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中文摘要：
电力市场中的电价序列存在很大的随机波动和价格尖峰。文章提出根据电价序列的变化特点，通过小波变换将其分解为概貌序列和细节序列，从而在不同尺度上反映电价的变化规律。通过概貌分量找出电价的主要波动规律，并由此对电价进行预测，剔除细节分量所反映的电价的随机波动影响。建立考虑异方差的广义自回归条件异方差模型fgeneralizedautoregressiveconditionalheteroscedasticity，GARCH）对概貌序列建模，并在GARCH模型中加入外生变量形成GARCHX模型，以弥补传统时间序列模型忽略外界影响的缺陷。对美国PJM电力市场的实例研究表明，所建立的W-GARCHX模型比传统时问序列模型的预测精度有明显提高。
英文摘要：
There are evident random fluctuations and peak price in the electricity price sequence of electricity market. According to its variation features, the price sequence is decomposed into approximate sequence and detailed sequence by wavelet transform to reflect the variation law of electricity price in different scales. By use of approximate components the principal fluctuation law of electricity price can be found and from this the electricity price is forecasted while the influence of random fluctuation due to detailed components is rejected. During the modeling of approximate sequence, a generalized autoregressive conditional heteroscedasticity （GARCH） model, to which the exogenous variables are added, is built to form GARCHX model to avoid the defect of traditional time sequence model that the external impacting factors are neglected. Case study results of PJM electricity market show that forecasted electricity prices by the built W-GARCHX model are much more accurate than those by traditional time sequence model.
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