  To facilitate the development of reinforcement learning (RL) based power
distribution system Volt-VAR control (VVC), this paper introduces a suite of
open-source datasets for RL-based VVC algorithm research that is sample
efficient, safe, and robust. The dataset consists of two components: 1. a
Gym-like VVC testing environment for the IEEE-13, 123, and 8500-bus test
feeders and 2. a historical operational dataset for each of the feeders.
Potential users of the dataset and testing environment could first train an
sample-efficient off-line (batch) RL algorithm on the historical dataset and
then evaluate the performance of the trained RL agent on the testing
environments. This dataset serves as a useful testbed to conduct RL-based VVC
research mimicking the real-world operational challenges faced by electric
utilities. Meanwhile, it allows researchers to conduct fair performance
comparisons between different algorithms.
