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User behavior analysis method for large-scale buildings based on improved clustering fusion

A technology of behavior analysis and clustering method, which is applied in data processing applications, instruments, character and pattern recognition, etc., can solve the problems of result differences and achieve accurate clustering results

Active Publication Date: 2018-12-21
SHANGHAI MUNICIPAL ELECTRIC POWER CO +1
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  • Description
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  • User behavior analysis method for large-scale buildings based on improved clustering fusion
  • User behavior analysis method for large-scale buildings based on improved clustering fusion
  • User behavior analysis method for large-scale buildings based on improved clustering fusion

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Embodiment

[0039] like figure 1 , figure 2 As shown, a large-scale building user behavior analysis method based on improved cluster fusion is used to determine the electricity consumption pattern of large-scale building users. The electricity consumption pattern here refers to: for different users, the behavior of electricity consumption and Habits are bound to be different. For example, some users start using electricity in the morning until evening, and some users use less electricity during the day and more electricity at night; for the same user, there are also differences in the time scale. According to the law, the electricity consumption in spring and summer must be different. The final performance of this different electricity consumption habits on the load is called the electricity consumption pattern.

[0040] The present invention is based on the large-scale building user behavior analysis method of improved cluster fusion and comprises the following steps:

[0041] (1) Ob...

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Abstract

The invention relates to a large-scale building user behavior analysis method based on improved clustering fusion. The method is used for determining the power consumption mode of the large-scale building user. The method comprises the following steps: (1) obtaining the total load data of the large-scale building user to be analyzed and the sub-item measurement data; (2) constructing the comprehensive evaluation index of clustering effect, and selecting various high-quality clustering methods; (3) Clustering the total load data of large-scale building users to obtain different clustering results by using the selected high-quality clustering method; (4) fusing the clustering results obtained by the high-quality clustering method to obtain the final power consumption mode. Compared with theprior art, the invention can absorb the advantages of different single clustering algorithms, the effectiveness and the accuracy of the clustering algorithm are higher than those of the single clustering method, and the expansibility is improved.

Description

technical field [0001] The invention relates to a large-scale building user behavior analysis method, in particular to a large-scale building user behavior analysis method based on improved cluster fusion. Background technique [0002] With the continuous advancement of the smart grid process, a large amount of investment in intelligent information collection systems has accumulated a large amount of electricity consumption data while promoting the construction of smart grids. As an important part of the electricity user-side load, large buildings generate massive, scattered, and high-frequency electricity consumption data, and there are similarities and correlations between different data. It is an important content in the research to promote the development of smart grid to mine the content with practical significance by processing these data. Therefore, using data analysis methods to explore users' electricity consumption patterns and accurately analyze the electricity c...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q50/06G06K9/62G06Q10/06
CPCG06Q10/06393G06Q50/06G06F18/23
Inventor 张勇蔡鹏飞凌平杨秀时志雄方陈赵立强田英杰苏运
Owner SHANGHAI MUNICIPAL ELECTRIC POWER CO
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