Open Access

ARTICLE

Novel Static Security and Stability Control of Power Systems Based on Artificial Emotional Lazy Q-Learning

Tao Bao^*, Xiyuan Ma, Zhuohuan Li, Duotong Yang, Pengyu Wang, Changcheng Zhou

Digital Grid Research Institute, Southern Power Grid, Guangzhou, 510000, China

* Corresponding Author: Tao Bao. Email:

Energy Engineering 2024, 121(6), 1713-1737. https://doi.org/10.32604/ee.2023.046150

Received 20 September 2023; Accepted 16 November 2023; Issue published 21 May 2024

Abstract

The stability problem of power grids has become increasingly serious in recent years as the size of novel power systems increases. In order to improve and ensure the stable operation of the novel power system, this study proposes an artificial emotional lazy Q-learning method, which combines artificial emotion, lazy learning, and reinforcement learning for static security and stability analysis of power systems. Moreover, this study compares the analysis results of the proposed method with those of the small disturbance method for a stand-alone power system and verifies that the proposed lazy Q-learning method is able to effectively screen useful data for learning, and improve the static security stability of the new type of power system more effectively than the traditional proportional-integral-differential control and Q-learning methods.

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Keywords

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