A General Equivalent Modeling Method for DFIG Wind Farms Based on Data-Driven Modeling

Zhu, Qianlong; Tao, Jun; Deng, Tianbai; Zhu, Meiling

doi:10.3390/en15197205

Cited by 5 publications

(2 citation statements)

References 24 publications

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“…Under the test conditions of Figure 7, the active and reactive power errors of the proposed equivalent node model are calculated according to Equations ( 2) and (3), respectively. To demonstrate the performance of the proposed model in detail, the differences in accuracy at different stages of the electromechanical transient period, i.e., the pre-fault phase, the early fault phase, the quasi-steady-state phase during the fault, the early fault-recovery phase, and the quasi-steady-state phase during the fault recovery [6,39], are illustrated in Figures 8 and 9. In addition, the average errors during the entire transient process are listed in Table 1.…”

Section: Example Analysismentioning

confidence: 99%

Refined Equivalent Modeling Method for Mixed Wind Farms Based on Small Sample Data

Zhu,

Xiong,

Wang

et al. 2023

Energies

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For equivalent modeling of mixed wind farms (WFs), existing clustering indicators cannot consider the complex coupling characteristics between different types of wind turbines (WTs). In this paper, a refined equivalent modeling approach based on artificial intelligence technology is proposed. Firstly, the electromechanical transient performance of mixed WFs is analyzed. The WT type, wind speed and direction, and voltage dip are considered the dominant factors affecting the external dynamic response of mixed WFs. Secondly, the equivalent node model is established, including the selection of independent and dependent variables. Then, the multiple artificial neural networks (ANNs) are trained one by one based on small sample data, to fit the nonlinear relationship between the dependent variables and the independent variables. Finally, the dynamic response of the power systems with a mixed WF is simulated in the MATLAB platform. A comparison of the errors in electromechanical phenomena demonstrates that the proposed model can reflect the external characteristics of the test mixed WF in different wind conditions and voltage dips.

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Section: Example Analysismentioning

confidence: 99%

Refined Equivalent Modeling Method for Mixed Wind Farms Based on Small Sample Data

Zhu,

Xiong,

Wang

et al. 2023

Energies

Self Cite

View full text Add to dashboard Cite

show abstract

“…Due to the length limitations and the specific research focus, an in-depth elaboration on the specific implementation steps of PSO will not be undertaken here. For a comprehensive understanding of the details and applications of PSO, we direct the reader to consult the reference provided in [33,34].…”

Section: Parameters Of the Aggregated Modelmentioning

confidence: 99%

Dynamic Equivalent Modeling of a Large Renewable Power Plant Using a Data-Driven Degree of Similarity Method

Liao,

Zhu,

et al. 2023

Energies

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This paper aims to develop a novel method for the dynamic equivalence of a renewable power plant, ultimately contributing to power system modeling and enhancing the integration of renewable energy sources. In order to address the challenge posed by clusters of renewable generation units during the equivalence process, the paper introduces the degree of similarity to assess similarity features under data. After leveraging the degree of similarity in conjunction with data-driven techniques, the proposed method efficiently entails dividing numerous units in a large-scale plant into distinct clusters. Additionally, the paper adopts practical algorithms to determine the parameters for each aggregated cluster and streamline the intricate collector network within the renewable power plant. The equivalent model of a renewable power plant is thereby conclusively derived. Comprehensive case studies are conducted within a practical offshore wind plant setting. These case studies are accompanied by simulations, highlighting the advantages and effectiveness of the proposed method, offering an accurate representation of the renewable power plant under diverse operating conditions.

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Power quality assessment in different wind power plant models considering wind turbine wake effects

Khatamiaghda,

Bahraminejad,

Fadaeinedjad

2023

Clean Energy

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The intense increase in the installed capacity of wind farms has required a computationally efficient dynamic equivalent model of wind farms. Various types of wind-farm modelling aim to identify the accuracy and simulation time in the presence of the power system. In this study, dynamic simulation of equivalent models of a sample wind farm, including single-turbine representation, multiple-turbine representation, quasi-multiple-turbine representation and full-turbine representation models, are performed using a doubly-fed induction generator wind turbine model developed in DIgSILENT software. The developed doubly-fed induction generator model in DIgSILENT is intended to simulate inflow wind turbulence for more accurate performance. The wake effects between wind turbines for the full-turbine representation and multiple-turbine representation models have been considered using the Jensen method. The developed model improves the extraction power of the turbine according to the layout of the wind farm. The accuracy of the mentioned methods is evaluated by calculating the output parameters of the wind farm, including active and reactive powers, voltage and instantaneous flicker intensity. The study was carried out on a sample wind farm, which included 39 wind turbines. The simulation results confirm that the computational loads of the single-turbine representation (STR), the multiple-turbine representation and the quasi-multiple-turbine representation are 1/39, 1/8 and 1/8 times the full-turbine representation model, respectively. On the other hand, the error of active power (voltage) with respect to the full-turbine representation model is 74.59% (1.31%), 43.29% (0.31%) and 7.19% (0.11%) for the STR, the multiple-turbine representation and the quasi-multiple representation, respectively.

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A General Equivalent Modeling Method for DFIG Wind Farms Based on Data-Driven Modeling

Cited by 5 publications

References 24 publications

Refined Equivalent Modeling Method for Mixed Wind Farms Based on Small Sample Data

Refined Equivalent Modeling Method for Mixed Wind Farms Based on Small Sample Data

Dynamic Equivalent Modeling of a Large Renewable Power Plant Using a Data-Driven Degree of Similarity Method

Power quality assessment in different wind power plant models considering wind turbine wake effects

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