Pub Date : 2023-06-12DOI: 10.1109/APL57308.2023.10181888
Hau Lee Cheun, Chua Kein Huat, Albert Kow Kek Hing, Lim Kim Ten, Steven Chia
This paper presents the results of the reliability and sensitivity analysis conducted on lightning risk assessment (LRA) software compliant with the MS IEC 62305-2:2007 standard. The aim was to identify input parameters that can be fixed without compromising the reliability of the LRA and input parameters that have strong influence on the output risk values, thus significantly influencing the reliability of LRA. The results show that input CE, $r_{a}, h_{b}, R_{s}, W_{a}, L_{a}, H_{pb}, P_{A}$, and Uw have minimal impact on the output risk values and can be fixed. Conversely, the input parameters $mathrm{P}_{SPD}, mathrm{P}_{B}, r_{p}, mathrm{H}_{c}, mathrm{H}_{b}, mathrm{W}_{b}, r_{f}$, and Ng have strong influences on the output risk values. The accurate entry of these strong influence input parameters is crucial for reliable LRA as small changes can lead to significant changes in output risk values. It is recommended to carefully consider and accurately enter the remaining input parameters, as they could still result in influencing changes on the output risk values. The findings of this study are used in developing LRA software to provide qualitative LRA for protecting fixed structures and services against lightning hazards.
{"title":"A Comprehensive Reliability and Sensitivity Analysis of MS IEC 62305-2:2007 Lightning Risk Assessment Compliant Software","authors":"Hau Lee Cheun, Chua Kein Huat, Albert Kow Kek Hing, Lim Kim Ten, Steven Chia","doi":"10.1109/APL57308.2023.10181888","DOIUrl":"https://doi.org/10.1109/APL57308.2023.10181888","url":null,"abstract":"This paper presents the results of the reliability and sensitivity analysis conducted on lightning risk assessment (LRA) software compliant with the MS IEC 62305-2:2007 standard. The aim was to identify input parameters that can be fixed without compromising the reliability of the LRA and input parameters that have strong influence on the output risk values, thus significantly influencing the reliability of LRA. The results show that input CE, $r_{a}, h_{b}, R_{s}, W_{a}, L_{a}, H_{pb}, P_{A}$, and Uw have minimal impact on the output risk values and can be fixed. Conversely, the input parameters $mathrm{P}_{SPD}, mathrm{P}_{B}, r_{p}, mathrm{H}_{c}, mathrm{H}_{b}, mathrm{W}_{b}, r_{f}$, and Ng have strong influences on the output risk values. The accurate entry of these strong influence input parameters is crucial for reliable LRA as small changes can lead to significant changes in output risk values. It is recommended to carefully consider and accurately enter the remaining input parameters, as they could still result in influencing changes on the output risk values. The findings of this study are used in developing LRA software to provide qualitative LRA for protecting fixed structures and services against lightning hazards.","PeriodicalId":371726,"journal":{"name":"2023 12th Asia-Pacific International Conference on Lightning (APL)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122148297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Smart appliances refer to a class of devices that have monitoring, protection, control, and communication functions, such as smart circuit breakers, smart contactors, smart surge protective devices (SPD), and so on. However, the manual maintenance of these smart appliances has security risks because of missed and false detections. In order to reduce the difficulties in SPD maintenance, the smart SPD is taken as the research object in this paper. The IoT cloud platform technology is used to develop the smart SPD online monitoring system. The system is divided into the device-side and the application-side. When designing the device-side, a Python program is written to collect the data from the SPD and send the data to the cloud platform. When designing the application-side, the Aliyun IoT platform is used to manage the SPDs and develop the Web application. After the design, all parts of the monitoring system are tested. The results show that each part of the system operates well and can achieve the desired goal.
