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Exploration of Artificial-intelligence Oriented Power System Dynamic Simulators

Authors :
Tannan Xiao
Ying Chen
Jianquan Wang
Shaowei Huang
Weilin Tong
Tirui He
Source :
Journal of Modern Power Systems and Clean Energy, Vol 11, Iss 2, Pp 401-411 (2023)
Publication Year :
2023
Publisher :
IEEE, 2023.

Abstract

With the rapid development of artificial intelligence (AI), it is foreseeable that the accuracy and efficiency of dynamic analysis for future power system will be greatly improved by the integration of dynamic simulators and AI. To explore the interaction mechanism of power system dynamic simulations and AI, a general design for AI-oriented power system dynamic simulators is proposed, which consists of a high-performance simulator with neural network supportability and flexible external and internal application programming interfaces (APIs). With the support of APIs, simulation-assisted AI and AI-assisted simulation form a comprehensive interaction mechanism between power system dynamic simulations and AI. A prototype of this design is implemented and made public based on a highly efficient electromechanical simulator. Tests of this prototype are carried out in four scenarios including sample generation, AI-based stability prediction, data-driven dynamic component modeling, and AI-aided stability control, which prove the validity, flexibility, and efficiency of the design and implementation for AI-oriented power system dynamic simulators.

Details

Language :
English
ISSN :
21965420
Volume :
11
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Journal of Modern Power Systems and Clean Energy
Publication Type :
Academic Journal
Accession number :
edsdoj.68732bf920a84c129a70a4d4e9ad3a84
Document Type :
article
Full Text :
https://doi.org/10.35833/MPCE.2022.000099