Improving DFIG performance under fault scenarios through evolutionary reinforcement learning based control

Gao, Wei; Fan, Rui; Huang, Renke; Huang, Qiuhua; Du, Yan; Qiao, Wei; Wang, Shaobu; Gao, Wenzhong

doi:10.1049/gtd2.12563

Improving DFIG performance under fault scenarios through evolutionary reinforcement learning based control

Journal Article · Wed Aug 03 00:00:00 EDT 2022 · IET Generation, Transmission, & Distribution

DOI:https://doi.org/10.1049/gtd2.12563· OSTI ID:1887238

Gao, Wei ^[1]; ^[1]; Huang, Renke ^[2]; ^[3]; Du, Yan ^[3]; Qiao, Wei ^[4]; Wang, Shaobu ^[3]; Gao, Wenzhong ^[1]

Univ. of Denver, CO (United States)
Shanghai Jiao Tong Univ. (China)
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Univ. of Nebraska, Lincoln, NE (United States)

The double-fed induction generator (DFIG) usually experiences high rotor current and DC capacitor link voltage during system fault events. In this paper, a novel data-driven approach is proposed to enhance the DFIG performance under fault scenarios. An advanced reinforcement learning (RL) algorithm called guided surrogate-gradient-based evolution strategy (GSES) is used to control the DFIG power and capacitor DClink voltage by adjusting the optional reference signals. This controller is able to prevent the rotor of DFIG from overcurrent risk and maintain the grid-connected operation. The proposed GSES-based control algorithm was evaluated through simulations on a 3.6-MW DFIG in PSCAD/EMTDC software. Results have validated the effectiveness of the proposed GSESbased control algorithm in improving the DFIG performance under fault scenarios.

View Accepted Manuscript (DOE)

Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE Office of Electricity (OE)

Grant/Contract Number:: AC05-76RL01830

OSTI ID:: 1887238

Report Number(s):: PNNL-SA-172973

Journal Information:: IET Generation, Transmission, & Distribution, Journal Name: IET Generation, Transmission, & Distribution Journal Issue: 19 Vol. 16; ISSN 1751-8687

Publisher:: Institution of Engineering and Technology (IET)Copyright Statement

Country of Publication:: United States

Language:: English

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