Electricity-Theft

该数据集是由GridLab-D模拟工具生成的综合数据集，包含了31天内以15分钟为间隔的数据，并附加了电压和电流等额外属性。该数据集不仅包含了能源消耗数据，还包含了其他属性信息；数据集被划分为训练集（70%）、验证集（10%）和测试集（20%）。其规模涉及多位用户，他们的能源消耗行为各不相同。任务旨在针对不同的消费模式进行能源消耗预测以及能源盗窃的检测。

This comprehensive dataset was generated using the GridLab-D simulation tool. It contains data sampled at 15-minute intervals over a 31-day period, with supplementary attributes including voltage and current. In addition to energy consumption data, the dataset includes various other attribute information. The dataset is split into three subsets: the training set (70%), validation set (10%), and test set (20%). It covers multiple users with heterogeneous energy consumption behaviors. The targeted tasks include energy consumption prediction based on different consumption patterns and energy theft detection.