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学者姓名：张逸
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目前污染源企业点多面广,各个企业的生产与治污流程不同,缺乏有效统一的监管指标和预警手段,导致监管困难、实时性差、工作量大等问题,提出一种基于用电数据挖掘的企业环保异常识别方法.首先,采用K-means聚类识别设备运行状态、基于动态时间规整(dynamic time warping,DTW)距离构建企业生产线模型;其次,对历史数据统计进行连续型与间歇型生产线划分、利用傅里叶变换识别生产线的生产周期,建立适合企业的环保工况模型;再次,提出分别针对连续型与间歇型生产线的环保工况识别方法;最后,利用实际污染源企业监测数据验证所提方法的有效性与实用性.目前基于所提方法研发的电力智慧环保平台已在某省得到实际应用,取得了良好成效,为环保部门掌握企业环保情况提供有效的技术手段与数据支撑.
Keyword ：
K-means聚类 K-means聚类 企业环保 企业环保 傅里叶变换 傅里叶变换 动态时间规整(DTW) 动态时间规整(DTW) 用电数据 用电数据 连续型 连续型 间歇型 间歇型
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| GB/T 7714 | 陈锦涛 , 张逸 , 张良羽 et al. 基于用电数据挖掘的企业环保异常识别 [J]. | 电力建设 , 2025 , 46 (2) : 74-87 . |
| MLA | 陈锦涛 et al. "基于用电数据挖掘的企业环保异常识别" . | 电力建设 46 . 2 (2025) : 74-87 . |
| APA | 陈锦涛 , 张逸 , 张良羽 , 宁志毫 . 基于用电数据挖掘的企业环保异常识别 . | 电力建设 , 2025 , 46 (2) , 74-87 . |
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为了解决现有方法无法适用于已投运负荷或需要已知敏感负荷类型等问题,提出一种基于电能质量监测数据的敏感负荷识别方法,以有功功率有效值监测数据为切入点,采用Hodrick-Prescott滤波、滑动均值分段进行电压暂降事件时段划分;利用电压暂降事件前、后的电能质量监测数据变化量构建待处理稳态数据集,通过动态聚类来有效划分各次电压暂降事件;对各暂降事件集进行边界拟合,得到多个拟合拐点,并与预设拐点行比较,完成对用户所含敏感负荷的类型识别.通过MATLAB/Simulink仿真算例和实际敏感用户电能质量监测数据对所提方法进行验证,结果表明所提方法可准确识别交流接触器、变频调速系统、可编程逻辑控制器、个人计算机这4种典型敏感负荷,能有效利用稳态电能质量监测数据与电压暂降事件数据进行综合分析,具有成本低、可实施性强的优点.
Keyword ：
VTC拐点拟合 VTC拐点拟合 动态K-means聚类 动态K-means聚类 敏感负荷识别 敏感负荷识别 电压暂降 电压暂降 电能质量监测数据 电能质量监测数据
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| GB/T 7714 | 张逸 , 张良羽 , 陈锦涛 et al. 基于电能质量监测数据的电压暂降敏感负荷识别 [J]. | 电力自动化设备 , 2025 , 45 (2) : 176-184 . |
| MLA | 张逸 et al. "基于电能质量监测数据的电压暂降敏感负荷识别" . | 电力自动化设备 45 . 2 (2025) : 176-184 . |
| APA | 张逸 , 张良羽 , 陈锦涛 , 姚文旭 , 陈敏 . 基于电能质量监测数据的电压暂降敏感负荷识别 . | 电力自动化设备 , 2025 , 45 (2) , 176-184 . |
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In order to address issues such as the existing methods are not applicable to operational loads or require knowledge of sensitive load types，a sensitive load identification method based on power quality monitoring data is proposed. Taking the monitoring data of active power root-mean-square value as the entry point，the Hodrick-Prescott filtering and sliding mean segmentation are used to divide the period of transient voltage sag events. The steady-state dataset is constructed based on the variation of power quality monitoring data before and after the transient voltage sag events，and dynamic clustering is used to effectively divide various transient voltage sag events. Finally，the voltage tolerance curves of each action area are fitted and compared with the preset curves to complete the type of identification of the sensitive load contained by the user. Through MATLAB／Simulink simulation examples and actual sensitive user power quality monitoring data，it is proved that the proposed method can accurately identify four typical sensitive loads such as AC contactor，adjustable speed drive，programable logic controller and personal computer，and can effectively use steady-state power quality monitoring data and voltage sag event data for comprehensive analysis，which has the advantages of low cost and strong implementation. © 2025 Electric Power Automation Equipment Press. All rights reserved.
