Short-term load prediction method based on artificial intelligence, computer equipment and storage medium

The invention discloses a short-term load prediction method based on artificial intelligence, computer equipment and a storage medium, and the method comprises the following steps: firstly, selecting a load feature, a lag feature, a time feature and a meteorological feature which have influences on a load, and constructing a dynamic coding feature for holidays and festivals with different time lengths; then, modeling is carried out by adopting a Seq2Seq network, and a short-term load prediction model is established; and finally, predicting the short-term load by adopting the short-term load prediction model. According to the invention, a festival and holiday dynamic coding mode is constructed according to the lengths of different festivals and holidays, and a LightGBM-based festival and holiday load model is established in combination with numerical mode prediction, so that the festival and holiday load prediction effect is improved. 本发明公开了一种基于人工智能的短期负荷预测方法、计算机设备及存储介质，其中短期负荷预测方法包括如下步骤：首先，选取对负荷具有影响的负荷特征、滞后特征、时