Mitigating sub-synchronous oscillation using intelligent damping control of DFIG based on improved TD3 algorithm with knowledge fusion

The occurrence of sub-synchronous oscillation (SSO) phenomenon in doubly-fed induction generators (DFIGs)-based wind turbines threatens the secure and stable operation of the power grid. Conventional sub-synchronous damping controllers encounter challenges in adapting to the dynamic operating condit...

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Bibliographic Details
Published in:Scientific reports 2024-06, Vol.14 (1), p.14692-14, Article 14692
Main Authors: Liu, Ge, Liu, Jun, Liu, Andong
Format: Article
Language:English
Subjects:
639/166
639/4077
639/705/117
Adaptability
Adaptive output signal selection
Algorithms
Controllers
Decision making
Deep learning
Design
Humanities and Social Sciences
Intelligent damping controller
Knowledge
Knowledge fusion
Mathematical models
Methods
multidisciplinary
Regression analysis
Robust control
S-TD3 algorithm
Science
Science (multidisciplinary)
Sub-synchronous oscillation
Turbines
Wind farms
Wind power
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Summary:The occurrence of sub-synchronous oscillation (SSO) phenomenon in doubly-fed induction generators (DFIGs)-based wind turbines threatens the secure and stable operation of the power grid. Conventional sub-synchronous damping controllers encounter challenges in adapting to the dynamic operating conditions of power systems. This paper introduces an Intelligent Sub-Synchronous Damping Controller (I-SSDC) for DFIGs that integrates deep reinforcement learning (DRL) and knowledge to address the limitations of conventional methods for SSO mitigation. The initial step involves formulating a framework for I-SSDC using the improved twin delayed deep deterministic policy gradient (TD3) algorithm incorporating Softmax. Following this, a surrogate model is constructed, employing Weighted Linear Regression and regularization. This model is designed to identify the predominant influencing factors of SSO, focusing on the selection of the output signal (installation position) to optimize decision-making in I-SSDC. The objective is to enhance the controller’s environmental adaptability and interpretability. Moreover, knowledge and experience related to SSOs are integrated into agent training to improve the exploration efficiency of the agent. Case studies under various operating conditions of the test power system validate the efficacy of the proposed I-SSDC in suppressing SSOs.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-65372-y