Community population feature analysis and power supply classification service system based on big data

Abstract

The invention discloses a community population feature analysis and power supply classification service system based on big data, and belongs to the field of power supply management. Power consumption mode analysis is carried out based on daily power consumption of the residential users according to flat valley period data, and analysis and recognition are carried out for various key user types; analyzing by adopting a support vector machine method with supervised learning and a k-means clustering method without supervised learning to obtain user characteristics and power utilization modes of various key user types; completing specific evaluation on various key user types; the electricity consumption data is applied to mining analysis of population characteristics, and the community population characteristic evaluation method is provided, so that the electricity industry can better serve communities. The power utilization data is applied to mining and analysis of the population characteristics, and a diversified power supply service system for the population characteristics is constructed, so that a power supply company can expand the terminal energy utilization market; the application value of the power utilization information acquisition system is exerted, and power utilization data value increment is realized. The method can be widely used in power supply management field.

Description

Technical field [0001] The present invention relates to the field of power management, in particular to a power supply classification management system for different nature community populations. Background technique [0002] In recent years, with the development of internationalization and the economic structure, the changes in population structure, the family in the majority of Shanghai (referring to the resident user of the corresponding electricity address), has a diversified trend, and there have been many new types. . [0003] For example, with the development of the real estate industry and the improvement of the people's living standards, there are more and more families in the above housing, while the external migrant workers have increased, there have been many tenant families; another seven eighties The first generation of the earliest children's policy has entered the age, and the empty nest issues have become a group of groups that are not unpredictable; in addition,...

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Problems solved by technology

[0005] However, the data analysis in the above studies is limited to the analysis of the characteristics of the user's electricity consumption behavior itself, and has not yet involved the mining analysis of population characteristics.

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