Keyword ：
MATLAB MATLAB Personal computers Personal computers Power quality Power quality Programmable logic controllers Programmable logic controllers Transient analysis Transient analysis
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| GB/T 7714 | Zhang, Yi , Zhang, Liangyu , Chen, Jintao et al. Voltage sag-sensitive load identification based on power quality monitoring data [J]. | Electric Power Automation Equipment , 2025 , 45 (2) : 176-184 . |
| MLA | Zhang, Yi et al. "Voltage sag-sensitive load identification based on power quality monitoring data" . | Electric Power Automation Equipment 45 . 2 (2025) : 176-184 . |
| APA | Zhang, Yi , Zhang, Liangyu , Chen, Jintao , Yao, Wenxu , Chen, Min . Voltage sag-sensitive load identification based on power quality monitoring data . | Electric Power Automation Equipment , 2025 , 45 (2) , 176-184 . |
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| GB/T 7714 | Zhang, Yi . Special Issue: Advanced Technologies in Power Quality and Power Disturbance Data Application [J]. | SYMMETRY-BASEL , 2025 , 17 (2) . |
| MLA | Zhang, Yi . "Special Issue: Advanced Technologies in Power Quality and Power Disturbance Data Application" . | SYMMETRY-BASEL 17 . 2 (2025) . |
| APA | Zhang, Yi . Special Issue: Advanced Technologies in Power Quality and Power Disturbance Data Application . | SYMMETRY-BASEL , 2025 , 17 (2) . |
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The gradual increase in the penetration rate of distributed renewable energy has become a new situation. Under the new situation, industrial users with high energy consumption need to make reasonable decisions in electricity and carbon markets while ensuring power quality. This is a real problem that needs to be solved for high energy consumption industrial users. Therefore, we propose a decision model for industrial users participating in electricity and carbon markets considering differentiated power quality based on information gap decision theory (IGDT). Firstly, we analyze the impact of users' installation of distributed renewable energy on their power quality and carbon emissions. Considering the differentiated power quality services in the future electricity market, the carbon emissions when the user chooses different levels of power quality are quantified. Secondly, a decision-making model of industrial users participating in electricity market and carbon market considering differentiated power quality services is established. The objective function is the maximum profit of the user participating in the double market trading performance period. Thirdly, the IGDT theory is used to describe the uncertainty of distributed renewable energy generation, which reduces the decision-making risk of industrial users. Finally, we take a steel production enterprise as an example to analyze. The numerical results show that the proposed model can reduce carbon emissions and obtain maximum benefits for industrial users. The proposed model can realize the coordination and optimization of monthly electricity purchase and carbon quota trading volume. Moreover, it can help industrial users rationally arrange the access capacity of distributed renewable energy devices and select the improved power quality level.
Keyword ：
Carbon market Carbon market Distributed renewable energy Distributed renewable energy Electricity market Electricity market Industrial users Industrial users Power quality Power quality
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| GB/T 7714 | Zhang, Yi , Xiang, Mengru , Zheng, Zonghua . An IGDT-based decision model for industrial users participating in electricity and carbon markets considering differentiated power quality services [J]. | ENERGY , 2025 , 315 . |
| MLA | Zhang, Yi et al. "An IGDT-based decision model for industrial users participating in electricity and carbon markets considering differentiated power quality services" . | ENERGY 315 (2025) . |
| APA | Zhang, Yi , Xiang, Mengru , Zheng, Zonghua . An IGDT-based decision model for industrial users participating in electricity and carbon markets considering differentiated power quality services . | ENERGY , 2025 , 315 . |
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Electricity theft detection is very important for the economic benefits of power companies and the effectiveness of safe operation of power systems. At present, the traditional power theft detection method can only identify whether the user has power theft, but cannot perform rapid and accurate inspections for various types of power theft users. Aiming at the characteristics of medium-voltage users with large power consumption and regular power consumption, this paper proposed a method for detecting the type of power theft in medium-voltage distribution lines based on robust regression and convolutional neural network. Firstly, considering the existence of abnormal data due to factors such as communication delay interruption, a robust regression algorithm is used to reduce its impact and improve the accuracy of regression analysis. Secondly, the correction coefficient and error term of each user obtained by regression are taken as the characteristics of user stealing electricity, and input into the convolutional neural network model for training to complete the identification of stealing electricity type. Finally, the method is verified by simulation and measured data. The results show that under different disturbance conditions, the proposed method can accurately identify different types of power stealing behaviors, which can better assist on-site investigation, narrow the investigation scope and improve the verification rate. © 2024 The Author(s)
