We introduce a four-factor arithmetic model for electricity baseload spot prices in Germany and Austria. The model consists of a deterministic seasonality and trend function, both short- and long-term stochastic components, and exogenous factors such as the daily wind energy production forecasts, the residual demand and the wind penetration index. We describe the short-term stochastic factor by a Lévy semi-stationary (LSS) process, and the long-term component is modelled as a Lévy process with increments belonging to the class of generalised hyperbolic distributions.

We derive the corresponding futures prices and develop an inference methodology for our multi-factor model. The methodology allows to infer the various factors in a step-wise procedure taking empirical spot prices, futures prices and wind energy production and total load data into account.

Our empirical work shows that taking into account the impact of the wind energy generation on the prices improves the goodness of fit. Moreover, we demonstrate that the class of LSS processes can be used for modelling the exogenous variables including wind energy production, residual demand and the wind penetration index.

我们介绍了德国和奥地利电力基荷现货价格的四因素算术模型。该模型由确定性的季节性和趋势函数、短期和长期随机分量以及外生因素（如每日风能生产预测、剩余需求和风能渗透指数）组成。我们通过 Lévy 半平稳 (LSS) 过程描述短期随机因子，并将长期分量建模为 Lévy 过程，增量属于广义双曲线分布类。

我们推导出相应的期货价格并为我们的多因素模型开发一种推理方法。该方法允许在考虑经验现货价格、期货价格和风能生产以及总负荷数据的逐步程序中推断各种因素。

我们的实证工作表明，考虑到风能发电对价格的影响可以提高拟合优度。此外，我们证明了 LSS 过程类别可用于建模外生变量，包括风能生产、剩余需求和风能渗透指数。