{"title":"Research on Monitoring Platform of Smart SPD Based on Cloud System","authors":"Jiawei Shen, Qibin Zhou, Bin Shao, Xiao-liang Bian, Ting Cao, Xin Huang","doi":"10.1109/APL57308.2023.10181697","DOIUrl":"https://doi.org/10.1109/APL57308.2023.10181697","url":null,"abstract":"Smart appliances refer to a class of devices that have monitoring, protection, control, and communication functions, such as smart circuit breakers, smart contactors, smart surge protective devices (SPD), and so on. However, the manual maintenance of these smart appliances has security risks because of missed and false detections. In order to reduce the difficulties in SPD maintenance, the smart SPD is taken as the research object in this paper. The IoT cloud platform technology is used to develop the smart SPD online monitoring system. The system is divided into the device-side and the application-side. When designing the device-side, a Python program is written to collect the data from the SPD and send the data to the cloud platform. When designing the application-side, the Aliyun IoT platform is used to manage the SPDs and develop the Web application. After the design, all parts of the monitoring system are tested. The results show that each part of the system operates well and can achieve the desired goal.","PeriodicalId":371726,"journal":{"name":"2023 12th Asia-Pacific International Conference on Lightning (APL)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128323281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-12DOI: 10.1109/APL57308.2023.10181418
N. Bahari, Mona Riza Mohd Esa, M. A. Wahab
Flash flood is a natural disaster that causes many casualties and economic losses; it has become prevalent in Malaysia, where several events have been reported showing a possible correlation between lightning, rain, and flash floods. The lightning and rainfall intensity associated with flash flood events, are analyzed between January and April 2022 for three events (cases) within a distance of 100 km from Universiti Teknologi Malaysia, Johor. The data supplied by Tenaga Nasional Berhad Research Sdn. Bhd. (TNBR), Department of Irrigation and Drainage (DID) and Malaysia Meteorological Department (MetMalaysia) were evaluated for statistical discrepancies, which is a different approachable method by limiting the criteria for each data source. This research aims to investigate the relationship between the number of lightning occurrences with the amount of rain in 24 hours by applying the Pearson correlation coefficient (r) and determine the relationship strength between lightning and rainfall intensity parameters by implementing the rainfall-lightning ratio (RLR) change to rainfall-lightning rate, which is commonly used to evaluate the relationship between rainfall and lightning. This study found that the r-values between lightning and rain range from 0.4 to 0.7, which correlates well with rainfall and is considered an acceptable correlation. The different values due to the number of lightning and rain occurrences are inconsistent for each independent case. According to the findings, lightning data may be utilized in association with rain. Therefore, the accuracy of the existing flood forecasting system may be improved.
山洪是造成大量人员伤亡和经济损失的自然灾害;这种现象在马来西亚非常普遍，据报道，马来西亚发生的几起事件表明闪电、降雨和山洪暴发之间可能存在关联。分析了2022年1月至4月期间与山洪事件相关的闪电和降雨强度，这些事件发生在距柔佛州马来西亚科技大学100公里范围内的三个事件(案例)。数据由Tenaga national Berhad Research Sdn提供。有限公司(TNBR)、灌溉和排涝部(DID)和马来西亚气象部(MetMalaysia)进行了统计差异评估，这是一种不同的可接近方法，通过限制每个数据源的标准。本研究利用Pearson相关系数(r)研究24 h内闪电发生次数与降雨量的关系，并通过将降雨-闪电比(RLR)变化为降雨-闪电率，确定闪电与降雨强度参数之间的关系强度。降雨-闪电率通常用于评价降雨与闪电的关系。本研究发现闪电与降雨之间的r值在0.4 ~ 0.7之间，与降雨量的相关性较好，是可以接受的。由于闪电和降雨发生的次数而产生的不同值在每个独立的情况下是不一致的。根据研究结果，闪电资料可与降雨结合使用。因此，现有的洪水预报系统的准确性可能会有所提高。
{"title":"Correlation Analysis of Lightning and Flash Flood Events using Pearson Model in Southeast Peninsular Malaysia","authors":"N. Bahari, Mona Riza Mohd Esa, M. A. Wahab","doi":"10.1109/APL57308.2023.10181418","DOIUrl":"https://doi.org/10.1109/APL57308.2023.10181418","url":null,"abstract":"Flash flood is a natural disaster that causes many casualties and economic losses; it has become prevalent in Malaysia, where several events have been reported showing a possible correlation between lightning, rain, and flash floods. The lightning and rainfall intensity associated with flash flood events, are analyzed between January and April 2022 for three events (cases) within a distance of 100 km from Universiti Teknologi Malaysia, Johor. The data supplied by Tenaga Nasional Berhad Research Sdn. Bhd. (TNBR), Department of Irrigation and Drainage (DID) and Malaysia Meteorological Department (MetMalaysia) were evaluated for statistical discrepancies, which is a different approachable method by limiting the criteria for each data source. This research aims to investigate the relationship between the number of lightning occurrences with the amount of rain in 24 hours by applying