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Qian Tan
Publications - 5
Citations - 32
Qian Tan is an academic researcher. The author has contributed to research in topics: Engineering & Digital protective relay. The author has an hindex of 1, co-authored 1 publications receiving 29 citations.
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Journal ArticleDOI
Self-adaptive transformer differential protection
TL;DR: In this paper, a novel adaptive protection criterion is proposed, which can self-regulate the parameters of percentage differential characteristic (e.g., pickup current, restraint coefficient and restraint current at the knee point of the slope characteristic) on the basis of operating conditions of power transformers.
Proceedings ArticleDOI
Multi-dimensional Visualization Method of SCD File Information of Intelligent Substation Based on Knowledge Graph
TL;DR: In this paper , a multi-dimensional visualization method of SCD file information of smart substation based on knowledge graph is presented, which can provide guidance for operation and maintenance and information retrieval.
Journal ArticleDOI
Operation and Maintenance Technology of Relay Protection Equipment Based on Digital Twin Technology
TL;DR: In this article , the reliability probability density by function is applied to solve the problems of fuzziness, gray, and randomness of the relay protection status index, which can ensure the security and stability of the power system and reduce the reliable power consumption of the majority of power users.
Proceedings ArticleDOI
A Data Storage Method of Intelligent Substation Based on Physical Model
TL;DR: In this article , the authors presented a data storage method of intelligent substation based on physical model, where the authors analyzed the data transmission mode of IEC 61850, introduced the object-oriented modeling technology of IED 618 50, the relationship between various configuration files, and the tree structure of the transmitted data.
Proceedings ArticleDOI
A LSTM-Based Method for Prediction of Network Security Situation in Smart Electric Power Grid
TL;DR: In this paper , the improved Simple Particle Swarm Optimization algorithm (SPSO) was applied to optimize the hyperparameters of LSTM such as the number of neurons, learning rate, and learning rate of the network.