The mechanism of DFIGs grouping tripped off from power grid

Mu, Gang; Wang, Jian; Yan, Gangfeng

doi:10.17775/cseejpes.2016.01530

Cited by 13 publications

(8 citation statements)

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“…This inequality causes the power oscillation and acceleration of the rotor (see Figure 2(a)). If the rotor speed exceeds a certain margin, which is called the critical speed, the DFIG must be tripped off from the grid [8]. To simplify the concept of the critical speed of the generator, its power versus rotor speed curve can be assisted.…”

Section: Power Versus Rotor Speed Curve and Stability Marginmentioning

confidence: 99%

“…These disturbances might be caused by such reasons as short-circuit, load shedding and so on [4]. Thus, it is quite obvious that DFIG based wind turbines (WTs) need specific protection circuits to protect them against grid faults [5][6][7][8]. In this regard, various protection systems are proposed in recent years, that the crowbar circuit is the most commonly used protection schemes in the wind farms [5].…”

Section: Introductionmentioning

confidence: 99%

“…Under this transient condition, the equilibrium between mechanical and electrical energy is lost, which results in electromechanical oscillations and acceleration of the rotor [6]. These oscillations might cause the unstable condition, and therefore the DFIG must be tripped off from the network [8]. Accordingly, accurate detection of transient instability (TI) in grid-connected DFIG based WTs can be considered a major concern in wind power plants.…”

Section: Introductionmentioning

confidence: 99%

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An Analytical method for detecting instability in grid‐connected doubly‐fed induction generator

Nasab

Yaghobi

2021

IET Renewable Power Gen

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Doubly‐fed induction generator (DFIG) is among the most attractive technologies in wind farms. As the penetration of wind power into the grid has increased in recent years, protecting of wind farm's generators against grid disturbances has become a major issue for the power system industry. Transient instability (TI) is among the most frequent phenomena due to severe grid disturbances. This phenomenon might cause significant damages to network equipment. In DFIG based wind turbine (WT), when the crowbar circuit is activated, the rotor winding is short‐circuited and the power converter is blocked. At this moment, the DFIG operational mode is temporarily changed to squirrel‐cage induction generator (SCIG). This lead to reactive power absorption and voltage drop, that might cause electromechanical oscillations and unstable condition. This study presents an analytical method for detection TI of a grid‐connected DFIG based on analysis of angular velocity and acceleration data, which are readily obtained from locally measured quantities. This technique works on a setting‐free manner, i.e. revising would not be required even when the network configuration changes, which is a favourable feature in protective relaying. The performance of the proposed method is verified using MATLAB/Simulink. Simulation results prove the method's reliability and simplicity.

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Section: Power Versus Rotor Speed Curve and Stability Marginmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Analytical method for detecting instability in grid‐connected doubly‐fed induction generator

Nasab

Yaghobi

2021

IET Renewable Power Gen

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“…The doubly fed induction generator (DFIG)-based wind turbine, as the main model in the current wind power industry [1], has been widely used because of the excellent control performance of the active and reactive power [2,3]. However, the increasing penetration of wind power brings more complex challenges to the connected system [4,5]. Long-distance and large-capacity high voltage transmission technology is generally adopted for wind farms which are located at the ends of the grid with an insufficient support capacity of the voltage [6,7].…”

Section: Introductionmentioning

confidence: 99%

An Active Voltage Coordinate Control Strategy of DFIG-Based Wind Farm with Hybrid Energy Storage System

et al. 2021

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In a power system with wind farms, the point of common coupling (PCC) usually suffers from voltage instability under large wind speed variations and the load impact. Using the internal converter of a doubly fed induction generator (DFIG)-based wind turbine to provide voltage support auxiliary service is an effective scheme to suppress the voltage fluctuation at PCC. To satisfy the reactive power demand of the connected grid, an active voltage coordinate control strategy with the hybrid energy storage system of the wind farm is proposed. The dynamic reactive power balance model is established to show the interaction between the reactive power limitation of the wind farm and the reactive power compensation demand of the grid. This indicates the initial conditions of the active voltage coordinate control strategy. According to the critical operating point and the operation state of the DFIG, the active and reactive power coordinate control strategy composed of active ω-β coordinate control and active β control is proposed to enhance the reactive power support capability and stabilize the grid voltage. To compensate the active power shortage, an auxiliary control strategy based on the hybrid energy storage system is introduced. The simulation results show that the proposed strategy can suppress the voltage fluctuation effectively and make full use of primary energy.

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“…After careful analyses on the wind farm HVTO cases, there are mainly 3 conditions that can lead to overvoltage and HVTOs at wind farms. These conditions include: (1) when wind farms with the fixed reactive power compensation are partly disconnected due to a short-circuit fault [6], [7]; (2) when a HVDC commutation failure fault occurs [8], [9]; (3) when a HVDC block fault occurs [10], [11].…”

Section: Introductionmentioning

confidence: 99%

Complex Fault Source Identification Method for High-Voltage Trip-Offs of Wind Farms Based on SU-MRMR and PSO-SVM

et al. 2020

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Large-scale high-voltage trip-offs (HVTOs) of wind farms are serious incidents afflicting power systems that can lead to voltage instability, power deficiency, and frequency fluctuation. In order to reduce the influence of HVTOs, it is necessary to efficiently identify the fault source after an HVTO at a wind farm. A fault source identification method for wind farm HVTOs is proposed in this work. First, the fault tree analysis (FTA) method is used to summarize the causal and logical relationships among the different factors that lead to HVTOs at wind farms. An index system is constructed according to simulations of wind farm HVTOs under multiple scenarios. Second, a set of feature indices are selected from the original index system as key criteria for wind farm HVTOs based on the symmetrical uncertainty of mutual information and the maximum relevance and minimum redundancy (SU-MRMR) method. Finally, the particle swarm optimization (PSO) method is effectively utilized in the parameter optimization of support vector machine (SVM) method, and the optimized SVM with good performance is further employed for fault source identification based on the feature indices. Both single fault source and compound fault source are identified in an actual power system, and the proposed method is verified as a reliable solution for complex fault source identification for wind farm HVTOs based on the statistical identification accuracy. INDEX TERMS High-voltage trip-offs (HVTOs), fault source identification, SU-MRMR method, feature index, PSO method, SVM method.

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The mechanism of DFIGs grouping tripped off from power grid

Cited by 13 publications

References 0 publications

An Analytical method for detecting instability in grid‐connected doubly‐fed induction generator

An Analytical method for detecting instability in grid‐connected doubly‐fed induction generator

An Active Voltage Coordinate Control Strategy of DFIG-Based Wind Farm with Hybrid Energy Storage System

Complex Fault Source Identification Method for High-Voltage Trip-Offs of Wind Farms Based on SU-MRMR and PSO-SVM

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