Method and device used for power load aggregation

Abstract

The invention discloses a method and device used for power load aggregation. The method and device used for power load aggregation comprise S1, acquiring sample data of n transformer substation comprehensive load static characteristics; S2, mapping the sample data to a Hilbert space through a gaussian kernel function and acquiring samples; S3, confirming an initial aggregation center by selecting K samples in the samples; S4, performing aggregation calculation on mapped samples in a core space by adopting a k-means algorithm, and assigning each sample to closest-type upper and lower approximations according to an upper and lower approximation method; S5, dynamically adjusting weights omega1, omegabnr according to a current iteration; S6, calculating a Jomega value according to an arithmetic convergence criteria, and judging whether |Jomega(t)- Jomega(t-1)|<= epsilon or t>=tmax, if yes, then generating a final collection and finishing, if not, then entering into S7; and S7, enabling t=t+1, reconfirming an aggregation center and transferring to S4. The method and device used for power load aggregation is simple, easy, fast and effective, aggregation results are reasonable, and has important significance on practicability of load modeling research.

Description

technical field [0001] The invention belongs to the technical field of electric load clustering, and more specifically relates to a method and device for electric load clustering. Background technique [0002] In power system analysis, the clustering of substation load characteristics is to group different substations of the same power grid and substations with similar or similar characteristics in different periods, such as substations dominated by heavy industrial loads, substations dominated by municipal life, Substation mid-month and quarterly load curves, daily and quarterly load curves, etc. The same model is used to describe the characteristics of each category, and a comprehensive load model that can effectively describe the characteristics of substations can be established through clustering. As far as the practicality of load modeling is concerned, the classification and synthesis of load characteristics are of great significance, which can reduce the work and lab...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the defects of the prior art, the purpose of the present invention is to provide a method for electric load clustering, which aims to solve the problem that the clustering method in the prior art cannot handle nonlinear data, cannot handle boundary objects, and cannot handle high-dimensional Mixed data leads to poor usability of clustering results, which cannot be accurately and efficiently used by managers to make business decisions

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