Pub Date : 2024-07-23DOI: 10.3390/electronics13152892
Qinghui Zhang, Yaya Sun, Pengtao Lv, Lei Lu, Mengya Zhang, Jinhui Wang, Chenxia Wan, Jingping Wang
Unstructured Chinese medical texts are rich sources of entity and relational information. The extraction of entity relationships from medical texts is pivotal for the construction of medical knowledge graphs and aiding healthcare professionals in making swift and informed decisions. However, the extraction of entity relationships from these texts presents a formidable challenge, notably due to the issue of overlapping entity relationships. This study introduces a novel extraction model that leverages RoFormer’s rotational position encoding (RoPE) technique for an efficient implementation of relative position encoding. This approach not only optimizes positional information utilization but also captures syntactic dependency information by constructing a weighted adjacency matrix. During the feature fusion phase, the model employs an entity attention mechanism for a deeper integration of features, effectively addressing the challenge of overlapping entity relationships. Experimental outcomes demonstrate that our model achieves an F1 score of 83.42 on datasets featuring overlapping entity relations, significantly outperforming other baseline models.
非结构化中文医学文本是实体和关系信息的丰富来源。从医学文本中提取实体关系对于构建医学知识图谱和帮助医护人员迅速做出明智决策至关重要。然而，从这些文本中提取实体关系是一项艰巨的挑战，特别是由于实体关系重叠的问题。本研究介绍了一种新颖的提取模型，该模型利用 RoFormer 的旋转位置编码（RoPE）技术有效地实现了相对位置编码。这种方法不仅能优化位置信息的利用，还能通过构建加权邻接矩阵捕捉句法依赖信息。在特征融合阶段，该模型采用了实体关注机制对特征进行深度融合，从而有效地解决了实体关系重叠的难题。实验结果表明，我们的模型在具有重叠实体关系的数据集上取得了 83.42 的 F1 分数，明显优于其他基线模型。
{"title":"RoGraphER: Enhanced Extraction of Chinese Medical Entity Relationships Using RoFormer Pre-Trained Model and Weighted Graph Convolution","authors":"Qinghui Zhang, Yaya Sun, Pengtao Lv, Lei Lu, Mengya Zhang, Jinhui Wang, Chenxia Wan, Jingping Wang","doi":"10.3390/electronics13152892","DOIUrl":"https://doi.org/10.3390/electronics13152892","url":null,"abstract":"Unstructured Chinese medical texts are rich sources of entity and relational information. The extraction of entity relationships from medical texts is pivotal for the construction of medical knowledge graphs and aiding healthcare professionals in making swift and informed decisions. However, the extraction of entity relationships from these texts presents a formidable challenge, notably due to the issue of overlapping entity relationships. This study introduces a novel extraction model that leverages RoFormer’s rotational position encoding (RoPE) technique for an efficient implementation of relative position encoding. This approach not only optimizes positional information utilization but also captures syntactic dependency information by constructing a weighted adjacency matrix. During the feature fusion phase, the model employs an entity attention mechanism for a deeper integration of features, effectively addressing the challenge of overlapping entity relationships. Experimental outcomes demonstrate that our model achieves an F1 score of 83.42 on datasets featuring overlapping entity relations, significantly outperforming other baseline models.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141810513","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 : 2024-07-23DOI: 10.3390/electronics13152897
Wencheng Jiang, Zhenyu Zhao, Zhiyuan Luo, Jie Zhou, Shuzheng Zhang, Bo Hu, Peiyun Bian
Timing Engineering Change Order (ECO) is time-consuming in IC design, requiring multiple rounds of timing analysis. Compared to traditional methods for accelerating timing analysis, which focus on a specific design, timing ECO requires higher accuracy and generalization because the design changes considerably after ECO. Additionally, there are challenges with slow acquisition of data for large designs and insufficient data for small designs. To solve these problems, we propose TSTL-GNN, a novel approach using two-stage transfer learning based on graph structures. Significantly, considering that delay calculation relies on transition time, we divide our model into two stages: the first stage predicts transition time, and the second stage predicts delay. Moreover, we employ transfer learning to transfer the model’s parameters and features from the first stage to the second due to the similar calculation formula for delay and transition time. Experiments show that our method has good accuracy on open-source and industrial applications with an average R2score/MAE of 0.9952/13.36, and performs well with data-deficient designs. Compared to previous work, our model reduce prediction errors by 37.1 ps on the modified paths, which are changed by 24.27% on average after ECO. The stable R2 score also confirms the generalization of our model. In terms of time cost, our model achieved results for path delays consuming up to 80 times less time compared to open-source tool.
