Short-term load prediction method and device for power utilization region

Abstract

The invention discloses a short-term load prediction method and device for a power utilization region. The method comprises the steps of collecting historical load index data of a to-be-predicted power utilization region; respectively inputting the historical load index data into corresponding classification load prediction models; performing the operation of the classification load prediction model, obtaining unit short-term load prediction results corresponding to different user categories, wherein the classification load prediction model is a neural network model trained by taking a morletmother wavelet function as a transfer function based on load index principal components of the same user category, and the load index principal components are obtained through a principal component analysis mode according to historical load index data of the same user category; and summing the short-term load prediction results of the units to obtain a short-term load prediction result of the to-be-predicted power utilization region. The technical problem of low prediction precision of an existing short-term load prediction mode of the power utilization region is solved.

Description

technical field [0001] The present application relates to the field of electricity load management, in particular to a short-term load forecasting method and device in an electricity-consuming area. Background technique [0002] In the current environment of vigorously promoting smart distribution networks, the access of new loads and distributed power sources can optimize the allocation of resources and the environment on the one hand, and on the other hand, it also puts forward higher requirements for the accuracy of power load forecasting. How to carry out high-precision short-term load forecasting based on the development characteristics of electricity load under the smart grid is an important research direction in the smart grid environment. [0003] At present, electricity user load forecasting is usually carried out through neural network prediction. The specific method is usually to first analyze the various influencing factors that affect the user's electricity load...

AI Technical Summary

Problems solved by technology

[0004] This application provides a method and device for short-term load forecasting in power-consuming areas, which is used to solve the technical problem of low prediction accuracy existing in the existing short-term load forecasting methods in power-consuming areas

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