Electricity consumption prediction method and device

Abstract

The invention provides an electricity consumption prediction method and device, actual electricity consumption information is introduced on the basis of BP neural network rolling prediction, the actual electricity consumption information is not directly introduced, but is introduced in a prediction error mode, a BP neural network rolling prediction result is finely adjusted and corrected through a third error of rolling prediction, and the accuracy of power consumption prediction is improved.

Description

technical field [0001] The present invention relates to the field of electric power technology, and more specifically, to a power consumption prediction method and a device thereof. Background technique [0002] In production and life, electricity is an indispensable part of people, and it plays an irreplaceable role in economy and society. Power consumption forecasting refers to the forecast of the total amount of electric energy consumed by the load of the power system within a certain period of time. Improving the technical level of power consumption forecasting is conducive to planning power consumption management, rationally arranging power grid operation mode and unit maintenance plan, helping to save coal, oil and power generation costs, and to formulate reasonable power supply construction plans. Improve the economic and social benefits of the power system. In recent years, electricity consumption forecasting has become one of the important contents in realizing th...

AI Technical Summary

Problems solved by technology

Since there are many factors affecting electricity consumption, such as regional economy, policy, climate, etc., some of these factors are deterministic and random, which increases the difficulty of electricity forecasting. Although many current methods for electricity consumption forecasting can To a certain extent, the prediction needs are met, but there is still room for improvement

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