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学者姓名：黄奕钒
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Abstract ：
针对静电荷逃逸电子式电压互感器(electronic voltage transducer,EVT)电场边缘效应引入的附加电容影响其测量准确性的问题,提出一种粒子群优化算法(particle swarm optimization,PSO)、风驱动优化算法(wind driven optimization,WDO)、最小二乘支持向量机(least squares support vector machine,LSSVM)结合的电场优化方法.首先,采用WDO-LSSVM构建描述EVT电场分布的数学模型,其中用WDO优化LSSVM的参数选择.其次,采用PSO算法求解上述数学模型,获得EVT电场分布最优时的物理参数组合.同时,提出一种电极结构优化方法,将电极边缘切削成圆弧或斜面以改善电场局部集中现象.最后,采用COMSOL仿真软件构建EVT的三维模型,对EVT进行电流-电路耦合场仿真.仿真结果表明,所提方法减小了边缘效应引入的附加电容和EVT的测量误差.
Keyword ：
COMSOL仿真 COMSOL仿真 人工智能算法 人工智能算法 电场优化 电场优化 电子式电压互感器 电子式电压互感器 结构改进 结构改进
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| GB/T 7714 | 黄星童 , 黄奕钒 , 徐启峰 . 静电荷逃逸电子式电压互感器的电场优化方法 [J]. | 福州大学学报（自然科学版） , 2024 , 52 (5) : 536-543 . |
| MLA | 黄星童 等. "静电荷逃逸电子式电压互感器的电场优化方法" . | 福州大学学报（自然科学版） 52 . 5 (2024) : 536-543 . |
| APA | 黄星童 , 黄奕钒 , 徐启峰 . 静电荷逃逸电子式电压互感器的电场优化方法 . | 福州大学学报（自然科学版） , 2024 , 52 (5) , 536-543 . |
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The development of electrical measurement technology has brought high latitude residential electricity consumption data to power companies, which contains the characteristics of users' electricity consumption behavior and provides data support for the behavior classification. In order to improve the efficiency of data feature extraction and the accuracy of electricity consumption behavior identification, a classification model based on sparse denoising autoencoder feature dimensionality reduction and spectral clustering is proposed in this paper. Firstly, the sparse denoising autoencoder (SDAE) and the manually defining electricity consumption characteristic indicators are deployed to extract features from the residential daily electricity consumption data, and then the spectral clustering is employed to classify the extracted electricity consumption characteristics. Secondly, the t-distributed stochastic neighbor embedding (t-SNE) is applied to visualize and analyze the classification results, and on this basis, the secondary classification is implemented to fix the issue of the confused electricity consumption behaviors. Finally, the typical consumption behavior curves are calculated by Gaussian distance weighting method, and the characteristics of power consumption behavior are analyzed and summarized. The proposed approach is evaluated and verified by using the electricity dataset in Fujian, China.
Keyword ：
Autoencoder Autoencoder Clustering Clustering Electricity consumption behavior classification Electricity consumption behavior classification Feature extraction Feature extraction Secondary classification Secondary classification
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| GB/T 7714 | Huang, Yifan , Yao, Zhengnan , Xu, Qifeng . Classification model of electricity consumption behavior based on sparse denoising autoencoder feature dimensionality reduction and spectral clustering [J]. | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS , 2024 , 158 . |
| MLA | Huang, Yifan 等. "Classification model of electricity consumption behavior based on sparse denoising autoencoder feature dimensionality reduction and spectral clustering" . | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 158 (2024) . |
| APA | Huang, Yifan , Yao, Zhengnan , Xu, Qifeng . Classification model of electricity consumption behavior based on sparse denoising autoencoder feature dimensionality reduction and spectral clustering . | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS , 2024 , 158 . |
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The insulation method of traditional electromagnetic current transformers (CTs) is single-stage insulated, and the insulation materials include oil, SF6 gas, polytetrafluoroethylene (PTFE) film, and epoxy resin. It has to deploy multiple capacitive screens for voltage equalization to improve the electric field distribution, which results in complex insulation structure and high cost. A multistage dry insulated CT for measurement is proposed in this article, which is composed of multistage CTs in series and insulated by epoxy resin, so the line voltage is shared by the multistage CTs. Therefore, a five-stage prototype CT is analyzed and designed, and the structure, the measurement principle, the electric field distribution, the technical characteristics, and the error calculation and compensation of this CT are explored. The results show that the proposed dry CT meets the 0.2S class accuracy and has advantages of low insulation cost, high safety, environmental protection, and so on.
