[其它]Application of GARCH Model in the Forecasting of Day-Ahead Electricity Prices

In the new deregulated electric power industry, |oH,   
price forecasting is becoming increasingly important D.B.7-_8  
for the producers and consumers to estimate and 3oGt3F{gZ  
maximize their profits. A generalized autoregressive dt \TQJc~  
conditional heteroskedastic (GARCH) methodology is 8ndYV>{f
 
presented to predict day-ahead electricity prices. For V)Z}En["1  
the high volatility of the electricity prices, the GARCH AK,J7
 
model is more suitable for illustrating the time series _E&A{HkJ  
data than other forecast model adopted generally. The b
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prediction error is assumed to be serially correlated ]fx"4qKM  
other than independent variable with zero mean and Bn=by{i  
constant variance, which can be modeled by an Auto A
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Regressive process. Based on the initial values of the nt 81Bk=  
parameters of the model gained by Eviews software,  $UMFNjL  
Genetic arithmetic is used to optimize them to improve \\r)Ue]  
its performance. A detailed explanation of GARCH tvkb~  
models is pre .. Y>|B;Kj0(  
XX7{-Yy  

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