A Power Grid Power Forecasting Method Based on Industry Classification and Dominant Industry Data

Abstract

The invention discloses a power grid electric quantity prediction method based on industry classifications and leading industry data. The method includes the steps that firstly, user types are divided; secondly, the user types are selected; thirdly, industries are divided; fourthly, the total electric quantity and power-grid total electric quantity of each industry after division are collected; fifthly, a total electric quantity multiple linear regression prediction model is built, and a total electric quantity prediction value P1 is acquired through the model; sixthly, a total electric quantity gray GM(1,N) model is built, and a total electric quantity prediction value P2 is acquired through the model; seventhly, the average value of P1 and P2 serves as the final prediction result, and a total electric quantity prediction value P is acquired. Principles adopted in the method are simple, prediction results are high in precision, the purpose of predicting total electric quantity through small-sample data is achieved, data collection work is substantially reduced in the electric quantity prediction process, and very strong operability is achieved.

Description

technical field [0001] The invention relates to the field of power grid data processing, in particular to a power grid power prediction method based on industry classification and leading industry data. Background technique [0002] Affected by factors such as economic transformation and industrial structure adjustment, the total power consumption of the grid has also changed accordingly. Power forecasting is a basic task in the electricity market. Combining the characteristics of electricity consumption in the industry to correctly predict power consumption and provide marketing decision support for power supply companies is very important for the safe and economic operation of the power grid and the construction and development of the power market. significance. [0003] Industrial electricity consumption is the basis of grid electricity consumption. The changing trend of electricity consumption in different industries has different impacts on the electricity consumption...

AI Technical Summary

Problems solved by technology

At present, the power and load forecasting methods mainly present the following two problems. One is to pursue the fitting accuracy of the original data of the total power of the power grid, and the other is to pursue complex algorithms based on the premise of large-capacity samples, while ignoring the characteristics of power grid users and industries

In electricity forecasting work, due to many influencing factors and different influencing factors in different industries, there are also large differences in electricity consumption trends in different industries. If the data fitting accuracy is blindly pursued, the generalization of the forecasting method will be reduced; if Too much pursuit of complex algorithms will reduce operability due to large data requirements

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