Keyword ：
Current transformers Current transformers Dry insulated Dry insulated electric field distribution electric field distribution Electric fields Electric fields electromagnetic current transformer (CT) electromagnetic current transformer (CT) Epoxy resins Epoxy resins Insulation Insulation Magnetic cores Magnetic cores multistage multistage Oils Oils Windings Windings
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| GB/T 7714 | Xu, Qifeng , Zhang, Junfeng , Huang, Yifan et al. A Multistage Dry Insulated Current Transformer [J]. | IEEE SENSORS JOURNAL , 2023 , 23 (5) : 5339-5344 . |
| MLA | Xu, Qifeng et al. "A Multistage Dry Insulated Current Transformer" . | IEEE SENSORS JOURNAL 23 . 5 (2023) : 5339-5344 . |
| APA | Xu, Qifeng , Zhang, Junfeng , Huang, Yifan , Tan, Qiao . A Multistage Dry Insulated Current Transformer . | IEEE SENSORS JOURNAL , 2023 , 23 (5) , 5339-5344 . |
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The J-A hysteresis theory is widely used in the modeling of magnetic characteristics of electromagnetic current transformers (CTs), but there is a large error in the model when considering the harmonics excitation, and unfortunately, the harmonic pollution in modern power grids is becoming more and more serious. Considering that the nonlinearity error of the CT for measurement is less than 0.2S, that is, the ratio error at 100% rated current is <0.2%, and the phase error is <10 ', the correction of the magnetic characteristics of each harmonic is approximately applicable to the principle of linear superposition. Therefore, this article uses the dung beetle algorithm (DBA) to identify the parameters, corrects the J-A model parameters for each harmonic, and then linearly superimposes the magnetic characteristics of each harmonic to realize the magnetic characteristics modeling. Taking the 0.2S permalloy core CT as an example, the simulation analysis and experimental results show that the proposed method can accurately reflect the transmission characteristics of the CT at harmonic excitation. The approximate linear superposition of the multiple harmonics magnetic characteristics introduces a ratio error of 0.01% and a phase error of 0.5 ', and its influence can be ignored, thus confirming that the correction method is reasonable and effective.
Keyword ：
Dung beetle algorithm (DBA) Dung beetle algorithm (DBA) electromagnetic current transformer (CT) electromagnetic current transformer (CT) harmonics harmonics J-A hysteresis model J-A hysteresis model linear superposition linear superposition
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| GB/T 7714 | Xu, Qifeng , He, Yulong , Huang, Yifan et al. Harmonics Correction of J-A Hysteresis Model [J]. | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2023 , 72 . |
| MLA | Xu, Qifeng et al. "Harmonics Correction of J-A Hysteresis Model" . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 72 (2023) . |
| APA | Xu, Qifeng , He, Yulong , Huang, Yifan , Xiao, Xianbo , Tan, Qiao . Harmonics Correction of J-A Hysteresis Model . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2023 , 72 . |
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Abstract ：
User electricity data contains the characteristics of residential users' electricity consumption behavior. In order to help power companies formulate demand response plans and time of use electricity prices, and better extract electricity consumption behavior characteristics, this paper proposes an electricity consumption behavior classification model based on sparse denoising autoencoder (SDAE) feature dimensionality reduction and K-means clustering. Firstly, sparse denoising autoencoder is used to learn features, and K-means clustering is used for classification. Visualize the classification results using the t-distributed stochastic neighbor embedding (t-SNE) method, calculate typical user curves using Gaussian distance weighting, and analyze the characteristics of the electricity consumption curve. The effectiveness of the proposed method was verified by calculating and comparing the clustering indicators of other common dimensionality reduction methods. © 2023 IEEE.
Keyword ：
Classification (of information) Classification (of information) Electric loads Electric loads Electric power utilization Electric power utilization Electric utilities Electric utilities Housing Housing K-means clustering K-means clustering Learning systems Learning systems Reduction Reduction Stochastic systems Stochastic systems
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| GB/T 7714 | Yao, Zhengnan , Wei, Feishen , Huang, Yifan . Residential Electricity Behavior Classification Model Based on Sparse Denoising Autoencoder And K-Means [C] . 2023 : 506-510 . |
| MLA | Yao, Zhengnan et al. "Residential Electricity Behavior Classification Model Based on Sparse Denoising Autoencoder And K-Means" . (2023) : 506-510 . |
| APA | Yao, Zhengnan , Wei, Feishen , Huang, Yifan . Residential Electricity Behavior Classification Model Based on Sparse Denoising Autoencoder And K-Means . (2023) : 506-510 . |
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The proportion of electric maloperation accidents (EMAs) in substations caused by human and organizational factors (HOFs) has gradually increased. Although there has been some research into the factors affecting EMAs in substations, the available results are insufficient to support the interpretation of HOFs in EMAs. This article explores the relationships between the HOFs and EMAs using Human Factors Analysis and Classification System-gradient boosting with categorical features support (HFACS-CatBoost) and Shapley Additive exPlanation (SHAP) methods. First, the HFACS framework was introduced to identify 135 EMAs in the Southern Power Grid risk causation. CatBoost was used to construct an accident classification model to analyze the important relationship between accidents and HOFs and to compare and analyze with the extreme gradient boosting (XGBoost) and the binary logistic regression (BLR) to verify the superiority of CatBoost. Finally, to solve the problem of inadequate interpretation of the CatBoost black-box model, the SHAP value plot was applied to express the contribution degree relationship between accidents and HOFs. The results show that the above method can explore and explain the importance and contribution of HOFs in EMAs. And from this, it is concluded that poor psychological state, poor communication and coordination, inadequate supervision, and inadequate training and education are highly correlated with the occurrence of EMAs. The findings will help substation operations and maintenance staff to develop safety measures to address the confusion of HOFs in substations and prevent the occurrence of EMAs.
