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Trends and Innovations in Wind Power Systems
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Trends and Innovations in Wind Power Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A3: Wind, Wave and Tidal Energy".

Deadline for manuscript submissions: closed (15 April 2023) | Viewed by 15874

Special Issue Editors

Prof. Dr. Mircea Neagoe

E-Mail Website
Guest Editor
Renewable Energy Systems and Recycling Research Centre, Transilvania University of Brasov, 500036 Brasov, Romania
Interests: wind power system; planetary speed increaser; counter-rotating wind turbine; dynamics; power flow; modeling; simulation; artificial intelligence; product design and development
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Radu Săulescu

E-Mail Website
Guest Editor
Design of Mechanical Elements and Systems R&D Centre, Transilvania University of Brasov, 500036 Brasov, Romania
Interests: renewable energy systems; counter-rotating wind turbines; dynamics of planetary speed increasers; solar tracking systems; product design and development
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Codruta Jaliu

E-Mail Website
Guest Editor
Renewable Energy Systems and Recycling Research Centre, Transilvania University of Brasov, Brașov, Romania
Interests: small hydropower; wind energy; conversion systems; hybrid systems; energy efficiency; product design and development
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to invite you to publish your latest research results in this Special Issue of Energies on ‘Trends and Innovations in Wind Power Systems’.

The global wind power capacity registered in the last decade, including both onshore and offshore, an exponential increase every year reaching over 650 GW and a consolidated second place among the other renewables. Thus, the wind energy is becoming a major source of green and cost-competitive energy worldwide, although it is site-dependent and its conversion is influenced by the equipment performance.

Increasing energy-conversion efficiency to maximize the use of the onsite renewable potential is a major challenge. Many innovative solutions of wind turbines have been proposed in recent years, such as counter-rotating wind rotors, high-performance mechanical transmissions, and more compact and efficient electric generators, including the counter-rotating generator type, large-capacity wind turbines that use multiple, smaller rotors in a spatial arrangement, etc. The integration of wind turbines in the built environment has been intensively studied by combining technical, environmental, and aesthetic aspects. Researchers and designers in the field are facing market demands for affordable, efficient, reliable, stable, and smart solutions for wind turbines.

This Special Issue will gather new research results and future trends in the field of wind turbines, covering a broad range of topics of interest for publication but not limited to the following:

  • Wind energy potential and forecasting
  • Innovative design and optimization of wind turbines
  • Modeling and numerical simulation of wind turbines
  • Intelligent control of wind turbines
  • Wind energy conversion efficiency
  • Reliability and maintenance of wind turbines
  • Integration of wind turbines in the built environment
  • Energy management

Review papers and articles based on multidisciplinary research are also encouraged.

Prof. Dr. Mircea Neagoe
Prof. Dr. Radu Săulescu
Prof. Dr. Codruta Jaliu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Wind power system
  • Horizontal axis wind turbine
  • Vertical axis wind turbine
  • Counter-rotating wind turbine
  • Wind rotor
  • Speed increaser
  • Gearbox
  • Electrical generator
  • Wind energy
  • Potential
  • Forecasting
  • Onshore
  • Offshore
  • Hybrid energy systems
  • Integration in the built environment
  • Design
  • Optimization
  • Innovation
  • Dynamics
  • Efficiency
  • Grid integration
  • Emerging technology
  • Operation
  • Control
  • Stability
  • Artificial intelligence
  • Fault detection
  • Power quality
  • Modeling
  • Economics
  • Numerical simulations
  • Experimental testing
  • Reliability
  • Maintainance
  • Condition monitoring
  • Recycling

Published Papers (5 papers)

