Power grid multidimensional sensing and safety assessment system and method on the basis of big data

Abstract

The invention discloses power grid multidimensional sensing and a safety assessment system and method on the basis of big data. The system comprises: a power grid big data storage platform, a power grid big data security feature extraction platform, a power grid safe operation knowledge base analysis platform and a result display platform. The system adopts Hadoop file distributed management system and performs quick storage and query to big data collected by EMS; and then, power grid main security features, ancillary features and data features are extracted by the feature extraction platform and dimensionality reduction is performed to the power grid big data; the extracted security features enter the power grid safe operation knowledge base and are compared with relative safe rules in the base to obtain a safety status assessment of the current power grid. Compared with common methods, the provided system and method has following beneficial effects: an assessment system suitable for big data is designed, reasonable dimensionality reduction of power grid big data is realized, and a comprehensive and reasonable assessment for the power grid safety status is realized.

Description

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AI Technical Summary

Benefits of technology

This patented technology uses Apache's Distributed File Management System (DFM) to efficiently manage large amounts of data from different sources such as electricity grids or other systems like communication networks. It also includes tools that help identify potential hazards related to these areas. These technical results include efficient storage and retrieval of important insights about how well they were operating under various conditions, reduced dimensions of their data, and overall understanding of its healthy state during use.

Problems solved by technology

This patents discusses how modern electric grids have become smarter due in part to their ability to detect changes quickly over multiple levels of networked infrastructure. However, current methods for analyzing power grid operations lack flexibility or cannot effectively handle these challengings.

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