{"title":"TSTL-GNN: Graph-Based Two-Stage Transfer Learning for Timing Engineering Change Order Analysis Acceleration","authors":"Wencheng Jiang, Zhenyu Zhao, Zhiyuan Luo, Jie Zhou, Shuzheng Zhang, Bo Hu, Peiyun Bian","doi":"10.3390/electronics13152897","DOIUrl":"https://doi.org/10.3390/electronics13152897","url":null,"abstract":"Timing Engineering Change Order (ECO) is time-consuming in IC design, requiring multiple rounds of timing analysis. Compared to traditional methods for accelerating timing analysis, which focus on a specific design, timing ECO requires higher accuracy and generalization because the design changes considerably after ECO. Additionally, there are challenges with slow acquisition of data for large designs and insufficient data for small designs. To solve these problems, we propose TSTL-GNN, a novel approach using two-stage transfer learning based on graph structures. Significantly, considering that delay calculation relies on transition time, we divide our model into two stages: the first stage predicts transition time, and the second stage predicts delay. Moreover, we employ transfer learning to transfer the model’s parameters and features from the first stage to the second due to the similar calculation formula for delay and transition time. Experiments show that our method has good accuracy on open-source and industrial applications with an average R2score/MAE of 0.9952/13.36, and performs well with data-deficient designs. Compared to previous work, our model reduce prediction errors by 37.1 ps on the modified paths, which are changed by 24.27% on average after ECO. The stable R2 score also confirms the generalization of our model. In terms of time cost, our model achieved results for path delays consuming up to 80 times less time compared to open-source tool.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141811776","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 : 2024-07-23DOI: 10.3390/electronics13152893
Xiaoli He, Bo Zhang, Yuan Long
Offline handwritten Chinese character recognition involves the application of computer vision techniques to recognize individual handwritten Chinese characters. This technology has significantly advanced the research in online handwriting recognition. Despite its widespread application across various fields, offline recognition faces numerous challenges. These challenges include the diversity of glyphs resulting from different writers’ styles and habits, the vast number of Chinese character labels, and the presence of morphological similarities among characters. To address these challenges, an optimization method based on a separated pre-training model was proposed. The method aims to enhance the accuracy and robustness of recognizing similar character images by exploring potential correlations among them. In experiments, the HWDB and Chinese Calligraphy Styles by Calligraphers datasets were employed, utilizing precision, recall, and the Macro-F1 value as evaluation metrics. We employ a convolutional self-encoder model characterized by high recognition accuracy and robust performance. The experimental results demonstrated that the separated pre-training models improved the performance of the convolutional auto-encoder model, particularly in handling error-prone characters, resulting in an approximate 6% increase in precision.
