Short-term Electrical Load Forecasting Based on Modified Genetic Algorithm and SVR

doi:10.3969/j.issn.1006-2475.2016.06.013

Abstract

Abstract: In order to effectively and accurately predict the power load, we proposed a Support Vector Regression (SVR) based forecast method to modeling the load consumption, at the same time proposed a two stage modified Genetic Algorithm(MGA) based on Genetic Algorithm to adjust the parameters of SVR. Under the SVR constraint conditions, we chose the Mean Absolute Percentage Error (MAPE) as fitness function of MGA.Finally using a set of practical data, we verified the feasibility and effectiveness of MGA based SVR forecasting method.
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Key words: SVR, load forecasting, GA

CLC Number:

TP311.5

YANG Dan, ZANG Lie, GAN Lu. Short-term Electrical Load Forecasting Based on Modified Genetic Algorithm and SVR[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2016.06.013.

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