A Space Load Prediction Method Based on Cellular Growth Model

Abstract

Disclosed in the invention is a cell-growth-model-based space load prediction method. The method comprises: establishing a cell growth model; selecting and setting a cell sample zone in a space-time database; defining power load cells; establishing a conversion rule of the power load cells; establishing a power load cell sample sub database; obtaining association attribute data of a center power load cell and neighboring cells; determining an activity value of the center power load cell according to the load attribute data; determining a load value of the center power load cell based on the conversion rule of the power load cell and storing cell data that may be changed within a planning period into an optimized cell data table; and carrying out space load prediction on all power load cells and outputting a space load prediction value. According to the invention, a problem that load prediction is not accurate because phenomena that the plot data are not complete and all plots are influenced mutually are not considered can be solved.

Description

technical field [0001] The invention relates to a power load forecasting method, in particular to a space load forecasting method based on a cell growth model. Background technique [0002] The results of load forecasting have guiding significance for the determination of power network and power supply point, and are an important basis for power grid planning, as well as essential basic data for urban planning and economic development. At present, the methods commonly used in medium and long-term load forecasting mainly include S-curve method, elastic coefficient method, gray system method, fuzzy algorithm, etc., and comprehensive methods based on the above methods. These methods generally can only predict the total load but cannot determine the load. specific distribution. In power distribution system planning, load forecasting not only requires the ability to predict the total amount of load, but also requires location information that can predict future load growth, beca...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the deficiencies in the above-mentioned prior art, the present invention provides a space load prediction method based on the cell growth model, which comprehensively considers the development mode of the load from multiple aspects, multiple angles, and multiple factors, and predicts the future space of the planning area. The load distribution value and its development trend can be predicted to a certain extent, which solves the problem of incomplete plot data and lack of consideration of the mutual influence of each plot, which leads to inaccurate load forecasting.

Images