Research on Electric Power Demand Prediction Based on Improved Extreme Learning Machine
SUN Wei
BAO Yi
DAI Bo
LU Junbo
WANG Kun
Abstract：In view of the electric power demand forecasting accuracy or not for the healthy development of the electric power enterprise,and has the important influence on national economy,this paper puts forward the electric power demand forecasting mod?el based on improved extreme learning machine. First of all,the electric power demand forecasting is analyzed,according to the characteristics of the demand for electricity power demand can be divided into industry,agriculture,transportation,residents,and power consumption of power,and the principle and process of electric power demand forecasting is analyzed. Secondly,an ELM model based on GA is proposed to improve the fitting capacity of ELM network model through GA optimization. Then,through the actual case simulation,the model prediction research is carried out on the large industry,the non-pup industry,the commercial, the residential electricity and non-living electricity consumption of a region. The simulation error is small,and the validity and ap?plicability of the proposed method are verified.
Keywords：hereditylimit learning machineelectricity demandforecast
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 806-811,819 )