High-applicability and high-precision industrial electricity user classification off-peak electricity utilization method

Abstract

The invention discloses a high-applicability and high-precision industrial electricity user classification off-peak electricity utilization method, which is characterized by being based on a clustering algorithm and Fourier transform, and comprises the following steps: step S10, collecting electricity utilization load data of a target user, and performing data cleaning by using a load transformation ratio rule; step S20, carrying out data smoothing processing on the cleaned load data by using a moving average method; step S30, performing Fourier transform on the smoothed data, and taking the smoothed data as data features; step S40, inputting the data after the feature engineering is completed into a K-means clustering algorithm, and adjusting and optimizing model parameters; step S50, classifying the clustered users according to the load volume to obtain a result; and step S60, performing intra-class grouping on the users of the same class, and arranging off-peak power utilization. The method solves the problem that the power consumption behaviors of the users are complex and difficult to distinguish, extracts the deep power consumption rules of the users for clustering, carries out the off-peak power consumption management of the users, and has the advantages of being clear in thought and suitable for popularization and use.

Description

technical field [0001] The invention belongs to the field of power system analysis and calculation, and in particular relates to the technical field of power consumption behavior classification and shifting of different large industrial users in the power system. Background technique [0002] In response to the country's strategic goal of carbon neutrality, the rational use of electric energy has become the top priority. In order to avoid the waste of electric energy, many provinces and cities have implemented power limit measures for industrial users. However, blind power limit The economy will have a negative impact and will greatly reduce user satisfaction. Therefore, there is currently room for exploration, regulation and optimization of the reasonable distribution of electricity consumption by large users in certain industries. Stable operation also has a huge impact, and reasonable power consumption arrangements will also reduce the peak load of the grid, which is of g...

AI Technical Summary

Problems solved by technology

To classify users according to their electricity consumption behavior, it is necessary to extract the characteristics of electricity consumption behavior and calculate the similarity between each user. Part of the length will lead to information loss and affect the calculation accuracy, and most of the original load data has a small range of volatility, which has little meaning in classification but will greatly affect the calculation value of the similarity, resulting in poor classification results

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