Classification of load forecasting studies by forecasting problem to select load forecasting techniques and methodologies
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This article proposes a two-dimensional classification methodology to select the relevant forecasting tools developed by the scientific community based on a classification of load forecasting studies. The inputs of the classifier are the articles of the literature and the outputs are articles classified into categories. The classification process relies on two couple of parameters that defines a forecasting problem. The temporal couple is the forecasting horizon and the forecasting resolution. The system couple is the system size and the load resolution. 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 cleansing data techniques and the error metrics. This process is illustrated by reviewing and classifying thirty-four articles.
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