Keyword ：
CatBoost CatBoost electric maloperation accidents electric maloperation accidents human and organization factors human and organization factors Human Factors Analysis and Classification System Human Factors Analysis and Classification System SHAP SHAP
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| GB/T 7714 | Lin, Chuan , Xu, Qifeng , Huang, Yifan . Quantifying and comparing the effects of human and organizational factors in electric maloperation accidents with HFACS-CatBoost and SHAP [J]. | HUMAN FACTORS AND ERGONOMICS IN MANUFACTURING & SERVICE INDUSTRIES , 2022 , 33 (2) : 164-183 . |
| MLA | Lin, Chuan et al. "Quantifying and comparing the effects of human and organizational factors in electric maloperation accidents with HFACS-CatBoost and SHAP" . | HUMAN FACTORS AND ERGONOMICS IN MANUFACTURING & SERVICE INDUSTRIES 33 . 2 (2022) : 164-183 . |
| APA | Lin, Chuan , Xu, Qifeng , Huang, Yifan . Quantifying and comparing the effects of human and organizational factors in electric maloperation accidents with HFACS-CatBoost and SHAP . | HUMAN FACTORS AND ERGONOMICS IN MANUFACTURING & SERVICE INDUSTRIES , 2022 , 33 (2) , 164-183 . |
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An electronic voltage transducer (EVT) based on electrostatic charge escape is proposed in this article. Its working principle is to apply the electric field (or voltage) to the electrostatic charges of the electrode, and the electrostatic charges are forced to escape directionally to form an escape current, so the voltage measurement can be achieved by detecting the escape current. Based on Gauss's theorem and dielectric polarization principle, the mathematical models of the new EVT's power frequency characteristics, harmonic transfer characteristics, and transient response characteristics are studied. And the COMSOL multiphysics coupling simulation is employed to verify these characteristics. The simulation shows that the new EVT can linearly transform the primary voltage, realize harmonic measurement, and have a satisfactory transient response. Finally, the experiment verification system is established to examine the new EVT. And the result demonstrates that the EVT has a 0.5 class accuracy, and enables it to accurately reflect the characteristics of harmonics and impulse voltage.
Keyword ：
COMSOL simulation COMSOL simulation Electrodes Electrodes electronic voltage transducer (EVT) electronic voltage transducer (EVT) electrostatic charge escape electrostatic charge escape Electrostatics Electrostatics escape current escape current Harmonic analysis Harmonic analysis linear measurement linear measurement Mathematical models Mathematical models Temperature measurement Temperature measurement Transducers Transducers Voltage measurement Voltage measurement
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| GB/T 7714 | Xu, Qifeng , Dong, Chunlin , Huang, Yifan . An Electronic Voltage Transducer Based on Electrostatic Charge Escape [J]. | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2022 , 71 . |
| MLA | Xu, Qifeng et al. "An Electronic Voltage Transducer Based on Electrostatic Charge Escape" . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 71 (2022) . |
| APA | Xu, Qifeng , Dong, Chunlin , Huang, Yifan . An Electronic Voltage Transducer Based on Electrostatic Charge Escape . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2022 , 71 . |
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Human reliability analysis (HRA) is a proactive approach to model and evaluate systematic human errors and has been extensively implemented in various complicated systems. The assessment of human errors relies heavily on the knowledge and experience of experts in real-world cases. Moreover, there are usually specific sorts of uncertainty while experts use linguistic labels to evaluate human failure events. In this context, this paper seeks to establish a new model based on the hesitant fuzzy matrix (HFM) and the cognitive reliability and error analysis method (CREAM) to conduct a quantitative analysis of human errors. This model handles the multiple crisp scores of the common performance conditions (CPCs) given by experts according to the context description in terms of CPCs, determines the weights of CPCs by the HFM, and elicits the human error probability (HEP) point estimation formula considering consequences based on the CREAM. Finally, the effectiveness and practicality of the presented HFM-CREAM model are demonstrated through the emergency response analysis of the steam generator tube rupture (SGTR) in nuclear power plant.
