Abstract:The current research on probabilistic load forecasting models mostly combines machine learning algorithms and quantile regression methods to construct quantile models. This paper first summarizes and combs the commonly used quantile regression forecast models. Combined with the actual data, we analyzed the main factors affecting the performance of probabilistic load forecasting and attempted to elaborate on the influencing mechanism. Then, a quantile regression probabilistic load forecasting strategy based on … Show more
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