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电力市场中的电价受众多因素影响,单变量时间序列法已很难提高短期电价的预测精度。针对该问题,文中运用时间序列模型的动态计量方法来预测短期电价。首先建立电价和电量的一般自回归分布滞后模型;然后对电价和电量的时间序列数据进行预处理;在通过平稳性和协整性检验后,建立误差修正模型,最终由Eviews5.0估计出模型的参数。利用此模型对澳大利亚新南威尔士州电力市场的短期电价进行预测,结果表明此模型具有较高的预测精度。
Electricity prices in the electricity market are affected by many factors. It is hard to improve the forecast accuracy of short-term electricity prices by the single-variable time series method. In order to solve this problem, we use the dynamic measurement of time series model to forecast the short-term electricity price. Firstly, the general autoregressive distribution lag model of electricity price and electricity quantity is established. Then the time series data of electricity price and electricity quantity are preprocessed. After the test of stability and cointegration, the error correction model is established, and finally the model is estimated by Eviews5.0 The parameters. This model is used to forecast the short-term electricity price in New South Wales electricity market in Australia. The results show that this model has high prediction accuracy.