{"title":"Increasing Offline Handwritten Chinese Character Recognition Using Separated Pre-Training Models: A Computer Vision Approach","authors":"Xiaoli He, Bo Zhang, Yuan Long","doi":"10.3390/electronics13152893","DOIUrl":"https://doi.org/10.3390/electronics13152893","url":null,"abstract":"Offline handwritten Chinese character recognition involves the application of computer vision techniques to recognize individual handwritten Chinese characters. This technology has significantly advanced the research in online handwriting recognition. Despite its widespread application across various fields, offline recognition faces numerous challenges. These challenges include the diversity of glyphs resulting from different writers’ styles and habits, the vast number of Chinese character labels, and the presence of morphological similarities among characters. To address these challenges, an optimization method based on a separated pre-training model was proposed. The method aims to enhance the accuracy and robustness of recognizing similar character images by exploring potential correlations among them. In experiments, the HWDB and Chinese Calligraphy Styles by Calligraphers datasets were employed, utilizing precision, recall, and the Macro-F1 value as evaluation metrics. We employ a convolutional self-encoder model characterized by high recognition accuracy and robust performance. The experimental results demonstrated that the separated pre-training models improved the performance of the convolutional auto-encoder model, particularly in handling error-prone characters, resulting in an approximate 6% increase in precision.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141813674","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 : 2024-07-23DOI: 10.3390/electronics13152901
Mintai Kim, Sungju Lee
Natural ventilation is a critical method for reducing energy consumption for heating, cooling, and ventilating buildings. Recent research has focused on utilizing environmental IoT data from both inside and outside buildings for NVR prediction based on a deep learning model. To design an accurate NVR prediction model while considering individual building environments, various knowledge-sharing methods can be applied, such as transfer learning and ensemble models for cross-building prediction. However, the characteristics of learning data and model parameters should be considered when applying transfer learning and ensemble models to predict NVR with different spatial and temporal domains. In this paper, we propose a way to design an NVR prediction model for a cross-building environment by normalizing the training data, selecting transfer learning layers that are well-suited to the data environment, and augmenting NVR knowledge via ensemble methods. Based on the experimental results, we confirm that the proposed knowledge-sharing deep learning approach, while considering the normalizing of training data, the selecting transfer learning layers, and augmenting the NVR knowledge approach, can improve the accuracy up to 11.8% in the two different offices and seasons.
{"title":"Augmenting Knowledge for Individual NVR Prediction in Different Spatial and Temporal Cross-Building Environments","authors":"Mintai Kim, Sungju Lee","doi":"10.3390/electronics13152901","DOIUrl":"https://doi.org/10.3390/electronics13152901","url":null,"abstract":"Natural ventilation is a critical method for reducing energy consumption for heating, cooling, and ventilating buildings. Recent research has focused on utilizing environmental IoT data from both inside and outside buildings for NVR prediction based on a deep learning model. To design an accurate NVR prediction model while considering individual building environments, various knowledge-sharing methods can be applied, such as transfer learning and ensemble models for cross-building prediction. However, the characteristics of learning data and model parameters should be considered when applying transfer learning and ensemble models to predict NVR with different spatial and temporal domains. In this paper, we propose a way to design an NVR prediction model for a cross-building environment by normalizing the training data, selecting transfer learning layers that are well-suited to the data environment, and augmenting NVR knowledge via ensemble methods. Based on the experimental results, we confirm that the proposed knowledge-sharing deep learning approach, while considering the normalizing of training data, the selecting transfer learning layers, and augmenting the NVR knowledge approach, can improve the accuracy up to 11.8% in the two different offices and seasons.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141810223","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 : 2024-07-23DOI: 10.3390/electronics13152908
Dujuan Hu, Li Yang, Xiujun Zhang, Yan Xue, Xizhang Wei, Tairan Lin
This paper provides a comprehensive theoretical derivation of the residual noise power and effective isotropic isolation (EII) signal models in baseband digital cancellation, aperture-level digital cancellation, and beamforming spatial cancellation models in simultaneous transmit and receive (STAR) arrays. We simulated and analyzed the isolation performance and self-interference (SI) noise cancellation of STAR systems using digital SI cancellation (SIC) and beamforming in a 32-element planar array. The simulation results show that in the absence of SIC or baseband digital SIC, the EII obtained by receive adaptive beamforming (ABF) is 20 dB higher than that obtained by transmit ABF. On the basis of aperture-level digital SIC, the EII obtained from transmit ABF and receive ABF is basically the same. The EII obtained by baseband digital SIC is 22.5 dB and 41.1 dB lower than that of transmit ABF and receive ABF, respectively. Therefore, baseband digital SIC technology is not required when using transmit ABF and receive ABF.
