Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.0
2.1
Journals
Machines
Special Issues
Advances in Wind and Solar Energy Generation
share announcement

Advances in Wind and Solar Energy Generation

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Electromechanical Energy Conversion Systems".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 13427

Special Issue Editor

Prof. Dr. Wah Hoon Siew

E-Mail Website
Guest Editor
Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK
Interests: large systems electromagnetic compatibility; lightning protection; electrical systems monitoring and diagnostics

Special Issue Information

Dear Colleagues,

Renewable Energy Systems have begun to prevail in recent years due to the ambition by various governments to reduce their carbon footprint to zero in the future. Consequently, more and more renewable energy systems are being installed and very large systems tend to be in remote and not very accessible areas. There is, therefore, a challenge to design such systems that will be able to operate with minimum (if not without) human intervention in terms of maintenance and operation.  This Special Issue, therefore, invites contributions from authors who are working on such systems in monitoring; operation (including smart operation); design; ease of maintenance, and so on, which will help towards achieving the goal of minimum intervention.

Prof. Dr. Wah Hoon Siew
Guest Editor

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. Machines is an international peer-reviewed open access monthly 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 2400 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.

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (5 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

17 pages, 8428 KiB  
Article
Mitigation of Lightning-Induced Transient Effects on a Hybrid Photovoltaic–Wind System Based on Lightning Protection Standards
by Zmnako Mohammed Khurshid Abda, Mohd Zainal Abidin Ab Kadir, Hashim Hizam and Chandima Gomes
Machines 2023, 11(7), 707; https://doi.org/10.3390/machines11070707 - 3 Jul 2023
Viewed by 1549
Abstract
Installing surge protection devices in a hybrid photovoltaic (PV)–wind system is essential to guarantee the survival of the system’s components. If the surge arresters are connected without taking into account the recommendations given by standards, the equipment to be protected might be damaged [...] Read more.
Installing surge protection devices in a hybrid photovoltaic (PV)–wind system is essential to guarantee the survival of the system’s components. If the surge arresters are connected without taking into account the recommendations given by standards, the equipment to be protected might be damaged despite the energy coordination of the arresters. In this study, nonlinear surge protective devices (SPDs) are designed for a multi-MW hybrid system based on lightning protection standards with optimised threat level ratings to investigate the mitigation of lightning transients to an acceptable level. The system is implemented using Power System Computer-Aided Design for Electromagnetic Transients including Direct Current (PSCAD/EMTDC) software. It comprises a 2 MW PV farm, a 2 MW wind farm, and a backup energy storage system (ESS), which are all connected to a 132 kV grid via a step-up transformer and a transmission line. The results were obtained at critical system nodes for two standard lightning current surges, i.e., 1/10 µs and 10/350 µs, considering two lightning strike point scenarios with and without a lightning protection system (LPS). The simulation results showed that the connected SPDs could successfully limit the transient overvoltage in the system to an acceptable level. The analysis in this work is crucial for designing, operating, and maintaining a hybrid PV–wind system. It can help to find the potential vulnerability areas within such a system and implement appropriate protection measures since there is no available lightning standard for such systems. Additionally, it assists the system operators in increasing the uptime and dependability of their RE systems, limiting expensive downtime and environmental effects while optimising energy output. Based on the results obtained, recommendations were made for lightning protection developers. Full article
(This article belongs to the Special Issue Advances in Wind and Solar Energy Generation)
►▼ Show Figures

Figure 1

12 pages, 2046 KiB  
Article
Wind Turbine Blade LPS Design Process Revisited—Leveraging on the Latest Knowledge from Actual Lightning Measurements in Wind Turbines
by Søren Find Madsen, Stephan Vogel, Javier Lopez and Lisa Carloni
Machines 2023, 11(5), 541; https://doi.org/10.3390/machines11050541 - 11 May 2023
Viewed by 2019
Abstract
The present paper addresses some recent lightning measurements with the in actual wind turbines, to demonstrate the amount of data that is currently collected, and the information provided. Basic statistical analysis is conducted on the 2603 lightning waveforms obtained, and implications for design [...] Read more.
The present paper addresses some recent lightning measurements with the in actual wind turbines, to demonstrate the amount of data that is currently collected, and the information provided. Basic statistical analysis is conducted on the 2603 lightning waveforms obtained, and implications for design and verification processes for blades are suggested. Some reflections on the increased industry openness are shared, which is already benefitting the general understanding of lightning exposure, and the future standards on the topic. Full article
(This article belongs to the Special Issue Advances in Wind and Solar Energy Generation)
►▼ Show Figures

