Towards an AI-friendly cross-timescale simulation and analysis platform for electric distribution systems

Substantial changes are occurring in electric distribution systems due to ambitious targets towards carbon-neutrality in many regions around the world. One of the key challenges is how to analyze the interactions of massive amount of energy end-users with the electric distribution grid operator. In...

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Bibliographic Details
Main Authors: Dongqi Wu, Rayan El Helou, Le Xie
Format: Article
Language:English
Published: Tsinghua University Press 2022-03-01
Series:iEnergy
Subjects:
Online Access:https://www.sciopen.com/article/10.23919/IEN.2022.0009
Description
Summary:Substantial changes are occurring in electric distribution systems due to ambitious targets towards carbon-neutrality in many regions around the world. One of the key challenges is how to analyze the interactions of massive amount of energy end-users with the electric distribution grid operator. In this paper, we introduce a comprehensive simulation platform, AI4Dist, that is capable to perform a wide collection of distribution system studies that capture multiple timescales ranging from market planning to transient event analysis. AI4Dist is designed to effortlessly integrate with off-the-shelf machine learning packages and algorithm implementations. We envision that AI4Dist will serve as a platform to empower researchers with different expertise to contribute to the development of low carbon electricity sector.
ISSN:2771-9197