本文从理论上全面推导了同步发射和接收（STAR）阵列中基带数字消除、孔径级数字消除和波束成形空间消除模型的残余噪声功率和有效各向同性隔离（EII）信号模型。我们模拟并分析了在 32 元平面阵列中使用数字 SI 消除（SIC）和波束成形的 STAR 系统的隔离性能和自干扰（SI）噪声消除。仿真结果表明，在没有 SIC 或基带数字 SIC 的情况下，接收自适应波束成形（ABF）获得的 EII 比发射 ABF 获得的 EII 高 20 dB。在孔径级数字 SIC 的基础上，发射 ABF 和接收 ABF 获得的 EII 基本相同。基带数字 SIC 获得的 EII 分别比发射 ABF 和接收 ABF 低 22.5 dB 和 41.1 dB。因此，使用发射 ABF 和接收 ABF 时不需要基带数字 SIC 技术。
{"title":"Comparative Analysis of Digital Self-Interference Cancellation Methods for Simultaneous Transmit and Receive Arrays","authors":"Dujuan Hu, Li Yang, Xiujun Zhang, Yan Xue, Xizhang Wei, Tairan Lin","doi":"10.3390/electronics13152908","DOIUrl":"https://doi.org/10.3390/electronics13152908","url":null,"abstract":"This paper provides a comprehensive theoretical derivation of the residual noise power and effective isotropic isolation (EII) signal models in baseband digital cancellation, aperture-level digital cancellation, and beamforming spatial cancellation models in simultaneous transmit and receive (STAR) arrays. We simulated and analyzed the isolation performance and self-interference (SI) noise cancellation of STAR systems using digital SI cancellation (SIC) and beamforming in a 32-element planar array. The simulation results show that in the absence of SIC or baseband digital SIC, the EII obtained by receive adaptive beamforming (ABF) is 20 dB higher than that obtained by transmit ABF. On the basis of aperture-level digital SIC, the EII obtained from transmit ABF and receive ABF is basically the same. The EII obtained by baseband digital SIC is 22.5 dB and 41.1 dB lower than that of transmit ABF and receive ABF, respectively. Therefore, baseband digital SIC technology is not required when using transmit ABF and receive ABF.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141810519","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}
Ferroelectric hafnium and zirconium oxides have recently garnered significant attention due to their potential applications in in-memory computing. In this study, we present an optimized process design for a wake-up free 15 nm thick Hf0.5Zr0.5O2 (HZO) ferroelectric capacitor by fine-tuning the dual-oxygen process and incorporating oxygen annealing after post-metallization annealing (PMA). The optimized approach resulted in a competitive polarization of 28.6 μC/cm2, consistently exceeding 25 μC/cm2 at 3 V after 2 × 107 cycles, showcasing a current density of 3.2 mA/cm2 at 2 V after 105 cycles. The synergistic effect of oxygen vacancies and grain properties (grain size, phase proportion) enables competitive ferroelectric polarization at lower voltages, while the generation of WOx near the top electrode and increased grain size further ensure the reliability of the HZO ferroelectric capacitor. This work presents innovative perspectives for the development of non-volatile devices characterized by low leakage current and low power consumption.
{"title":"Optimal Process Design for Wake-Up Free Hf0.5Zr0.5O2 Ferroelectric Capacitors: Toward Low-Power Devices with Enhanced Ferroelectric Performance","authors":"Hui Wang, Jiabin Qi, Xinyu Xie, Zongfang Liu, Wenhao Wu, Choonghyun Lee","doi":"10.3390/electronics13152895","DOIUrl":"https://doi.org/10.3390/electronics13152895","url":null,"abstract":"Ferroelectric hafnium and zirconium oxides have recently garnered significant attention due to their potential applications in in-memory computing. In this study, we present an optimized process design for a wake-up free 15 nm thick Hf0.5Zr0.5O2 (HZO) ferroelectric capacitor by fine-tuning the dual-oxygen process and incorporating oxygen annealing after post-metallization annealing (PMA). The optimized approach resulted in a competitive polarization of 28.6 μC/cm2, consistently exceeding 25 μC/cm2 at 3 V after 2 × 107 cycles, showcasing a current density of 3.2 mA/cm2 at 2 V after 105 cycles. The synergistic effect of oxygen vacancies and grain properties (grain size, phase proportion) enables competitive ferroelectric polarization at lower voltages, while the generation of WOx near the top electrode and increased grain size further ensure the reliability of the HZO ferroelectric capacitor. This work presents innovative perspectives for the development of non-volatile devices characterized by low leakage current and low power consumption.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141812497","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 : 2024-07-23DOI: 10.3390/electronics13152905
Yifan Lei, Degang Xu
In this study, we study the tracking of the molten metal region in the dross removal process during metal ingot casting, and propose a real-time tracking method based on adaptive feature selection and weighted histogram. This research is highly significant in metal smelting, as efficient molten metal tracking is crucial for effective dross removal and ensuring the quality of metal ingots. Due to the influence of illumination and temperature in the tracking environment, it is difficult to extract suitable features for tracking molten metal during the metal pouring process using industrial cameras. We transform the images captured by the camera into a multi-scale feature space and select the features with the maximum distinction between the molten metal region and its surrounding background for tracking. Furthermore, we introduce a weighted histogram based on the pixel values of the target region into the mean-shift tracking algorithm to improve tracking accuracy. During the tracking process, the target model updates based on changes in the molten metal region across frames. Experimental tests confirm that this tracking method meets practical requirements, effectively addressing key challenges in molten metal tracking and providing reliable support for the dross removal process.
