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学者姓名：张逸
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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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| 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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Implementing nonintrusive load monitoring (NILM) for industrial consumers plays a vital role in managing power demand and enhancing energy utilization efficiency. Focusing on the scarcity of sampling data and continuous variation of loads in industrial settings, this article proposes a nonintrusive industrial load decomposition (LD) method that considers the load power consumption characteristics and time series correlation. According to the time-varying characteristics of the power consumption, the load is divided into three types including switching load, multi state load, and continuously varying load. On this basis, the active and reactive power characteristics are jointly considered, and integer programming is used to build the load decomposition model. Particularly, the matrix factorization (MF) method is used to describe the continuously varying load. In addition, the timing correlation constraints under the base vector grouping constraint and production process constraints are proposed and integrated into the load decomposition model. Finally, the proposed method is validated on a public dataset using a PC platform and a Raspberry Pi 5, respectively. The results of the tests on the PC platform show that the proposed method has higher accuracy than the existing methods.
Keyword ：
Correlation Correlation Data models Data models Industrial loads Industrial loads integer programming integer programming Libraries Libraries Load modeling Load modeling Load monitoring Load monitoring matrix factorization (MF) matrix factorization (MF) nonintrusive load monitoring (NILM) nonintrusive load monitoring (NILM) Optimization Optimization power characteristics power characteristics Power demand Power demand Production Production Switches Switches Timing Timing timing correlation timing correlation
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| GB/T 7714 | Zhang, Yi , Chen, Jintao , Li, Chuandong et al. Nonintrusive Industrial Load Monitoring Considering Load Power Characteristics and Timing Correlation [J]. | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2025 , 74 . |
| MLA | Zhang, Yi et al. "Nonintrusive Industrial Load Monitoring Considering Load Power Characteristics and Timing Correlation" . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 74 (2025) . |
| APA | Zhang, Yi , Chen, Jintao , Li, Chuandong , Zhang, Liangyu , Sun, Shouquan . Nonintrusive Industrial Load Monitoring Considering Load Power Characteristics and Timing Correlation . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2025 , 74 . |
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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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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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Abstract ：
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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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 transmission network is generally considered as three-phase balanced, while the consideration of threephase unbalance is mainly on distribution networks. However, with the increasingly interconnection of renewable energy, such as wind energy, onto transmission networks, non-adoption of commutation long transmission lines usually results in unbalanced line parameters. Therefore, developing reliable three-phase power flow algorithms for transmission and distribution (T&D) systems becomes more and more important for the reliable and safe operation of emerging power systems. Among the many three-phase power flow algorithms, Newton Raphson method (NRM) and its variants occupy a large share, due to their ability in dealing with multiple sources and looped sub-networks. However, they are sensitive to the initial value, and can hardly ensure convergence to a physically meaningful solution with improper initial values, especially for three-phase unbalanced system. To this end, a general three-phase power flow method for T&D systems is proposed based on the holomorphic embedding method (HEM), and the advantages of the proposed method compared with traditional NRM in solving the power flow problem to a physically meaningful solution are theoretically analyzed. Based on the IEEE 33 system, the modified IEEE 123 system, and a regional power grid in China, it is verified that the proposed method has the advantages of high computational efficiency, reliable converging ability, and independence to the initial value.
Keyword ：
Convergency Convergency Holomorphic embedding method Holomorphic embedding method Three-phase power flow Three-phase power flow Transmission and distribution network Transmission and distribution network
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| GB/T 7714 | Zhang, Yi , Lan, Tian , Li, Chuandong et al. Holomorphic embedding method based Three-Phase power flow algorithm considering the sensitivity of the initial value [J]. | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS , 2024 , 162 . |
| MLA | Zhang, Yi et al. "Holomorphic embedding method based Three-Phase power flow algorithm considering the sensitivity of the initial value" . | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 162 (2024) . |
| APA | Zhang, Yi , Lan, Tian , Li, Chuandong , Cai, Weijie , Lin, Zhiyu , Lin, Jinrong . Holomorphic embedding method based Three-Phase power flow algorithm considering the sensitivity of the initial value . | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS , 2024 , 162 . |
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Abstract ：
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 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 networks. Firstly, considering 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 the 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 the on-site investigation, narrow the investigation scope, and improve the verification rate. © 2024 Power System Technology Press. All rights reserved.
Keyword ：
Convolution Convolution Convolutional neural networks Convolutional neural networks Power distribution lines Power distribution lines Regression analysis Regression analysis
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| GB/T 7714 | Chen, Min , Zhang, Yi , Zou, Yang et al. A Medium-voltage Stealing Type Detection Method Based on Robust Regression and Convolutional Neural Network [J]. | Power System Technology , 2024 , 48 (11) : 4729-4738 . |
| MLA | Chen, Min et al. "A Medium-voltage Stealing Type Detection Method Based on Robust Regression and Convolutional Neural Network" . | Power System Technology 48 . 11 (2024) : 4729-4738 . |
| APA | Chen, Min , Zhang, Yi , Zou, Yang , Xin, Rong , Zhang, Liangyu , Gao, Chen et al. A Medium-voltage Stealing Type Detection Method Based on Robust Regression and Convolutional Neural Network . | Power System Technology , 2024 , 48 (11) , 4729-4738 . |
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