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Short-term Electricity Price Forecasting Based on Grey System Theory and Time Series Analysis

机译:基于灰色系统理论和时间序列分析的短期电价预测

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Under deregulated environment, accurate price forecasting provides crucial information for electricity market participants to make reasonable competing strategies. With comprehensive consideration of the influencing factors and the varying rules of the day-ahead electricity price of the PJM electricity market, a short-term electricity price forecasting method based on GM(1,2) and ARMA is proposed, in which the equal-dimension and new-information GM(1,2) model is firstly used to the raw data of electricity price series, and then the ARMA model is used to the gray residuals. The numerical example based on the historical data of the PJM market shows that the method can reflect the characteristics of electricity price better and the forecasting accuracy can be improved virtually compared with the conventional GM(1,2) model.
机译:在放松管制的环境下,准确的价格预测可为电力市场参与者制定合理的竞争策略提供关键信息。综合考虑PJM电力市场日均电价的影响因素和变化规律,提出了一种基于GM(1,2)和ARMA的短期电价预测方法,其中,维和新信息GM(1,2)模型首先用于电价序列的原始数据,然后将ARMA模型用于灰色残差。基于PJM市场历史数据的数值算例表明,与传统的GM(1,2)模型相比,该方法可以更好地反映电价的特征,并且可以虚拟地提高预测精度。

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