In the present paper we study the statistical properties of the Italian daily electricity load market, by mean of different statistical methods, such, e.g., the exponential smoothing model, the ARMA-ARIMA model and the ARIMA-GARCH model, also providing results about the goodness of each of the proposed approaches. Moreover, we show how the aforementioned models behave if exogenous regressors, as the day of the week or the temperature, are additionally taken into account. Analysed methods are then exploited to perform the one-day ahead energy load prediction, where the main focus is on guessing the right sign of the energy load unbalance.

中文翻译：

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意大利电力市场中预测能源负荷不平衡的新颖方法

在本文中，我们通过不同的统计方法，例如指数平滑模型，ARMA-ARIMA模型和ARIMA-GARCH模型，研究了意大利日用电市场的统计特性，还提供了有关每种建议方法的优点。此外，我们显示了如果另外考虑外源回归变量（如星期几或温度），上述模型的行为。然后，利用分析的方法进行提前一天的能量负荷预测，其中主要重点是猜测能量负荷不平衡的正确迹象。