Inertia Characteristic of DFIG-Based WT Under Transient Control and its Impact on the First-Swing Stability of SGs

Ying, Jie; Yuan, Xiaoming; Hu, Jiabing

doi:10.1109/tec.2017.2698521

Cited by 30 publications

(10 citation statements)

References 22 publications

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“…where P ei is the original electromagnetic power of synchronous generator i and P ei , I i , and ψ i are the electromagnetic power increment and the amplitude and angle of the equivalent injection current associated with wind power for synchronous motor i. Subsequently, the equivalent OMIB system motion equation in equation ( 2) can be modified to M gδg = P mg − P eg (7) where M g , δ g , and P mg are defined in the same way as in equation (2). P eg is the corrected equivalent electromagnetic power after wind power is connected and can be expressed as…”

Section: P-δ Fitting Methods For the Ts Prediciont Of Wind Power-integrated Systemmentioning

confidence: 99%

An Integrated Model-Driven and Data-Driven Method for On-Line Prediction of Transient Stability of Power System With Wind Power Generation

Jiang

Lin

et al. 2020

IEEE Access

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The increase of wind power permeability in modern power grid has turned rapid and accurate transient stability (TS) prediction into a more challenging issue. To accurately and promptly perform online TS prediction for power system with doubly fed induction generator (DFIG)-based wind farms, an integrated model-driven and data-driven method is proposed in this paper. The influence of DFIGs is considered in the transformation to guarantee the accuracy of the equivalent one machine infinite bus (OMIB) model transformed from the target system. The P-δ trajectory of the OMIB is fitted with the generator-terminal information to predict TS. To improve the prediction speed, an extreme learning machine (ELM)-based method is utilized to process the other DFIG and system information and evaluate the system status immediately after failure. The simulation results verify that the proposed method can reduce the dependence of the data-driven method on the data sample size and improve the speed and accuracy of online prediction.INDEX TERMS Extreme learning machine (ELM), doubly fed induction generators (DFIG), transient stability, trajectory fitting.

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Section: P-δ Fitting Methods For the Ts Prediciont Of Wind Power-integrated Systemmentioning

confidence: 99%

An Integrated Model-Driven and Data-Driven Method for On-Line Prediction of Transient Stability of Power System With Wind Power Generation

Jiang

Lin

et al. 2020

IEEE Access

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“…These researches have shown that numerous factors such as pre‐fault conditions, generator saturation, microgrid electric specifications, system loading restrictions, synchronous generators damping ratio, fault clearing time and microgrid overall inertia can affect the transient stability. In particular, the inertia is the factor with the greatest impact on the behavior of the first swing stability in synchronous machines as an important type of transient stability 43‐46 . Therefore, a wide variety of techniques have been proposed for the improvement of transient stability in the literature as presented in Table 1.…”

Section: Introductionmentioning

confidence: 99%

A first swing stability improvement approach in microgrids with synchronous distributed generators

Fayazi

Moazzami

Fani

et al. 2021

Int Trans Electr Energ Syst

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Summary One of the effective approaches to maintain power generation consumption balance during contingencies and therefore transient stability of the system is instantaneous rise of generation power and changing the generators excitation control system. This article proposes an auxiliary droop controller, which can replace generator main controller in order to maintain the transient stability of the system at the time of fault occurrence. Because of its linear structure, the proposed droop controller has a high response speed, so it can well supply the additional power demand given the rapid changes of the electric power demand at the time of fault occurrence. The proposed controller replaces the main controller of the generator that has the most impact on the maintaining system transient stability. Therefore, in the proposed method, first, the most efficient generator of the grid is identified using trajectory sensitivity analysis. Then, to maintain balance between power generation and consumption at the worst time of fault occurrence, the smallest amount of auxiliary controller slope is calculated through trajectory sensitivity analysis. Therefore, under any contingencies occurrence in the system, replacing the main controller with an appropriate auxiliary one will guarantee the transient stability of the system. The affectivity of the proposed method is shown using simulations on the IEEE 33‐bus test system. The simulation results show that the proposed auxiliary control method can lead to the at least 20% increase of critical clearing time (CCT) compared to the conventional droop control method. Furthermore, it is robust against the changes of inertia, up to 5%, as one of the main parameters in the first swing stability of the system.

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“…Asynchronous operation of a power system may result in high transient mechanical torque and currents. As a result, mechanical and thermal damage can be experienced if instability is not detected and the islanded synchronous generators are not tripped [2].…”

Section: Introductionmentioning

confidence: 99%

Generator‐based threshold for transient stability assessment

et al. 2019

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Power systems are frequently subjected to variations of the operating conditions due to the occurrence of contingencies such as faults, load or generator tripping. These disturbances might enforce the system to enter the instability region and thus deteriorate its overall performance. This paper proposes a systematic approach for transient stability assessment using generator-based threshold. An individual stability limit is designed for each generator instead of using only one pre-defined threshold for all generators. The considered contingencies are characterized by a fault type, location, loading condition and critical clearing time to consider wide range of operating conditions. Two fault locations are only considered to reduce the search space for stability limits; the generator terminals and mid of transmission lines. The critical clearing time is used to find the maximum relative rotor angle (MRRA) of individual generators attained during the entire time domain simulation. The MRRA of each generator represents the maximum angle which can be reached without losing synchronism at a given contingency. Conservative stability limits are drawn around the minimum stable drift of each generator which is chosen from the set of MRRAs of all contingencies. The effectiveness of the proposed approach is tested using the modified New-England, 39bus system.

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Inertia Characteristic of DFIG-Based WT Under Transient Control and its Impact on the First-Swing Stability of SGs

Cited by 30 publications

References 22 publications

An Integrated Model-Driven and Data-Driven Method for On-Line Prediction of Transient Stability of Power System With Wind Power Generation

An Integrated Model-Driven and Data-Driven Method for On-Line Prediction of Transient Stability of Power System With Wind Power Generation

A first swing stability improvement approach in microgrids with synchronous distributed generators

Generator‐based threshold for transient stability assessment

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