Semantic knowledge-based remote fee control decision framework and method for intelligent power network

Abstract

The invention relates to a semantic knowledge-based remote fee control decision framework and method for an intelligent power network, and belongs to the field of combination of semantic network and intelligent power network technologies. The framework comprises an original information layer, a semantic layer and an application layer. The original information layer comprises intelligent electric meter collected information, electricity customer archive information, electricity customer electricity consumption property information, electricity customer electricity consumption behavior information, electricity customer electricity consumption state information, electricity customer personalized customization information and electricity price information. The semantic layer comprises an intelligent power network remote fee control field knowledge ontology model, a semantic tagging module, a semantic query and reasoning engine, an ontology database and a semantic rule library. The application layer comprises a fee control policy application module, a fee control policy rule management module, a work order management module and a feedback processing module. The method has the advantages that the application of a fee control policy is converted to be in a semantic rule-based form, so that the maintenance difficulty of the fee control policy is lowered, the artificial participation degree is reduced, and the decision intelligence is improved.

Description

technical field [0001] The invention belongs to the field of combining semantic web and smart grid technologies, and relates to a semantic knowledge-based smart grid remote fee control decision-making framework and method. Background technique [0002] Remote fee control is a new type of "pay first, then use electricity" that has emerged with the development of smart grid technology. The difference from local fee control is that it adopts a centralized method for electricity consumption information. Application and implementation of collection and fee control strategies. This process involves multiple parties such as smart meter collection information, electricity customer file information, electricity customer behavior information, electricity customer nature information, electricity customer status information, electricity customer personalized customization information, and electricity price information. However, these data exist in heterogeneous forms in the electricity...

AI Technical Summary

Problems solved by technology

[0003] In view of this, the purpose of the present invention is to provide a smart grid remote fee control decision-making framework and method based on semantic knowledge to solve the inconvenience of management and implementation caused by the heterogeneity of information and the cost control under subdivided management of electricity customers Policy management complexity and application intelligence issues

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