Electricity consumption data feature extraction method and system based on user behaviors

A technology of electricity consumption data and feature extraction, applied in market data collection, data processing applications, marketing, etc., can solve the problems of small data volume data indicators, difficulty in data acquisition, and inability to classify and analyze users, so as to achieve effective extraction and improve Effects of Reliability and Accuracy

Pending Publication Date: 2021-12-03
SHANGHAI MUNICIPAL ELECTRIC POWER CO +1
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Problems solved by technology

The amount of data used in this kind of analysis is relatively small, the data indicators are macroscopic and one-sided, and the data acquisition is very difficult. This makes the analysis results often only give regional and long-term user behavior preferences, and cannot provide specific information for each user. Carry out classification analysis, give micro-scale high-frequency results, and cannot give short-term or even real-time user feedback

Method used

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  • Electricity consumption data feature extraction method and system based on user behaviors
  • Electricity consumption data feature extraction method and system based on user behaviors

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Embodiment

[0032] A method for feature extraction of electricity consumption data based on user behavior, comprising the following steps:

[0033] S1: Obtain user electricity consumption data.

[0034] In this embodiment, the electricity consumption data of the user within one year is obtained, and the parameter types of the electricity consumption data include the highest temperature, the daily minimum load, the daily maximum load, the daily average load, the minimum temperature, weather, day type, and wind force.

[0035] S2: Perform BIC-based feature selection on the user's electricity consumption data, obtain the parameter importance ranking of the user's electricity consumption data, and confirm the feature selection result.

[0036] The expression of the BIC model in BIC-based feature selection is:

[0037] BIC=2*lnN*p-2*lnφ

[0038] Among them, BIC is the BIC value of the parameter, p is the number of model parameters, N is the number of samples of user electricity consumption d...

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Abstract

The invention relates to an electricity consumption data feature extraction method and system based on user behaviors. The method comprises the following steps: S1, acquiring user power consumption data; S2, performing BIC-based feature selection on the user power consumption data, obtaining a parameter importance sequence of the user power consumption data, and confirming a feature selection result; S3, performing primary clustering according to the selected features to obtain a primary clustering result; and S4, performing secondary clustering on different types of primary clustering results to obtain power utilization data features. Compared with the prior art, the reliability and accuracy of the clustering result are improved, the effective extraction of the user power consumption data characteristics is realized, and the power consumption peak can be accurately found.

Description

technical field [0001] The invention relates to the field of electric power big data, in particular to a method and system for extracting features of electricity consumption data based on user behavior. Background technique [0002] With the rapid development of technologies such as smart grid, Internet of Things, and cloud computing, the power sector has become an important production sector of big data. A large amount of high-frequency data is generated in all links of transmission, transmission, distribution, and sales, in order to improve the security and stability of power supply. It provides new technical means for the needs of increasing the proportion of access to renewable energy, strengthening demand-side management, etc. [0003] Understand the electricity consumption behavior of different users, discover user groups with special value in different application scenarios, and provide a basis for management and decision-making in power distribution and consumption. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02G06Q50/06G06K9/62
CPCG06Q30/0201G06Q30/0202G06Q50/06G06F18/23213
Inventor 朱征田英杰苏运郭乃网吴裔李凡赵莹莹阮静娴金妍斐沈泉江冯楠杨洪山吴元庆
Owner SHANGHAI MUNICIPAL ELECTRIC POWER CO
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