Keyword ：
cognitive reliability and error analysis method (CREAM) cognitive reliability and error analysis method (CREAM) hesitant fuzzy matrix (HFM) hesitant fuzzy matrix (HFM) human error probability (HEP) human error probability (HEP) human reliability human reliability the common performance conditions (CPCs) the common performance conditions (CPCs)
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| GB/T 7714 | Lin, Chuan , Xu, Qi Feng , Huang, Yi Fan . An HFM-CREAM model for the assessment of human reliability and quantification [J]. | QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL , 2022 , 38 (5) : 2372-2387 . |
| MLA | Lin, Chuan et al. "An HFM-CREAM model for the assessment of human reliability and quantification" . | QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL 38 . 5 (2022) : 2372-2387 . |
| APA | Lin, Chuan , Xu, Qi Feng , Huang, Yi Fan . An HFM-CREAM model for the assessment of human reliability and quantification . | QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL , 2022 , 38 (5) , 2372-2387 . |
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Human and organizational factors (HOFs) play an important role in electric misoperation accidents (EMAs), but research into the reliability of human factors is still in its infancy in the field of EMAs, and further investment in research is urgently required. To analyze the HOFs in EMAs, a hybrid method including the Human Factors Analysis and Classification System (HFACS) and fuzzy fault tree analysis (FFTA) was applied to EMAs for the first time in the paper. HFACS is used to identify and classify the HOFs with 135 accidents, reorganized as basic events (BEs), intermediate events (IEs), and top event (TE), and develop the architecture of fault tree (FT). Fuzzy aggregation is employed to address experts' expressions and obtain the failure probabilities of the BEs and the minimal cut sets (MCSs) of the FT. The approach generates BEs failure probabilities without reliance on quantitative historical failure statistics of EMAs via qualitative records processing. The FFTA-HFACS model is applied for quantitative analysis of the probability of failure of electrical mishaps and the interaction between accident risk factors. It can assist professionals in deciding whether and where to take preventive or corrective actions and assist in knowledgeable decision-making around the electric operation and maintenance process. Finally, applying this hybrid method to EMAs, the results show that the probability of an EMAs is 1.0410 x 10(-2), which is a risk level that is likely to occur and must be controlled. Two of the most important risk factors are habitual violations and supervisory violation; a combination of risk factors of inadequate work preparation and paralysis, and irresponsibility on the part of employees are also frequent errors.
Keyword ：
electric misoperation accidents electric misoperation accidents failure probability failure probability fuzzy fault tree analysis fuzzy fault tree analysis human and organization factors human and organization factors human factors analysis and classification system human factors analysis and classification system
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| GB/T 7714 | Lin, Chuan , Xu, Qifeng , Huang, Yifan . Applications of FFTA-HFACS for Analyzing Human and Organization Factors in Electric Misoperation Accidents [J]. | APPLIED SCIENCES-BASEL , 2021 , 11 (19) . |
| MLA | Lin, Chuan et al. "Applications of FFTA-HFACS for Analyzing Human and Organization Factors in Electric Misoperation Accidents" . | APPLIED SCIENCES-BASEL 11 . 19 (2021) . |
| APA | Lin, Chuan , Xu, Qifeng , Huang, Yifan . Applications of FFTA-HFACS for Analyzing Human and Organization Factors in Electric Misoperation Accidents . | APPLIED SCIENCES-BASEL , 2021 , 11 (19) . |
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为解释全国电力安全事故的演化规律并为预控事故的发生,提出电力安全事故事理图谱的构建与推演方法.以国家能源局发布的全国电力安全生产情况为数据源,使用规则模板提取事件槽对;利用Word2vec训练词向量,通过事件槽相似度计算泛化事件槽,并以热力图矩阵记录泛化权重;采用Neo4j构建事故事理图谱,以泛化权重和事件链的方向预测事故走向.结果表明:方法能够较好地揭示事故演化的关键节点、预演电力安全事故发展路径,为事故的预控提供1种有效的知识服务方案.
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| GB/T 7714 | 林穿 , 徐启峰 , 黄奕钒 . 基于事理图谱的电力安全事故预控方法 [J]. | 中国安全生产科学技术 , 2021 , 17 (10) : 39-45 . |
| MLA | 林穿 et al. "基于事理图谱的电力安全事故预控方法" . | 中国安全生产科学技术 17 . 10 (2021) : 39-45 . |
| APA | 林穿 , 徐启峰 , 黄奕钒 . 基于事理图谱的电力安全事故预控方法 . | 中国安全生产科学技术 , 2021 , 17 (10) , 39-45 . |
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