the Pearson correlation coefficient (r) and determine the relationship strength between lightning and rainfall intensity parameters by implementing the rainfall-lightning ratio (RLR) change to rainfall-lightning rate, which is commonly used to evaluate the relationship between rainfall and lightning. This study found that the r-values between lightning and rain range from 0.4 to 0.7, which correlates well with rainfall and is considered an acceptable correlation. The different values due to the number of lightning and rain occurrences are inconsistent for each independent case. According to the findings, lightning data may be utilized in association with rain. Therefore, the accuracy of the existing flood forecasting system may be improved.","PeriodicalId":371726,"journal":{"name":"2023 12th Asia-Pacific International Conference on Lightning (APL)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133402270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-12DOI: 10.1109/APL57308.2023.10181525
S. H. Asman, N. F. Aziz, M. Kadir, U. Amirulddin, Nurzanariah Roslan, A. Elsanabary
Transmission lines are susceptible to a variety of phenomena that can cause system faults. The most prevalent cause of faults in the power system is lightning strikes, while other causes may include insulator failure, tree or crane encroachment. In this study, two machine learning algorithms, Support Vector Machine (SVM) and k-Nearest Neighbor (kNN), were used and compared to classify faults due to lightning strikes, insulator failure, tree and crane encroachment. The input variables for the models were based on the root mean square (RMS) current duration, voltage dip, and energy wavelet measured at the sending end of a line. The proposed method was implemented in the MATLAB/SIMULINK programming platform. The classification performance of the developed algorithms was evaluated using confusion matrix. Overall, SVM algorithm performed better than k-NN in terms of classification accuracy, achieving a value of 97.10% compared to k-NN’s 70.60%. Moreover, SVM also outperformed k-NN in terms of computational time, with time taken by SVM is 3.63 s compared to 10.06 s by k-NN.
{"title":"Lightning Fault Classification for Transmission Line Using Support Vector Machine","authors":"S. H. Asman, N. F. Aziz, M. Kadir, U. Amirulddin, Nurzanariah Roslan, A. Elsanabary","doi":"10.1109/APL57308.2023.10181525","DOIUrl":"https://doi.org/10.1109/APL57308.2023.10181525","url":null,"abstract":"Transmission lines are susceptible to a variety of phenomena that can cause system faults. The most prevalent cause of faults in the power system is lightning strikes, while other causes may include insulator failure, tree or crane encroachment. In this study, two machine learning algorithms, Support Vector Machine (SVM) and k-Nearest Neighbor (kNN), were used and compared to classify faults due to lightning strikes, insulator failure, tree and crane encroachment. The input variables for the models were based on the root mean square (RMS) current duration, voltage dip, and energy wavelet measured at the sending end of a line. The proposed method was implemented in the MATLAB/SIMULINK programming platform. The classification performance of the developed algorithms was evaluated using confusion matrix. Overall, SVM algorithm performed better than k-NN in terms of classification accuracy, achieving a value of 97.10% compared to k-NN’s 70.60%. Moreover, SVM also outperformed k-NN in terms of computational time, with time taken by SVM is 3.63 s compared to 10.06 s by k-NN.","PeriodicalId":371726,"journal":{"name":"2023 12th Asia-Pacific International Conference on Lightning (APL)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133739254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-12DOI: 10.1109/APL57308.2023.10182038
Shaoyang Wang, Ming-li Chen, Yan Gao, Ya-ping Du
Lightning current as one of the most important parameters in the study of lightning physics and lightning protection have long been attended. Previously, due to the lack of suitable current measurement devices, the formation process of several milliampere corona discharges under thunderstorms and the development process of lightning channel up to hundreds of kiloamperes could only be measured separately, and the study of transition from corona discharge to leader process in lightning initiation stage has not been well-addressed. In this study, a 100 V shock tolerated preamplifier with a noise floor as low as 0.55 μV was designed and installed on Shenzhen Meteorological Gradient Tower (SZMGT) with a single 0.25 mΩ coaxial shunt for lightning current measurement. By using this device, we have successfully observed the corona discharges of several hundred milliamperes just before the formation of lightning leaders. The results showed that the preamplifier had achieved a noise level below 10 mA with a shock tolerance up to 220 kA.