{"title":"Adaptive Real-Time Tracking of Molten Metal Using Multi-Scale Features and Weighted Histograms","authors":"Yifan Lei, Degang Xu","doi":"10.3390/electronics13152905","DOIUrl":"https://doi.org/10.3390/electronics13152905","url":null,"abstract":"In this study, we study the tracking of the molten metal region in the dross removal process during metal ingot casting, and propose a real-time tracking method based on adaptive feature selection and weighted histogram. This research is highly significant in metal smelting, as efficient molten metal tracking is crucial for effective dross removal and ensuring the quality of metal ingots. Due to the influence of illumination and temperature in the tracking environment, it is difficult to extract suitable features for tracking molten metal during the metal pouring process using industrial cameras. We transform the images captured by the camera into a multi-scale feature space and select the features with the maximum distinction between the molten metal region and its surrounding background for tracking. Furthermore, we introduce a weighted histogram based on the pixel values of the target region into the mean-shift tracking algorithm to improve tracking accuracy. During the tracking process, the target model updates based on changes in the molten metal region across frames. Experimental tests confirm that this tracking method meets practical requirements, effectively addressing key challenges in molten metal tracking and providing reliable support for the dross removal process.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141812569","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 : 2024-07-23DOI: 10.3390/electronics13152888
Changgeng Li, Yutao Cheng, Xiaochao Hou
Voltage Source Converter-based High-Voltage Direct Current Transmission (VSC-HVDC) is essential for integrating renewable energy sources and facilitating inter-regional power transmission. This study evaluates the reliability of control and protection devices within these systems, which are crucial for the stable operation of power grids. Humidity significantly affects both the operational conditions and lifespan of these devices. Previous studies, reliant on extensive full-condition fatigue testing, have lacked effective test models and detailed analyses of mechanisms. To address this gap, a humidity diffusion model was developed to comprehensively investigate moisture diffusion mechanisms. Using the insights gained, the Hallberg–Peck model was applied to predict the lifespan of these devices, quantitatively assessing how changes in humidity affect their reliability. This approach employs a stringent failure criterion, leading to a conservative predicted lifespan. This method achieved a prediction accuracy of 85.648% compared to the benchmarks in GB/T 2423.50-2012, validating the accuracy of our model and the effectiveness of our simulation technology under stringent conditions. This research provides vital theoretical data and serves as an essential tool for guiding the precise maintenance of equipment in varying environmental humidity levels.
