Parallel System Based Quantitative Assessment and Self-evolution for Artificial Intelligence of Active Power Corrective Control

Parallel System Based Quantitative Assessment and Self-evolution for Artificial Intelligence of Active Power Corrective Control

In artificial intelligence (AI) based-complex power system management and control technology, one of the urgent tasks is to evaluate AI intelligence and invent a way of autonomous intelligence evolution. However, there is, currently, nearly no standard technical framework for objective and quantitat...

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Bibliographic Details
Main Authors: Tianyun Zhang, Jun Zhang, Feiyue Wang, Peidong Xu, Tianlu Gao, Haoran Zhang, Ruiqi Si
Format: Article
Language:English
Published: China electric power research institute 2024-01-01
Series:CSEE Journal of Power and Energy Systems
Subjects:
AI quantitative intelligence assessment and self-evolution
automated reinforcement learning
Bayesian optimization
corrective control
parallel system
Online Access:https://ieeexplore.ieee.org/document/10375965/

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