Load forecasting algorithm of smart grid considering temperature cumulative effect
YANG Xiaolei
GUO Xiaming
LU Yi
ZHANG Dawei
LIAO Ye
Abstract：Aiming at the influence of temperature cumulative effect on load change,a load forecasting algorithm for smart grid considering temperature cumulative effect was studied.The effect of continuous high temperature on grid load was included in the forecasting model.A modular neural network was used to ensure the independence of temperature cumulative effect learning and the improvement of accuracy.Three sub-networks formed the first layer of the multi-module neural network,with temperature,time and load characteristics as input parameters.The accuracy of load forecasting is 98.13%,and the error is 28.63%lower than that before correction.The results show that the as-proposed algorithm has higher forecasting accuracy and operation efficiency.
Keywords：load forecastingsmart gridtemperature cumulative effecttemperature correctionneural networkmulti-moduletemperature characteristictime characteristicload characteristic
Publication Date：2024-03-25
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 121-126 )