Historical Similar Ticket Matching and Extraction used for Power Grid Maintenance Work Ticket Decision Making

Liu, Tong; Li, Shaoyan; Gu, Xueping; Wang, Tieqiang; Lü, Peng; Cao, Xin; Xiao-dong, Yang; Wang, Wei; Lv, Hao; Feng, Chunxian

doi:10.1109/icdsba48748.2019.00070

Cited by 4 publications

(2 citation statements)

References 2 publications

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“…Deep learning is widely used in power system because of its excellent ability in data analysis [10,11]; in order to shorten the reasoning process of operation tickets, some scholars use deep learning to guide the generation of operation tickets [12,13]. By learning the relationship between the environment and the operation sequence before and after the substation operation, a model that can match similar historical tickets according to the operation task and the initial state of the substation is obtained, and the generation of operation tickets is guided.…”

Section: Introductionmentioning

confidence: 99%

Substation Operation Sequence Inference Model Based on Deep Reinforcement Learning

Chen

et al. 2023

Applied Sciences

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At present, substation operation ticket system is developed based on an expert system, which has some problems such as knowledge base redundancy, intelligence deficiency and automatic learning ability. To solve this problem, this paper proposes an operation sequence reasoning model based on the knowledge base of the Neo4j knowledge graph and DuelingDQN (Dueling Deep Q Network) algorithm. Firstly, the diagram structure model of substation main wiring was established using the Neo4j knowledge graph. Based on the diagram structure model, the operable equipment set of the operation task was searched to form the task space, action space and action selection model of DuelingDQN. The reward and punishment function was designed based on the “five defense” rules and the state change of equipment. Make DuelingDQN model and Neo4j model interact in real time, and automatically learn the operation sequence. The test results show that the method proposed in this paper can automatically deduce the correct operation steps under different wiring modes and realize the transfer within the station, which is of great significance to the intellectualization of the operation ticket system.

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Section: Introductionmentioning

confidence: 99%

Substation Operation Sequence Inference Model Based on Deep Reinforcement Learning

Chen

et al. 2023

Applied Sciences

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“…This retrieval method has a large workload, poor reliability, and low automation level. Therefore, it is of great significance to study the intelligent filling method of power grid work tickets (Liu et al, 2020;Gui et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Intelligent Filling Method of Power Grid Working Ticket Based on Historical Ticket Knowledge Base

Liu

et al. 2021

Front. Energy Res.

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The traditional power grid ticket filling method has a large workload, low efficiency, and cannot achieve comprehensive and effective reference of historical tickets. This paper proposes a method of intelligent filling in a power grid working ticket based on a historical ticket knowledge base. Firstly, the historical ticket data are preprocessed, then the historical ticket information is mined by the association rule algorithm, and the method of establishing the historical ticket knowledge base is proposed. Based on the improved word bag model, an intelligent grid work ticket filling model is established based on the historical ticket knowledge base, and the correctness of the method is verified by an example. The results show that the accuracy of the proposed method is at least 18% higher than that of the traditional model, and the matching efficiency is 50% higher than the evaluation results of the three models based on semantic expressions. The method enables the identification and extraction of similar and associated work tickets, improves the efficiency of filling work tickets for power grids, and promotes the intelligence of the safety procedures for power grid operations.

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A Table Segmentation and Text Information Extraction Method for Power Work Ticket

Tan

Shen

Qiu³

et al. 2021

2021 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)

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Historical Similar Ticket Matching and Extraction used for Power Grid Maintenance Work Ticket Decision Making

Cited by 4 publications

References 2 publications

Substation Operation Sequence Inference Model Based on Deep Reinforcement Learning

Substation Operation Sequence Inference Model Based on Deep Reinforcement Learning

Intelligent Filling Method of Power Grid Working Ticket Based on Historical Ticket Knowledge Base

A Table Segmentation and Text Information Extraction Method for Power Work Ticket

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