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 10193

Special Issue Editor


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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

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Published Papers (5 papers)

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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 - 03 Jul 2023
Viewed by 998
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)
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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 1408
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)
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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 - 07 Dec 2022
Cited by 4 | Viewed by 2186
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)
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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 - 04 Feb 2022
Cited by 3 | Viewed by 1810
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)
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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 5 | Viewed by 2862
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)
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