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Research

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19 pages, 3641 KiB  
Article
A Novel Ensemble Model Based on an Advanced Optimization Algorithm for Wind Speed Forecasting
by Yukun Wang, Aiying Zhao, Xiaoxue Wei and Ranran Li
Energies 2023, 16(14), 5281; https://doi.org/10.3390/en16145281 - 10 Jul 2023
Cited by 2 | Viewed by 763
Abstract
Concerning the vision of achieving carbon neutral and peak carbon goals, wind energy is extremely important as a renewable and clean energy source. However, existing research ignores the implicit features of the data preprocessing technique and the role of the internal mechanism of [...] Read more.
Concerning the vision of achieving carbon neutral and peak carbon goals, wind energy is extremely important as a renewable and clean energy source. However, existing research ignores the implicit features of the data preprocessing technique and the role of the internal mechanism of the optimization algorithm, making it difficult to achieve high-accuracy prediction. To fill this gap, this study proposes a wind speed forecasting model that combines data denoising techniques, optimization algorithms, and machine learning algorithms. The model discusses the important parameters in the data decomposition technique, determines the best parameter values by comparing the model’s performance, and then decomposes and reconstructs the wind speed time series. In addition, a novel optimization algorithm is used to optimize the parameters of the machine learning algorithm using a waiting strategy and an aggressive strategy to improve the effectiveness of the model. Several control experiments were designed and implemented using 10-min wind speed data from three sites in Penglai, Shandong Province. Based on the numerical comparison results and the discussion of the proposed model, it is concluded that the developed model can obtain high accuracy and reliability of wind speed prediction in the short term relative to other comparative models and can have further applications in wind power plants. Full article
(This article belongs to the Special Issue Trends and Innovations in Wind Power Systems)
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24 pages, 2221 KiB  
Article
Wind Turbine Power Maximization Using Log-Power Proportional-Integral Extremum Seeking
by Devesh Kumar and Mario A. Rotea
Energies 2022, 15(3), 1004; https://doi.org/10.3390/en15031004 - 29 Jan 2022
Cited by 2 | Viewed by 1597
Abstract
This paper proposes a Log-Power Proportional-Integral Extremum Seeking Control (LP-PIESC) framework for maximizing the power capture of a wind turbine operating at below-rated wind speeds, i.e., the so-called region-2 of a turbine’s power curve. Extremum seeking control (ESC) has emerged as a viable [...] Read more.
This paper proposes a Log-Power Proportional-Integral Extremum Seeking Control (LP-PIESC) framework for maximizing the power capture of a wind turbine operating at below-rated wind speeds, i.e., the so-called region-2 of a turbine’s power curve. Extremum seeking control (ESC) has emerged as a viable algorithm to maximize energy capture for a wind turbine operating in region-2. Despite the encouraging results of early ESC strategies, the basic algorithm suffers from slow and inconsistent convergence behavior under changing wind speed within region-2. It has been shown that replacing the power signal with its logarithm results in an algorithm that is robust and predictable even when the mean wind speed varies. In addition, new studies have suggested that replacing conventional ESC with proportional plus integral ESC (PIESC) results in faster convergence to optimal conditions. In the current paper, the idea of log-power feedback is merged with the PIESC scheme and is applied to tune the parameters of the region-2 torque controller for the NREL 5-MW turbine reference model. The results of this new algorithm are compared with the ESC with log-of-power feedback using NREL OpenFAST simulations. The log-power feedback PIESC is also implemented for the blade pitch set-point angle. Energy capture over the course of the simulations and damage equivalent loads calculated with MLife are used to assess the results. The simulations performed under different turbulent intensity cases demonstrate the rapid convergence of the log-power feedback PIESC. Full article
(This article belongs to the Special Issue Trends and Innovations in Wind Power Systems)
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16 pages, 3582 KiB  
Article
MPPT Improvement for PMSG-Based Wind Turbines Using Extended Kalman Filter and Fuzzy Control System
by Amirsoheil Honarbari, Sajad Najafi-Shad, Mohsen Saffari Pour, Seyed Soheil Mousavi Ajarostaghi and Ali Hassannia
Energies 2021, 14(22), 7503; https://doi.org/10.3390/en14227503 - 10 Nov 2021
Cited by 20 | Viewed by 2720
Abstract
Variable speed wind turbines are commonly used as wind power generation systems because of their lower maintenance cost and flexible speed control. The optimum output power for a wind turbine can be extracted using maximum power point tracking (MPPT) strategies. However, unpredictable parameters, [...] Read more.
Variable speed wind turbines are commonly used as wind power generation systems because of their lower maintenance cost and flexible speed control. The optimum output power for a wind turbine can be extracted using maximum power point tracking (MPPT) strategies. However, unpredictable parameters, such as wind speed and air density could affect the accuracy of the MPPT methods, especially during the wind speed small oscillations. In this paper, in a permanent magnet synchronous generator (PMSG), the MPPT is implemented by determining the uncertainty of the unpredictable parameters using the extended Kalman filter (EKF). Also, the generator speed is controlled by employing a fuzzy logic control (FLC) system. This study aims at minimizing the effects of unpredictable parameters on the MPPT of the PMSG system. The simulation results represent an improvement in MPPT accuracy and output power efficiency. Full article
(This article belongs to the Special Issue Trends and Innovations in Wind Power Systems)
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22 pages, 104336 KiB  
Article
Wind Speed and Solar Irradiance Prediction Using a Bidirectional Long Short-Term Memory Model Based on Neural Networks
by Fahad Radhi Alharbi and Denes Csala
Energies 2021, 14(20), 6501; https://doi.org/10.3390/en14206501 - 11 Oct 2021
Cited by 17 | Viewed by 3385
Abstract
The rapid growth of wind and solar energy penetration has created critical issues, such as fluctuation, uncertainty, and intermittence, that influence the power system stability, grid operation, and the balance of the power supply. Improving the reliability and accuracy of wind and solar [...] Read more.
The rapid growth of wind and solar energy penetration has created critical issues, such as fluctuation, uncertainty, and intermittence, that influence the power system stability, grid operation, and the balance of the power supply. Improving the reliability and accuracy of wind and solar energy predictions can enhance the power system stability. This study aims to contribute to the issues of wind and solar energy fluctuation and intermittence by proposing a high-quality prediction model based on neural networks (NNs). The most efficient technology for analyzing the future performance of wind speed and solar irradiance is recurrent neural networks (RNNs). Bidirectional RNNs (BRNNs) have the advantages of manipulating the information in two opposing directions and providing feedback to the same outputs via two different hidden layers. A BRNN’s output layer concurrently receives information from both the backward layers and the forward layers. The bidirectional long short-term memory (BI-LSTM) prediction model was designed to predict wind speed, solar irradiance, and ambient temperature for the next 169 h. The solar irradiance data include global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance (DHI). The historical data collected from Dumat al-Jandal City covers the period from 1 January 1985 to 26 June 2021, as hourly intervals. The findings demonstrate that the BI-LSTM model has promising performance in terms of evaluation, with considerable accuracy for all five types of historical data, particularly for wind speed and ambient temperature values. The model can handle different sizes of sequential data and generates low error metrics. Full article
(This article belongs to the Special Issue Trends and Innovations in Wind Power Systems)
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Review

