Work

Reinforcement Learning$\unicode{x2013}$Based Transient Response Shaping for Microgrids

Year: 2022

Type: preprint

Abstract: This work explores the usage of a supplementary controller for improving the transient performance of inverter$\unicode{x2013}$based resources (IBR) in microgrids. The supplementary controller is trained using a reinforcement learning (RL)$\unicode{x2013}$based algorithm to minimize transients in a power converter connected to a microgrid. The controller works autonomously to issue adaptive, intermediate set points based on the current state and trajectory of the observed or tracked variable. The ability of the designed controller to mitigate transients is verified on a medium voltage test system using PSCAD/EMTDC.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2207.05020

Authors: Venkataramanan, Ashwin, Mehrizi-Sani, Ali

Institution: Virginia Tech

Language: English

Topic: Microgrid Control and Optimization

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: green