{"title":"Humidity Diffusion Process Analysis and Life Prediction of a VSC-HVDC Control Protection Device Based on a Finite Element Simulation Method","authors":"Changgeng Li, Yutao Cheng, Xiaochao Hou","doi":"10.3390/electronics13152888","DOIUrl":"https://doi.org/10.3390/electronics13152888","url":null,"abstract":"Voltage Source Converter-based High-Voltage Direct Current Transmission (VSC-HVDC) is essential for integrating renewable energy sources and facilitating inter-regional power transmission. This study evaluates the reliability of control and protection devices within these systems, which are crucial for the stable operation of power grids. Humidity significantly affects both the operational conditions and lifespan of these devices. Previous studies, reliant on extensive full-condition fatigue testing, have lacked effective test models and detailed analyses of mechanisms. To address this gap, a humidity diffusion model was developed to comprehensively investigate moisture diffusion mechanisms. Using the insights gained, the Hallberg–Peck model was applied to predict the lifespan of these devices, quantitatively assessing how changes in humidity affect their reliability. This approach employs a stringent failure criterion, leading to a conservative predicted lifespan. This method achieved a prediction accuracy of 85.648% compared to the benchmarks in GB/T 2423.50-2012, validating the accuracy of our model and the effectiveness of our simulation technology under stringent conditions. This research provides vital theoretical data and serves as an essential tool for guiding the precise maintenance of equipment in varying environmental humidity levels.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141813871","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 : 2024-07-23DOI: 10.3390/electronics13152907
L. H. Lam, Le Khoa Nam, Nguyen Khac Tien Dung, Nguyen Huu Hieu
Currently, renewable energy sources (RESs) are gradually replacing traditional power sources that use fossil fuels. In some countries, such as Vietnam, RESs are developed on a massive scale and are concentrated in some key areas. This causes negative impacts on a power system when its transmission system is not deployed synchronously to release their capacity from these new renewable energy plants. An important challenge today is to ensure frequency stability in power systems with high uncertainty in RES output power. Additionally, the system requires solutions to prevent transmission line overloads during periods when RESs make a substantial contribution to the electricity generation capacity. Therefore, this paper builds an automatic generation control (AGC) system for a two-area power system with high penetration of RESs. This AGC system model aims to maintain system frequency stability amid unpredictable changes in RESs while also ensuring that tie-lines transmit the predetermined power levels to mitigate frequent congestion. By continuously monitoring and adjusting the system’s frequency, the challenges posed by the inherent variability of RESs can be effectively mitigated. The AGC model is simulated on DIgSILENT PowerFactory software and tested with a 106-bus system. The simulation results of this study show that the AGC system operates effectively, ensuring that the frequency returns to the rated value and maintaining the exchange capacity on the tie-lines after occurrences of RES power decrease events.
{"title":"Two-Area Automatic Generation Control for Power Systems with Highly Penetrating Renewable Energy Sources","authors":"L. H. Lam, Le Khoa Nam, Nguyen Khac Tien Dung, Nguyen Huu Hieu","doi":"10.3390/electronics13152907","DOIUrl":"https://doi.org/10.3390/electronics13152907","url":null,"abstract":"Currently, renewable energy sources (RESs) are gradually replacing traditional power sources that use fossil fuels. In some countries, such as Vietnam, RESs are developed on a massive scale and are concentrated in some key areas. This causes negative impacts on a power system when its transmission system is not deployed synchronously to release their capacity from these new renewable energy plants. An important challenge today is to ensure frequency stability in power systems with high uncertainty in RES output power. Additionally, the system requires solutions to prevent transmission line overloads during periods when RESs make a substantial contribution to the electricity generation capacity. Therefore, this paper builds an automatic generation control (AGC) system for a two-area power system with high penetration of RESs. This AGC system model aims to maintain system frequency stability amid unpredictable changes in RESs while also ensuring that tie-lines transmit the predetermined power levels to mitigate frequent congestion. By continuously monitoring and adjusting the system’s frequency, the challenges posed by the inherent variability of RESs can be effectively mitigated. The AGC model is simulated on DIgSILENT PowerFactory software and tested with a 106-bus system. The simulation results of this study show that the AGC system operates effectively, ensuring that the frequency returns to the rated value and maintaining the exchange capacity on the tie-lines after occurrences of RES power decrease events.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141811455","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 : 2024-07-23DOI: 10.3390/electronics13152899
Ying Fang, Yanhua Liu, Aolong Fu, S. Shi, Zhenbin Zhang
Modular multilevel converters (MMCs) have gained widespread adoption in high-voltage direct current (HVDC) transmission due to their high voltage levels, low harmonic content, and high scalability. However, conventional control methods such as finite control set model predictive control (FCS-MPC) suffer from a heavy computational burden and sensitivity to system parameter variations, limiting the performance of MMCs. This paper proposes a data-driven approach based on model-free adaptive control with an event-triggered mechanism that demonstrates superior robustness against parameter mismatches and enhanced dynamic performance in response to sudden output changes. Moreover, the introduction of the event-triggered mechanism effectively reduces redundant operations, decreasing the computational burden and switching losses. Finally, the proposed strategy is validated through a MATLAB/Simulink simulation model.
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