A two-stage frequency response method for DFIGs under variable wind speeds

Meng, Lingcong; Qin, Chao; Zeng, Yuan; Sun, Bing; Chen, Qichao; Chen, Wei

doi:10.1016/j.epsr.2023.109813

Cited by 3 publications

(1 citation statement)

References 30 publications

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“…Through the multi-dimensional visualization of the label information, the label information of a single supplier or the statistical data of the group supplier can be displayed respectively. The display diagram and related data output by the portrait can be applied to the fine operation of various departments of electric power enterprises, and provide a more scientific reference for management decisions [3] .…”

Section: Theoretical Construction Of Portrait System For Power Enterp...mentioning

confidence: 99%

Research on power enterprise supplier evaluation based on portrait technology

Shen,

Zhou,

Wang

et al. 2024

Third International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2023)

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With the digital transformation of traditional enterprises and the acceleration of modern supply chain construction, for power enterprises, the selection of high-quality suppliers is related to the safe and stable operation of the power grid. However, with the large number of suppliers of power enterprises and the large types of materials involved, there are various challenges in information and intelligent construction. This paper uses the portrait technology to extract the label information from the massive data for data analysis. It innovatively combines the portrait technology with the supplier management theory, designs the portrait system for power suppliers, and provides the path of label database construction and supplier evaluation system construction for the supplier evaluation of power enterprises.

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Section: Theoretical Construction Of Portrait System For Power Enterp...mentioning

confidence: 99%

Research on power enterprise supplier evaluation based on portrait technology

Shen,

Zhou,

Wang

et al. 2024

Third International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2023)

View full text Add to dashboard Cite

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RETRACTED: Enhancing the low-voltage ride-through capability of a wind turbine double-fed induction generator using hybrid model contains an adaptive neurofuzzy inference system controller and a crowbar circuit.

2024

Preprint

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The focal target of this paper is to increase the LVRT of the DFIG driven by WT. This task is realized, firstly, by inserting a crowbar circuit (CB) into rotor circuit (RC), in case of voltage dip (VD), to guard it from high current and high voltage that could result from the transient flux produced by the VD. In case of no CB circuit, the system may be vulnerable to instability. Secondly, a proposed ANFIS controller is proposed to control both the rotor side converter (RSC) and the grid side converter (GSC). While the RSC controller regulates the electromagnetic torque, the GSC controller control both the real power (RP) and reactive power (QP) supplied to the system during normal operation conditions beside with it keeps the value of the dc link voltage (DCLV) fixed. To enhance the LVRT, the GSC is controlled such that it injects the necessary reactive power required during severe voltage dips to improve the LVRT competency of the DFIG. From the results, it is obvious that the hybrid ANFIS and crowbar technique provides an improved LVRT response in challenging operating conditions.

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