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A power consumer classification method based on adaptive particle swarm clustering

A classification method and technology for power users, applied in data processing applications, instruments, character and pattern recognition, etc., can solve the problems of difficult to determine the number of clusters, large noise interference of clustering algorithms, etc., to improve search efficiency and convergence speed, The effect of small initial value impact and fast convergence

Active Publication Date: 2019-06-18
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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Problems solved by technology

[0005] The purpose of the present invention is to provide a power user classification method based on adaptive particle swarm clustering, realize the classification of power users according to the load curve shape, and solve the problems of large noise interference and difficult determination of the number of clusters in the clustering algorithm.

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  • A power consumer classification method based on adaptive particle swarm clustering
  • A power consumer classification method based on adaptive particle swarm clustering
  • A power consumer classification method based on adaptive particle swarm clustering

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Embodiment Construction

[0033] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0034] The present invention provides a technical solution: a power user classification method based on adaptive particle swarm clustering, the method includes the steps of:

[0035] A. Standardize the original load curve data;

[0036] B. Removal of data noise, i.e., interference load curves, by density-based data screening methods;

[0037] C. Use the adaptive particle swarm optimization algorithm to cluster the residual load curve data;

[0038] D. Coagulate the clusters of the clusters through the fuzzy clustering algorithm;

[0039] E. Reclassify the disturbance load curves based on the principle of pattern recognition to obtain clustering results.

[0040] The overall operation process of the proposed method of the present invention is as follows: figure 1 shown.

[0041] For step A, the raw load data to be processed should be selected first. Gene...

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Abstract

The invention discloses a power consumer classification method based on self-adaptive particle swarm clustering. The method comprises the following steps: A, carrying out standardization processing onoriginal load curve data; B, removing data noise, namely an interference load curve, through a density-based data screening method; C, clustering the residual load curve data by using an adaptive particle swarm algorithm; D, clustering the clusters through a fuzzy clustering algorithm; And E, re-classifying the interference load curve based on a pattern recognition principle to obtain a clustering result. According to the invention, classification of power consumers based on the load curve can be realized; The method is suitable for user power utilization behavior analysis in the field of demand response, can effectively remove data noise and reduce the sensitivity to the clustering number by fusing the DBSCAN algorithm and the fuzzy mathematics theory, and meanwhile, the self-adaptive particle swarm algorithm is less affected by an initial value, fast in convergence and not easy to fall into local optimum, so that the clustering precision is improved.

Description

technical field [0001] The invention relates to a method for power system load analysis, in particular to the classification of power users in demand response and the method for analyzing power consumption behavior of users, and belongs to the field of power demand response analysis. Background technique [0002] Electric load is an important object in power system research. Load classification is the basic work of load forecasting and power grid planning. important step. Therefore, it is of great significance to study the classification of user load and further analyze the user's electricity consumption behavior and law to improve the service level of power companies, improve the economic benefits of enterprises, and promote the development of power demand response. [0003] The traditional load classification is based on the industry the user belongs to. Users can be roughly divided into industrial users, commercial users and residential users, and can be further subdivid...

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/06G06K9/62G06N3/00
Inventor 曹昉李赛张姚
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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