Figure 1

18 pages, 6438 KiB  
Article
Wind Turbine Blade Defect Detection Based on Acoustic Features and Small Sample Size
by Yuefan Zhu, Xiaoying Liu, Shen Li, Yanbin Wan and Qiaoqiao Cai
Machines 2022, 10(12), 1184; https://doi.org/10.3390/machines10121184 - 7 Dec 2022
Cited by 5 | Viewed by 3072
Abstract
Wind power has become an important source of electricity for both production and domestic use. However, because wind turbines often operate in harsh environments, they are prone to cracks, blisters, and corrosion of the blade surface. If these defects cannot be repaired in [...] Read more.
Wind power has become an important source of electricity for both production and domestic use. However, because wind turbines often operate in harsh environments, they are prone to cracks, blisters, and corrosion of the blade surface. If these defects cannot be repaired in time, the cracks evolve into larger fractures, which can lead to blade rupture. As such, in this study, we developed a remote non-contact online health monitoring and warning system for wind turbine blades based on acoustic features and artificial neural networks. Collecting a large number of wind turbine blade defect signals was challenging. To address this issue, we designed an acoustic detection method based on a small sample size. We employed the octave to extract defect information, and we used an artificial neural network based on model-agnostic meta-learning (MAML-ANN) for classification. We analyzed the influence of locations and compared the performance of MAML-ANN with that of traditional ANN. The experimental results showed that the accuracy of our method reached 94.1% when each class contained only 50 data; traditional ANN achieved an accuracy of only 85%. With MAML-ANN, the training is fast and the global optimal solution is automatic searched, and it can be expanded to situations with a large sample size. Full article
(This article belongs to the Special Issue Advances in Wind and Solar Energy Generation)
►▼ Show Figures

Figure 1

18 pages, 6328 KiB  
Article
Numerical Simulation of the Lightning Leader Development and Upward Leader Initiation for Rotating Wind Turbine
by Wanshui Yu, Qingmin Li, Jiyao Zhao and Wah Hoon Siew
Machines 2022, 10(2), 115; https://doi.org/10.3390/machines10020115 - 4 Feb 2022
Cited by 4 | Viewed by 2312
Abstract
Lightning accidents seriously threaten safe operation of wind turbines because the influence mechanisms of wind turbine rotation on corona and upward leader initiation are, so far, not clear. A three-dimensional stochastic evolution model of the lightning downward leader was established by combining the [...] Read more.
Lightning accidents seriously threaten safe operation of wind turbines because the influence mechanisms of wind turbine rotation on corona and upward leader initiation are, so far, not clear. A three-dimensional stochastic evolution model of the lightning downward leader was established by combining the dielectric breakdown model and the lightning current shunt method, according to which the charge density distribution of leader branches was determined. The corona and leader initiation mechanisms of rotating wind turbine were studied based on the 3D drift and diffusion model of ion flow in the neighboring space of a rotating wind turbine. The results show that due to blade rotation, the charged particles are unevenly distributed near the blade tip and the contours are in a strip-like shape. As the rotating speed increases, the blade tip is more susceptible to initiating corona discharge. Combining the three-dimensional stochastic development model of the lightning downward leader and ion distribution model near a rotating wind turbine, the initiation direction of the upward leader was analyzed, and in 66% of cases, the initiation direction of the upward leader on the blade tip was on the back side of the blade rotation. Full article
(This article belongs to the Special Issue Advances in Wind and Solar Energy Generation)
►▼ Show Figures

Figure 1

21 pages, 6560 KiB  
Article
Study on Improvement of Lightning Damage Detection Model for Wind Turbine Blade
by Takuto Matsui, Kazuo Yamamoto and Jun Ogata
Machines 2022, 10(1), 9; https://doi.org/10.3390/machines10010009 - 22 Dec 2021
Cited by 7 | Viewed by 3411
Abstract
There have been many reports of damage to wind turbine blades caused by lightning strikes in Japan. In some of these cases, the blades struck by lightning continue to rotate, causing more serious secondary damage. To prevent such accidents, it is a requirement [...] Read more.
There have been many reports of damage to wind turbine blades caused by lightning strikes in Japan. In some of these cases, the blades struck by lightning continue to rotate, causing more serious secondary damage. To prevent such accidents, it is a requirement that a lightning detection system is installed on the wind turbine in areas where winter lightning occurs in Japan. This immediately stops the wind turbine if the system detects a lightning strike. Normally, these wind turbines are restarted after confirming soundness of the blade through visual inspection. However, it is often difficult to confirm the soundness of the blade visually for reasons such as bad weather. This process prolongs the time taken to restart, and it is one of the causes that reduces the availability of the wind turbines. In this research, we constructed a damage detection model for wind turbine blades using machine learning based on SCADA system data and, thereby, considered whether the technology automatically confirms the soundness of wind turbine blades. Full article
(This article belongs to the Special Issue Advances in Wind and Solar Energy Generation)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-5
Back to TopTop