Ms. Yang Gao Profile

Yang Gao

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Proceedings Article | 6 February 2024 Paper

Data repair and anomaly detection of power meter based on deep reinforcement learning

Jieqiong Han, Wenjing Fan, Chengxin Huo, Zixiang Zhou, Yang Gao

Proceedings Volume 12979, 129795E (2024) https://doi.org/10.1117/12.3015736

KEYWORDS: Education and training, Matrices, Data modeling, Interpolation, Error analysis, Singular value decomposition, Power meters, Mathematical optimization, Covariance matrices, Reliability

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The data quality of power metering device is very important for the operation and management of power system. However, these data are often faced with missing, abnormal and noise problems, which may lead to the difficulty of accurate evaluation of power system state and performance. Therefore, the purpose of this study is to propose a method based on deep reinforcement learning to restore missing values in power metering device data, and to detect anomalies. Firstly, the missing data are interpolated by the antagonistic network reconstruction, and the complete data of the power metering device is obtained to repair the power metering data. By constructing a model of abnormity detection based on deep reinforcement learning, a random matrix is established, and a feature index matrix is constructed to decompose the singular value of feature vector. Experimental results show that the proposed method has advantages in accuracy and time efficiency. This method can achieve more than 97% accuracy of anomaly detection and has shorter error detection time. These results verify the feasibility of the proposed method in data processing of power metering devices.

Proceedings Article | 10 August 2023 Paper

Parameter monitoring of electric energy metering system based on Internet of Things technology

Wenjing Fan, Yang Gao, Bin Ma, Chengxin Huo

Proceedings Volume 12748, 1274830 (2023) https://doi.org/10.1117/12.2690049

KEYWORDS: Internet technology, Internet of things, Data transmission, Power grids, Data processing, Transformers, Telecommunications, Data communications, Sensors, Intelligent sensors

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In order to further improve the Internet of Things technology and ensure the ability and effect of the on-line monitoring system for electric energy metering. A parameter monitoring method of electric energy metering system based on Internet of Things technology is proposed. In this paper, the necessity and composition of the transmission line online monitoring system based on the Internet of Things technology are summarized. The sensing layer carries out real-time data exchange by using wireless communication interfaces and controlled devices, or supervises the components of intelligent sensors in a consistent way, and collects the information effectively, and classifies the real-time data into the controller. The network layer communication equipment is used to accurately transmit the collected information to the electric power network system, and it provides further reference for the management of various equipment scheduling. By using different information transmission methods, the unified information can transmit the perceived data to the circuit system, and the data can be classified and processed in a unified way. And all the effective information is collected in the controller for real-time data forwarding; The most important function of the application layer is to further process the information from the network layer, and at the same time, store it in a unified code, and then judge whether there are some faults in the line according to the information. At the same time, the problems existing in the running circuit are concretely speculated by comparing the values of normal operation and variables. With the intelligent development of on-line monitoring system for transmission lines, we need to further expand various technologies such as state sensors, and further establish and improve the intelligent monitoring model for transmission and transformation equipment.

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