论文标题
从点预测到多元概率的预测：舍凯克洗牌的日常电价预测
From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting
论文作者
论文摘要
建模价格风险对于能源市场的经济决策至关重要。除了单一价格的风险外，多个价格的依赖结构通常是相关的。因此，我们提出了一种通用且易于实现的方法，用于基于日期电力价格的单变量预测来创建多元概率的预测。虽然每个单变量预测是指当天的24小时之一，但多元预测分布模型跨小时。所提出的方法基于简单的Copula技术和可选的时间序列组件。我们说明了Lago等人最近提供的五个基准数据集的方法。 （2020）。此外，我们展示了一个示例，用于构建连续电价加权总和的现实预测间隔，例如，定价个体负载概况所需的示例。
Modeling price risks is crucial for economic decision making in energy markets. Besides the risk of a single price, the dependence structure of multiple prices is often relevant. We therefore propose a generic and easy-to-implement method for creating multivariate probabilistic forecasts based on univariate point forecasts of day-ahead electricity prices. While each univariate point forecast refers to one of the day's 24 hours, the multivariate forecast distribution models dependencies across hours. The proposed method is based on simple copula techniques and an optional time series component. We illustrate the method for five benchmark data sets recently provided by Lago et al. (2020). Furthermore, we demonstrate an example for constructing realistic prediction intervals for the weighted sum of consecutive electricity prices, as, e.g., needed for pricing individual load profiles.
