Non-invasive load identification method based on improved particle swarm algorithm

A technology for improving particle swarm and load recognition, applied in character and pattern recognition, calculation, calculation model, etc., can solve problems such as high cost, time-consuming and labor-intensive, to improve accuracy, reduce cost and time consumption, and improve recognition The effect of accuracy

Active Publication Date: 2019-12-10
XIHUA UNIV
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Problems solved by technology

[0003] Aiming at the above-mentioned deficiencies in the prior art, the non-intrusive load identification method based on the improved particle sw

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  • Non-invasive load identification method based on improved particle swarm algorithm
  • Non-invasive load identification method based on improved particle swarm algorithm
  • Non-invasive load identification method based on improved particle swarm algorithm

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Embodiment Construction

[0052] The specific embodiments of the present invention are described below so that those skilled in the art can understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes Within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are included in the protection list.

[0053] Such as figure 1 and figure 2 As shown, a non-invasive load identification method based on improved particle swarm optimization algorithm, including the following steps:

[0054] S1. Collect the electrical data of the independent operation of the electrical equipment, and obtain the active power P of the electrical equipment in steady state operation i , reactive power Q i and distortion power D i , to establish...

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Abstract

The invention discloses a non-invasive load identification method based on an improved particle swarm algorithm, and the method comprises the following steps: collecting electrical data of independentoperation of electric equipment, obtaining active power Pi, reactive power Qi and distortion power Di of the electric equipment during steady-state operation, and building a load feature library; acquiring data of electric equipment, performing missing value processing on the data, and calculating average active power Pj, average reactive power Qj and average distortion power Dj by adopting fastFourier transform; acquiring a state change condition of the electric equipment by setting a threshold value of the processed electric equipment data. According to the state change condition of the electric equipment, feature extraction of the electric equipment is carried out and load is identified through an improved particle swarm algorithm according to the extracted features of the electric equipment and the load feature library. According to the invention, the improved particle swarm algorithm and the fitness function are used to improve the accuracy of load identification and reduce thetime consumption of the algorithm.

Description

technical field [0001] The invention belongs to the field of smart grids, and in particular relates to a non-invasive load identification method based on an improved particle swarm algorithm. Background technique [0002] Smart grid is an important direction of future energy management, which is conducive to safer and cleaner power consumption. The deployment of advanced metering infrastructure is regarded as the cornerstone of the smart grid. The advanced metering infrastructure collects, stores, and analyzes users' electricity consumption through smart meters, and provides detailed energy consumption information to users and power companies to realize the relationship between the grid and users. bidirectional information flow between them. Studying the details of consumers' electricity consumption helps power companies optimize power supply services. At the same time, the detailed electricity consumption of each device in the home can also help users adjust their electri...

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Application Information

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IPC IPC(8): G06Q50/06G06N3/00G06K9/62
CPCG06Q50/06G06N3/006G06F18/21
Inventor 郭奕伏淇黄永茂卿朝进张岷涛江婉周婷肖舒予
Owner XIHUA UNIV
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