Dataset for An Application of Machine Learning for a Smart Grid Resource Allocation Problem

The main dataset from a year’s of running the SGRA on the HPC (Summit) environment is divided into two sub-datasets. The two sub-datasets are used to develop machine learning methods to obtain relationships between aggregator profits and customer loads, and electricity prices, respectively. The first and second sub-datasets consist of 5,555 and 365 observations, respectively. Each dataset is divided into two groups: training data (75%) and test data (25%).

该数据集源自于在HPC（Summit）环境中运行SGRA（一种数据聚合算法）一年的主要数据集，该数据集被划分为两个子数据集。这两个子数据集旨在开发机器学习方法，以获取聚合商利润与客户负载、电价之间的关联关系。第一个和第二个子数据集分别包含5,555和365个观测值。每个数据集均被分为两组：训练数据（占比75%）和测试数据（占比25%）。