were calculated. In the evaluation of offshore wind energy resources, the calculation of energy density was performed. The results showed correlations above 0.70 for wind speed and above 0.91 for significant wave height, and additionally, the RMSE values showed maximums of 2.31 m/s for wind speed and 0.28 cm for significant wave height. In the PDF comparison of buoy data and reanalysis, similarities were observed, mainly in the PDF parameters. The energy density presented values consistent with other studies (352–461 W/m²). The results show that the reanalysis data can be applicable in studies focusing on offshore wind potential. Full article

(This article belongs to the Topic Advances in Wind Energy Technology)

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Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Applied Sciences applsci	2.5	5.3	2011	18.4 Days	CHF 2400
Clean Technologies cleantechnol	4.1	6.1	2019	33.5 Days	CHF 1600
Energies energies	3.0	6.2	2008	16.8 Days	CHF 2600
Journal of Marine Science and Engineering jmse	2.7	4.4	2013	16.4 Days	CHF 2600
Wind wind	-	-	2021	35.7 Days	CHF 1000

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Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Applied Sciences applsci	2.5	5.3	2011	18.4 Days	CHF 2400
Clean Technologies cleantechnol	4.1	6.1	2019	33.5 Days	CHF 1600
Energies energies	3.0	6.2	2008	16.8 Days	CHF 2600
Journal of Marine Science and Engineering jmse	2.7	4.4	2013	16.4 Days	CHF 2600
Wind wind	-	-	2021	35.7 Days	CHF 1000

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