Coordinated Control of DFIG Based Wind Farms and SGs for Improving Transient Stability

Zhou, Ming; Dong, Zhe; Li, Hongyu; Gan, Chun; Li, Gengyin; Li, Fangxing

doi:10.1109/access.2018.2866252

Cited by 23 publications

(15 citation statements)

References 30 publications

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“…where M i is the generator's moment of inertia, δ i is the rotor angle, P mi is the mechanical power and P ei is the electromagnetic power [10].…”

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

confidence: 99%

“…where P c , P max and β are the offset, amplitude and initial phase, respectively, of P eg [10]. It can be found that P eg is the sine function of δ g in (9).…”

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

confidence: 99%

“…Considerable research has been conducted in the field of the TS of power system with wind farms [5]- [11]. These studies have contributed to analyzing the influence of wind power integration on power system TS [5]- [9], and improving system TS after large disturbances through wind turbine control and dispatching [10]- [12].…”

Section: Introductionmentioning

confidence: 99%

“…The EEAC method converts a multimachine system into a two-machine system through PCOI equivalence and further transforms it into an OMIB system to assess TS based on the EAC [18]. Due to its simple and effective model and clear mechanism, the method is not only used for transient stability prediction [18], [19] but also serves as the basis for impact analyses of wind power integration [8]- [10].…”

Section: Introductionmentioning

confidence: 99%

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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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“…where M i is the generator's moment of inertia, δ i is the rotor angle, P mi is the mechanical power and P ei is the electromagnetic power [10].…”

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

confidence: 99%

“…where P c , P max and β are the offset, amplitude and initial phase, respectively, of P eg [10]. It can be found that P eg is the sine function of δ g in (9).…”

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

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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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“…[11] presented a harmonics analysis of the double output induction generator. The applications of transient models include improvement of the DFIM controllers [12], as well as reducing the computational cost of large-scale transient stability studies [13]. This paper takes the transient domain a step further.…”

Section: Introductionmentioning

confidence: 99%

An Analytical Model for Detailed Transient Fault Analysis of Doubly-Fed Induction Machines

Maurer

Nøland

2020

2020 International Conference on Electrical Machines (ICEM)

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This paper presents an exact analytical solution to the two-phase and three-phase short-circuit events of the doublyfed induction machine (DFIM). The contribution is intended to strengthen the predictability of DFIMs under the design stage or for control tuning purposes and reduce the computational costs of large-scale transient stability studies of the interconnected power system. In general, the approach enables to simplify and improve the analysis DFIMs. The original analytical equations are derived from first principles. A case study of a doublyfed induction generator (DFIG) is considered, where the "large machine approximation" is shown to be valid as well. The analytical equations are used to predict the torque transients in different handpicked transient scenarios and assessed against numerical simulations. Finally, the proposed analytical model shows excellent agreement with the numerical results in the SIMSEN environment.

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Transient stability improvement based on out-of-step prediction

Sobbouhi

Vahedi

2021

Electric Power Systems Research

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Coordinated Control of DFIG Based Wind Farms and SGs for Improving Transient Stability

Cited by 23 publications

References 30 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

An Analytical Model for Detailed Transient Fault Analysis of Doubly-Fed Induction Machines

Transient stability improvement based on out-of-step prediction

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