Power distribution network space load prediction method taking region and load property dual differences into consideration

Abstract

The invention relates to a power distribution network space load prediction method taking region and load property dual differences into consideration. A conventional space load prediction method does not take influences exerted by regional differences, sample types and quality on load density into consideration, and the applicability is not sufficient. First of all, a full-sample space taking the regional differences into consideration is established, and then, a typical sample is screened by verifying and carefully choosing a load through a typical daily load curve. A region where the load is disposed is clustered through weighted Euclidean distance tolerance, afterwards, a subsample space matching is carried out, a type which the sample belongs to is determined, load density of a plot to be measured is predicted by use of an SVM algorithm, and a total future load amount of the plot is calculated through the load density. The load prediction precision is quite high, and the application is facilitated.

Description

technical field [0001] The invention belongs to the field of power systems, in particular to a space load clustering and forecasting method suitable for distribution networks. Background technique [0002] With the development of the urbanization process and the adjustment of the economic structure, the urban grid load has shown a significant increase, which puts forward higher requirements for the planning and design of the urban grid. [0003] Spatial load forecasting is the basis of urban distribution network planning. Among the various methods of spatial load forecasting, the load density index method is suitable for areas with relatively clear land planning, and is widely used in our country. The key to the application of the method is to determine the load density of each plot in the planning area. [0004] The electricity load is obviously affected by the local economy and industrial development, and the load density reflects large regional differences. All regions ...

AI Technical Summary

Problems solved by technology

[0004] The electricity load is obviously affected by the local economy and industrial development, and the load density reflects large regional differences. All regions cannot follow or learn from the same set of standards. It is extremely time-consuming and laborious to study the local load indicators separately.

Existing load forecasting methods do not take into account the influence of regional differences on load density, and their applicability in various regions is weak, and there are obvious deficiencies

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