An Application of Auxiliary Operation of Power Dispatching based on Semantic Analysis
Autor: | Jixiang Lu, Feng Xie, Hong Li, Hao Li, Tao Zhang, Lu Jin Jun |
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Rok vydání: | 2020 |
Předmět: |
Multi-label classification
Computer science Semantic analysis (machine learning) Stability (learning theory) Unstructured data 02 engineering and technology 010501 environmental sciences computer.software_genre Fault (power engineering) 01 natural sciences Power (physics) Reliability engineering Information extraction 0202 electrical engineering electronic engineering information engineering Key (cryptography) 020201 artificial intelligence & image processing computer 0105 earth and related environmental sciences |
Zdroj: | 2020 12th IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC). |
Popis: | Power dispatching plays quite an important role in power grid operation in terms of safety and stability. Structured data has been well managed in the real-time power dispatching and controlling system. However, the management of unstructured data such as text data has not received enough attention. In this paper, we accomplish an application of auxiliary operation of power dispatching by doing semantic analysis on operation procedures, which belong to an important category of power dispatching text data for fault disposal. The method that we proposed in our application is achieved based on Natural Language Processing (NLP) technologies. Our contributions are mainly two-fold: 1) we accurately extract key information from text data through our proposed method, and 2) we help power dispatching operators reduce their work and improve efficiency by providing auxiliary operation advice. |
Databáze: | OpenAIRE |
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