Keyword ：
Convolution Convolution Convolutional neural networks Convolutional neural networks Electric power utilization Electric power utilization Electric utilities Electric utilities Power quality Power quality Regression analysis Regression analysis Smart meters Smart meters Voltage distribution measurement Voltage distribution measurement
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| GB/T 7714 | Yi, Zhang , Min, Chen , Yang, Zou et al. Detection of medium-voltage electricity theft types based on robust regression and convolutional neural network [J]. | International Journal of Electrical Power and Energy Systems , 2024 , 160 . |
| MLA | Yi, Zhang et al. "Detection of medium-voltage electricity theft types based on robust regression and convolutional neural network" . | International Journal of Electrical Power and Energy Systems 160 (2024) . |
| APA | Yi, Zhang , Min, Chen , Yang, Zou , Rong, Xin , Chen, Gao , Hua, Lin . Detection of medium-voltage electricity theft types based on robust regression and convolutional neural network . | International Journal of Electrical Power and Energy Systems , 2024 , 160 . |
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Renewable energy has developed rapidly in Ningxia, and it has become the first provincial power system in China whose renewable energy power generation output exceeds the power load of the whole region. The access of a high proportion of renewable energy puts forward higher requirements for the peak-shaving capacity of the Ningxia power system. In order to solve the problem of calculating the peak-shaving cost in the key scenarios of renewable energy development in Ningxia, a quantitative model of the peak-shaving cost of the power system considering time-of-use price is proposed. We take Ningxia power system as an example to study. First, the key scenarios of the Ningxia power system peak-shaving are obtained, and the technical cost characteristic boundaries of various peak-shaving resources are determined. Second, according to the characteristics of typical daily renewable energy and load in Ningxia, the quantification model of the power system peak-shaving cost is established. The model takes the minimum total cost of the power system as the objective function and considers the constraints such as technical output of thermal power units, charge-discharge characteristics of energy storage and time-of-use price mechanism. Finally, the model is solved and the peak-shaving cost and unit output under the optimal scheme are obtained. This example shows that the model can effectively evaluate the peak-shaving cost and unit output of the Ningxia power system under the key scenarios of peak-shaving. © 2024
Keyword ：
Energy storage Energy storage Fossil fuel power plants Fossil fuel power plants Renewable energy Renewable energy Sustainable development Sustainable development
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| GB/T 7714 | Xiang, Mengru , Zhang, Yi , Li, Chuandong et al. Peak-shaving cost of power system in the key scenarios of renewable energy development in China: Ningxia case study [J]. | Journal of Energy Storage , 2024 , 91 . |
| MLA | Xiang, Mengru et al. "Peak-shaving cost of power system in the key scenarios of renewable energy development in China: Ningxia case study" . | Journal of Energy Storage 91 (2024) . |
| APA | Xiang, Mengru , Zhang, Yi , Li, Chuandong , Qi, Caijuan . Peak-shaving cost of power system in the key scenarios of renewable energy development in China: Ningxia case study . | Journal of Energy Storage , 2024 , 91 . |
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The equivalent impedance parameters of loads have been widely used to identify and locate the harmonic sources. However, the existing calculation methods suffer from outliers caused by the zero-crossing of the denominator. These outliers can result in inaccuracy and unreliability of harmonic source location. To address this issue, this paper proposes an innovative method of equivalent impedance parameter calculation of three-phase symmetrical loads that avoid outliers. The correctness and effectiveness of the proposed method are verified by simulations on Simulink using actual monitoring data. The results show that the proposed method is not only simple and easy to implement but also highly accurate.
