基于優(yōu)化隨機(jī)森林算法的電動(dòng)汽車充電負(fù)荷預(yù)測(cè)

打開文本圖片集

doi：10.3969/J.ISSN.1672-7274.2025.06.009

中圖分類號(hào)：TM910.6;TP31;U469.72 文獻(xiàn)標(biāo)志碼：B 文章編碼：1672-7274（2025）06-0026-03

Electric Vehicle ChargingLoad Forecasting Based on Optimized Random Forest Algorithm

ZHANG Meng

（Shanxi Vocational College of Finance and Trade， Taiyuan O3oo31， China）

Abstract： With the rapid development ofthe electric vehicle （EV） market，the demand forcharging is increasing， posing unprecedented challnges to the existing power system. Accurately predicting the charging load of electric vehiclescan guidethe management and scheduling of the power system，improve the eficiencyofenergyutilization， and help alleviate charging pressure.This article proposes an electric vehicle charging load prediction method based on optimized random forest algorithm.The experimentalresults show that compared with the SVM method，this model has significantly improved accuracyand stability，and can provide more reliable basis for power system management and scheduling， effectively coping with the pressure of charging peak.

Keywords： charging load forecasting; random forest; grid search

0 引言

隨著全球?qū)沙掷m(xù)發(fā)展和環(huán)保的重視，電動(dòng)汽車（EV）作為一種低碳出行方式，近年來得到了快速發(fā)展。（剩余3522字）