ARIES: Low Voltage smArt gRid dIscrete Event Simulator to Enable Large Scale Learning in the Power Distribution Networks

Abstract

Accurate software based simulation of (complex) dynamic and, possibly, stochastic systems is a key component of the design and test of control strategies. Simulation tools developed according to software design best practices provide engineers and researchers with efficient and easy to use representations of the world. Hence, allowing for faster control algorithms design and test. Here we present ARIES, a (low voltage) smArt gRid dIscrete Event Simulator meant to enable large scale learning and easy smart grid applications design and testing. ARIES is designed according to object oriented best practices, and it is implemented in Python 3. ARIES is equipped with a REST API to actively interact with the simulations, it features a simulation results storage system based on a MongoDB database, and a event management system based on a redis in-memory data structure store used as message broker.