Power load

This dataset contains three regional subsets comprising the electricity load and corresponding weather conditions collected from Australia, Panama, and Austria. Each subset includes time-synchronized records of power consumption along with key meteorological variables such as temperature, humidity, wind speed, and other locally available weather indicators. The data were gathered from regional grid operators and national meteorological sources to reflect the actual operating and environmental conditions of each region.

The net load data have collected from a Chinese industrial microgrid throughout 2017, with a high temporal resolution of 15-minute intervals, yielding 96 data points per day. The dataset includes multiple features, including ambient temperature, humidity, global solar irradiance, scattering radiation, and the average temperature of key operating equipment.

The data for PVs and loads are sourced from “Multi-agent reinforcement learning for active voltage control on power distribution networks”, collected from Jan. 1 st, 2012 to Dec. 31 st, 2014 over a 3-minute interval. In this paper, the data is described as follows: 

The data for PVs and loads are sourced from “Multi-agent reinforcement learning for active voltage control on power distribution networks”, collected from Jan. 1 st, 2012 to Dec. 31 st, 2014 over a 3-minute interval. In this paper, the data is described as follows: 

Load data from three actual datasets. The first dataset is from Homestead on the southeast coast of Florida and covers electricity load data from January 1, 2018 to June 22, 2020 and corresponding weather forecast data. The second dataset includes energy consumption data from smart meters installed in London homes. We selected data from 5,567 London households spanning the period from November 24, 2011 to February 27, 2014 participating in the Low Carbon London project led by UK Power Networks.