{"title":"Preliminary Results of Corona Discharge Current Measurements in the Early Formation of Lightning on Tower","authors":"Shaoyang Wang, Ming-li Chen, Yan Gao, Ya-ping Du","doi":"10.1109/APL57308.2023.10182038","DOIUrl":"https://doi.org/10.1109/APL57308.2023.10182038","url":null,"abstract":"Lightning current as one of the most important parameters in the study of lightning physics and lightning protection have long been attended. Previously, due to the lack of suitable current measurement devices, the formation process of several milliampere corona discharges under thunderstorms and the development process of lightning channel up to hundreds of kiloamperes could only be measured separately, and the study of transition from corona discharge to leader process in lightning initiation stage has not been well-addressed. In this study, a 100 V shock tolerated preamplifier with a noise floor as low as 0.55 μV was designed and installed on Shenzhen Meteorological Gradient Tower (SZMGT) with a single 0.25 mΩ coaxial shunt for lightning current measurement. By using this device, we have successfully observed the corona discharges of several hundred milliamperes just before the formation of lightning leaders. The results showed that the preamplifier had achieved a noise level below 10 mA with a shock tolerance up to 220 kA.","PeriodicalId":371726,"journal":{"name":"2023 12th Asia-Pacific International Conference on Lightning (APL)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114721958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-12DOI: 10.1109/APL57308.2023.10181984
Ziwei Ma, J. Jasni, M. Kadir, N. Azis
Developing a numerical simulation model for shielding failure evaluation of UHV transmission lines is an urgent task. In this article, a dynamic leader propagation model of lightning attachment to UHV transmission lines was developed based on FEM. The lightning downward leader descending vertically at a speed of $2 times 10^{5} m/s$ from a distance of 50 m from the side of the UHV transmission line was considered as a lossy conductor. Peek’s formula was used for initial corona inception criterion. The streamer space charge and the leader length were calculated by using the voltage distortion method. The upward leader was assumed to propagate in the direction of the maximum field strength. The final jump was considered to occur once the average electric field strength of the remaining gap reaches 450 kV/m. Without considering the operating voltage, the simulation result shows that the striking distance of the ground wire under the return stroke current of 10 kA, 20 kA, 30 kA, 40 kA and 50 kA is 54 m, 94 m, 143 m, 157 m, and $234 m$ respectively. A new expression of $r_{s}=7.2 I_{p}^{0.87}$ for the striking distance calculation based on LPM was proposed. The striking distance calculated by this new model is between the EGM empirical model and theoretical model, which proves that the model is reasonable.
{"title":"A Lightning Attachment Model to UHV Transmission Lines Based on FEM","authors":"Ziwei Ma, J. Jasni, M. Kadir, N. Azis","doi":"10.1109/APL57308.2023.10181984","DOIUrl":"https://doi.org/10.1109/APL57308.2023.10181984","url":null,"abstract":"Developing a numerical simulation model for shielding failure evaluation of UHV transmission lines is an urgent task. In this article, a dynamic leader propagation model of lightning attachment to UHV transmission lines was developed based on FEM. The lightning downward leader descending vertically at a speed of $2 times 10^{5} m/s$ from a distance of 50 m from the side of the UHV transmission line was considered as a lossy conductor. Peek’s formula was used for initial corona inception criterion. The streamer space charge and the leader length were calculated by using the voltage distortion method. The upward leader was assumed to propagate in the direction of the maximum field strength. The final jump was considered to occur once the average electric field strength of the remaining gap reaches 450 kV/m. Without considering the operating voltage, the simulation result shows that the striking distance of the ground wire under the return stroke current of 10 kA, 20 kA, 30 kA, 40 kA and 50 kA is 54 m, 94 m, 143 m, 157 m, and $234 m$ respectively. A new expression of $r_{s}=7.2 I_{p}^{0.87}$ for the striking distance calculation based on LPM was proposed. The striking distance calculated by this new model is between the EGM empirical model and theoretical model, which proves that the model is reasonable.","PeriodicalId":371726,"journal":{"name":"2023 12th Asia-Pacific International Conference on Lightning (APL)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134013873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-12DOI: 10.1109/APL57308.2023.10182048