Keyword ：
equivalent impedance parameters of load equivalent impedance parameters of load Harmonic analysis Harmonic analysis harmonic source location harmonic source location Impedance Impedance Load modeling Load modeling nonlinear load nonlinear load Parameter estimation Parameter estimation Position measurement Position measurement power quality power quality Power system harmonics Power system harmonics Time-domain analysis Time-domain analysis
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| GB/T 7714 | Zhang, Yi , Liu, Bijie , Lin, Caihua et al. Equivalent Impedance Parameter Calculation of Three-Phase Symmetrical Loads for Harmonic Source Location [J]. | JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY , 2024 , 12 (1) : 251-260 . |
| MLA | Zhang, Yi et al. "Equivalent Impedance Parameter Calculation of Three-Phase Symmetrical Loads for Harmonic Source Location" . | JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY 12 . 1 (2024) : 251-260 . |
| APA | Zhang, Yi , Liu, Bijie , Lin, Caihua , Shao, Zhenguo , Xu, Yuncong . Equivalent Impedance Parameter Calculation of Three-Phase Symmetrical Loads for Harmonic Source Location . | JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY , 2024 , 12 (1) , 251-260 . |
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针对传统谐波源辨识方法无法实现工业用户谐波源具体类型的非侵入式识别的问题,该文提出一种基于盲源分离的工业谐波源负荷分类识别方法.该方法仅依据工业用户进线处电压、电流数据即可实现谐波源负荷具体类型的非侵入式识别.首先,从负荷等值阻抗模型入手,建立工业用户多负荷等值阻抗并联电路模型;其次,采用集合经验模态分解与奇异值分解相结合的方法确定构成用户进线处监测点综合等值阻抗信号的源阻抗信号数目;然后,采用快速独立分量分析实现将谐波源负荷等值阻抗信号从综合负荷等值阻抗信号中分离;最后,将分离出谐波源负荷等值阻抗信号频率特征与典型谐波源负荷进行匹配,进而实现分类识别.仿真与实测实验结果均表明,所提方法能够准确识别工业用户所含多种谐波源负荷的具体类型,具有较好的可行性和实用性.
Keyword ：
源信号数目估计 源信号数目估计 盲源分离 盲源分离 谐波源识别 谐波源识别 负荷等值阻抗 负荷等值阻抗
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| GB/T 7714 | 张逸 , 陈书畅 , 刘必杰 et al. 基于盲源分离的工业谐波源负荷分类识别方法 [J]. | 中国电机工程学报 , 2024 , 44 (10) : 3850-3861,中插9 . |
| MLA | 张逸 et al. "基于盲源分离的工业谐波源负荷分类识别方法" . | 中国电机工程学报 44 . 10 (2024) : 3850-3861,中插9 . |
| APA | 张逸 , 陈书畅 , 刘必杰 , 林才华 . 基于盲源分离的工业谐波源负荷分类识别方法 . | 中国电机工程学报 , 2024 , 44 (10) , 3850-3861,中插9 . |
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Accurate ultra-short-term power prediction for wind farms is challenging under rapid wind speed fluctuations, complicating production planning and power balancing. This paper proposes a new method considering spatial and temporal correlations of wind fluctuations among adjacent wind farms. The method first calculates the time difference between power fluctuations based on wind speed, direction, and relative positions, determining the prior information period. The variational Bayesian model is then used to extract implicit relationships between power fluctuations of adjacent wind farms, enabling power prediction during the prior information period. Finally, the non-prior information period is predicted to complete the ultra-short-term power prediction. Using measured data from three wind farms in Fujian Province, compared to other models, the method demonstrates improved accuracy by effectively leveraging the power fluctuation characteristics of adjacent wind farms, and it has a certain amount of generalizability.
Keyword ：
adjacent wind farms adjacent wind farms prior information period prior information period spatial-temporal correlation spatial-temporal correlation ultra-short-term output prediction ultra-short-term output prediction variational Bayesian model variational Bayesian model
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| GB/T 7714 | Li, Chuandong , Zhang, Minghui , Zhang, Yi et al. Ultra-Short-Term Wind Farm Power Prediction Considering Correlation of Wind Power Fluctuation [J]. | SENSORS , 2024 , 24 (20) . |
| MLA | Li, Chuandong et al. "Ultra-Short-Term Wind Farm Power Prediction Considering Correlation of Wind Power Fluctuation" . | SENSORS 24 . 20 (2024) . |
| APA | Li, Chuandong , Zhang, Minghui , Zhang, Yi , Yi, Ziyuan , Niu, Huaqing . Ultra-Short-Term Wind Farm Power Prediction Considering Correlation of Wind Power Fluctuation . | SENSORS , 2024 , 24 (20) . |
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