The Study of Knowledge-Based Active Learning Grid Operation Experience

Qiang Qing Zhou; Jing Liu; Qing Nian Zou; Guo Lin Huang; Ping Han; Yan Xu

doi:10.4028/www.scientific.net/AMR.860-863.2456

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The Empirical Study of Demand-Side Response Model Based on the Maximize Benefits under the Background of Smart Power Grid
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The Effect Research of Smart Grid to Residential Users Intelligent Response Behavior
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The Study of Knowledge-Based Active Learning Grid Operation Experience
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Improved GSA-GA Algorithm Based Bad Data Detection, Identification and Correction for Power Grid
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Research of DC Micro-Grid Photovoltaic Energy Storage System Control Strategy
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 860-863The Study of Knowledge-Based Active Learning Grid...

The Study of Knowledge-Based Active Learning Grid Operation Experience

Abstract:

By using of the object-oriented technology and the knowledge representation of the production rule, this paper classifies the operation experience of grid according to the nature and builds a power grid operation experience knowledge base with active learning capability. Through application of Bayesian classifier model based on weight, it classifies the statistical data and identifies the semantic, to realize the exchange between the knowledge base and the users feedback. Using the powerful learning ability of knowledge base, it can make the operation experience knowledge base optimize its knowledge system structure while exchanging with users feedback, so that it can go on refining the operation experience base of the grid. This method can provide technical support and improve the quality of the stuff, as well as strengthen the security and stability of the grid.

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Periodical:

Advanced Materials Research (Volumes 860-863)

Pages:

2456-2462

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.860-863.2456

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Online since:

December 2013

Authors:

Qiang Qing Zhou, Jing Liu, Qing Nian Zou, Guo Lin Huang*, Ping Han, Yan Xu

Keywords:

Active Learning, Knowledge Base, Operation Experience of Grid

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* - Corresponding Author

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