M.S. Azaman, D. Johari, F. A. Haris, A. F. Abidin, N. H. Nik Ali, N. Hatta
This paper presents an investigation on the characteristics of cloud-to-ground (CG) lightning over land and ocean in Peninsular Malaysia. The study aims to investigate the characteristics of negative and positive CG in Peninsular Malaysia, particularly over land and ocean on the west coast region and over the Malacca Straits. By analyzing 2020 lightning data recorded by the lightning locating system (LLS) operated by TNB Research (TNBR), we analyzed the negative and positive CG in terms of their occurrences, stroke density, and the peak currents. Six circular regions with a 15 km radius were selected: three (3) over the land and three (3) over the ocean, each having distinct characteristics from the others. We found that most of the CG lightning occurred over land than ocean but there is only a slight difference of 2.4% between the two. We also found that the average peak current for negative CG is higher over the ocean with a geometric mean of 25.7 kA whereas for land, the average value is 21.9 kA. For positive CG, we found that the average peak current is also higher over the ocean with a geometric mean of 32.3 kA whereas for land, the average value is 28.7 kA. The higher occurrence of the CG lightning over land could be due to the heat effect caused by the increase in the development over the land region. The higher intensity of the CG peak currents over the ocean could be due to larger aerosol emission in the area and the higher conductivity of the seawater.
{"title":"Cloud-to-Ground Lightning Activity over Land and Ocean in Peninsular Malaysia","authors":"M.S. Azaman, D. Johari, F. A. Haris, A. F. Abidin, N. H. Nik Ali, N. Hatta","doi":"10.1109/APL57308.2023.10182048","DOIUrl":"https://doi.org/10.1109/APL57308.2023.10182048","url":null,"abstract":"This paper presents an investigation on the characteristics of cloud-to-ground (CG) lightning over land and ocean in Peninsular Malaysia. The study aims to investigate the characteristics of negative and positive CG in Peninsular Malaysia, particularly over land and ocean on the west coast region and over the Malacca Straits. By analyzing 2020 lightning data recorded by the lightning locating system (LLS) operated by TNB Research (TNBR), we analyzed the negative and positive CG in terms of their occurrences, stroke density, and the peak currents. Six circular regions with a 15 km radius were selected: three (3) over the land and three (3) over the ocean, each having distinct characteristics from the others. We found that most of the CG lightning occurred over land than ocean but there is only a slight difference of 2.4% between the two. We also found that the average peak current for negative CG is higher over the ocean with a geometric mean of 25.7 kA whereas for land, the average value is 21.9 kA. For positive CG, we found that the average peak current is also higher over the ocean with a geometric mean of 32.3 kA whereas for land, the average value is 28.7 kA. The higher occurrence of the CG lightning over land could be due to the heat effect caused by the increase in the development over the land region. The higher intensity of the CG peak currents over the ocean could be due to larger aerosol emission in the area and the higher conductivity of the seawater.","PeriodicalId":371726,"journal":{"name":"2023 12th Asia-Pacific International Conference on Lightning (APL)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124508550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-12DOI: 10.1109/APL57308.2023.10181611
Yutaro Higashi, Kazuo Yamamoto
Wind power generation systems are vulnerable to winter lightning in the coastal areas of the Sea of Japan. For preventing the spread of lightning damage and ensuring safety, lightning detection systems (LDSs) have been installed to immediately stop wind turbines when a lightning strikes on the wind turbine. However, many of LDSs in widespread use in recent years are expensive, and many of them have a single mechanism that detects lightning strikes based on the lightning current obtained by integrating the magnetic field. In this study, in order to develop a relatively inexpensive and accurate LDS, we investigated a lightning detection method that uses acoustic data from lightning strikes to determine whether a lightning strike has occurred.
