The key contribution of this paper is to propose a classification into two dimensions of the load forecasting studies to decide which forecasting tools to use in which case. This classification aims to provide a synthetic view of the relevant forecasting techniques and methodologies by forecasting problem. In addition, the key principles of the main techniques and methodologies used are summarized along with the reviews of these papers. The classification process relies on two couples of parameters that define a forecasting problem. Each article is classified with key information about the dataset used and the forecasting tools implemented: the forecasting techniques (probabilistic or deterministic) and methodologies, the data cleansing techniques, and the error metrics. The process to select the articles reviewed in this paper was conducted into two steps. First, a set of load forecasting studies was built based on relevant load forecasting reviews and forecasting competitions. The second step consisted in selecting the most relevant studies of this set based on the following criteria: the quality of the description of the forecasting techniques and methodologies implemented, the description of the results, and the contributions. This paper can be read in two passes. The first one by identifying the forecasting problem of interest to select the corresponding class into one of the four classification tables. Each one references all the articles classified across a forecasting horizon. They provide a synthetic view of the forecasting tools used by articles addressing similar forecasting problems. Then, a second level composed of four Tables summarizes key information about the forecasting tools and the results of these studies. The second pass consists in reading the key principles of the main techniques and methodologies of interest and the reviews of the articles.

中文翻译：

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通过预测问题对负荷预测研究进行分类以选择负荷预测技术和方法

本文的主要贡献是将负荷预测研究分为两个维度，以决定在哪种情况下使用哪种预测工具。该分类旨在通过预测问题提供相关预测技术和方法的综合视图。此外，还总结了所使用的主要技术和方法的关键原则以及对这些论文的评论。分类过程依赖于定义预测问题的两对参数。每篇文章都使用有关使用的数据集和实施的预测工具的关键信息进行分类：预测技术（概率或确定性）和方法、数据清理技术和错误度量。选择本文中评论的文章的过程分为两个步骤。首先，基于相关的负荷预测回顾和预测竞赛，建立了一套负荷预测研究。第二步包括根据以下标准选择该组最相关的研究：所实施的预测技术和方法的描述质量、结果描述和贡献。这篇论文可以分两遍阅读。第一个通过识别感兴趣的预测问题来选择相应的类进入四个分类表之一。每一篇都引用了跨预测范围分类的所有文章。它们提供了解决类似预测问题的文章所使用的预测工具的综合视图。然后，由四个表格组成的第二层总结了有关预测工具和这些研究结果的关键信息。第二遍包括阅读感兴趣的主要技术和方法的关键原则以及文章的评论。