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36 pages, 4656 KiB  
Review
Electrical Generators for Large Wind Turbine: Trends and Challenges
by Amina Bensalah, Georges Barakat and Yacine Amara
Energies 2022, 15(18), 6700; https://doi.org/10.3390/en15186700 - 13 Sep 2022
Cited by 21 | Viewed by 6188
Abstract
This paper presents an overview of the emerging trends in the development of electrical generators for large wind turbines. To describe the developments in the design of electrical generators, it is necessary to look at the conversion system as a whole, and then, [...] Read more.
This paper presents an overview of the emerging trends in the development of electrical generators for large wind turbines. To describe the developments in the design of electrical generators, it is necessary to look at the conversion system as a whole, and then, the structural and mechanical performances of the drive train need to be considered. Many drive train configurations have been proposed for large wind turbines; they should ensure high reliability, long availability and reduced maintainability. Although most installed wind turbines are geared, directly driven wind turbines with permanent magnet generators have attracted growing interest in the last few years, which has been in parallel to the continuous increase of the per unit turbine power. The aim of this work is to present the recent commercial designs of electrical generators in large wind turbines. Both the strengths and weaknesses of the existing systems are discussed. The most emerging technologies in high-power, low-speed electrical generators are investigated. Furthermore, a comparative analysis of different electrical generator concepts is performed, and the generators are assessed upon a list of criteria such as the mass, cost, and mass-to-torque ratio. Within the framework of these criteria, it may help to determine whether the electrical generator is technically feasible and economically viable for high-power wind turbines. Finally, this review could help to determine suitable generators for use in large and ultra-large wind energy systems. Full article
(This article belongs to the Special Issue Trends and Innovations in Wind Power Systems)
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