{"title":"Study of Lightning Detection Method Using Acoustic Data","authors":"Yutaro Higashi, Kazuo Yamamoto","doi":"10.1109/APL57308.2023.10181611","DOIUrl":"https://doi.org/10.1109/APL57308.2023.10181611","url":null,"abstract":"Wind power generation systems are vulnerable to winter lightning in the coastal areas of the Sea of Japan. For preventing the spread of lightning damage and ensuring safety, lightning detection systems (LDSs) have been installed to immediately stop wind turbines when a lightning strikes on the wind turbine. However, many of LDSs in widespread use in recent years are expensive, and many of them have a single mechanism that detects lightning strikes based on the lightning current obtained by integrating the magnetic field. In this study, in order to develop a relatively inexpensive and accurate LDS, we investigated a lightning detection method that uses acoustic data from lightning strikes to determine whether a lightning strike has occurred.","PeriodicalId":371726,"journal":{"name":"2023 12th Asia-Pacific International Conference on Lightning (APL)","volume":"490 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122751410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-12DOI: 10.1109/APL57308.2023.10181774
Azwadi Mohamad, N. Abdullah, N. Hatta, H. Mokhlis, H. Illias, Mohd Syukri Ali
Accurate classification of lightning faults on transmission lines is crucial in identifying the type of fault, whether it is due to shielding failure or back-flashover. This knowledge is essential in implementing a cost-effective and optimized mitigation method to improve transmission line performance. Previous mitigation efforts focused on improving tower footing resistance (TFR), which does not mitigate shielding failure. This study proposes an artificial intelligence approach to recognize, classify, and distinguish between back-flashover and shielding failure based on waveform signatures of disturbance fault recorders (DFR) with a sampling rate of 5kHz. The methods used in this study are discrete wavelet transform (DWT) utilizing wavelet similarity index, and artificial neural network (ANN). The simulation data using these methods demonstrate an 88.9% accuracy rate for the DWT method, while the ANN method achieves an accuracy rate of 97% for back flashover and 100% for shielding failure using signals at 16.7MHz, while for down-sampled data at 5KHz, the accuracy are 93% and 97% respectively.
{"title":"Lightning Fault Classification on Transmission Lines using Discrete Wavelet Transform and Artificial Neural Network","authors":"Azwadi Mohamad, N. Abdullah, N. Hatta, H. Mokhlis, H. Illias, Mohd Syukri Ali","doi":"10.1109/APL57308.2023.10181774","DOIUrl":"https://doi.org/10.1109/APL57308.2023.10181774","url":null,"abstract":"Accurate classification of lightning faults on transmission lines is crucial in identifying the type of fault, whether it is due to shielding failure or back-flashover. This knowledge is essential in implementing a cost-effective and optimized mitigation method to improve transmission line performance. Previous mitigation efforts focused on improving tower footing resistance (TFR), which does not mitigate shielding failure. This study proposes an artificial intelligence approach to recognize, classify, and distinguish between back-flashover and shielding failure based on waveform signatures of disturbance fault recorders (DFR) with a sampling rate of 5kHz. The methods used in this study are discrete wavelet transform (DWT) utilizing wavelet similarity index, and artificial neural network (ANN). The simulation data using these methods demonstrate an 88.9% accuracy rate for the DWT method, while the ANN method achieves an accuracy rate of 97% for back flashover and 100% for shielding failure using signals at 16.7MHz, while for down-sampled data at 5KHz, the accuracy are 93% and 97% respectively.","PeriodicalId":371726,"journal":{"name":"2023 12th Asia-Pacific International Conference on Lightning (APL)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124104000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-12DOI: 10.1109/APL57308.2023.10181380
M. Matsui, N. Honjo, K. Michishita, S. Yokoyama
The authors have observed lightning strokes occurring in a coastal area of the Sea of Japan, where is the most active area of winter lightning in the world. Catastrophic accidents have been frequent at wind farms in those areas due to winter lightning. We have analyzed the characteristics of lightning strokes hitting wind turbines and the relationship between those and temperatures at the upper-air layer. We used the datasets observed by the Japanese Lightning Detection Network (JLDN) for this analysis. We showed the seasonal differences in the characteristics of lightning strokes hitting the wind turbines. Our studies showed that lightning strokes were more concentrated near the wind turbines in winter than in summer. This is one of the characteristics of winter lightning due to discharges initialized upward from tall structures. We also showed the relationship between the ratios of lightning strokes that occurred in the vicinity of the wind turbine and the temperatures at the 700 hPa level and the altitude of −10°C isotherm altitude. We discussed how to define the occurrence conditions of winter lightning using the relationship shown above.
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