Review of <scp>DFIG</scp> wind turbine impact on power system dynamic performances

Ngamroo, Issarachai

doi:10.1002/tee.22379

Cited by 49 publications

(34 citation statements)

References 117 publications

(141 reference statements)

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“…The DFIG effect on power system dynamics is divided into four main categories which are voltage stability, small-signal stability, transient stability, and frequency stability [16]. Voltage stability is defined as the capability of power systems to maintain nominal voltages at all buses after disturbances.…”

Section: E Dfig-based Wecs Effects On Power Systemsmentioning

confidence: 99%

Grid Ancillary Services From Doubly Fed Induction Generator-Based Wind Energy Conversion System: A Review

Debouza

Al‐Durra

2019

IEEE Access

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Modern electrical grids face serious challenges to maintain healthy operational conditions. The nominal voltage and frequency, for instance, are affected by huge load changes and renewable energy integration. Renewable energy conversion systems are traditionally installed to provide active power. Fortunately, advanced renewable energy conversion systems have the ability to provide other facilities such as reactive power control and harmonic mitigation. In fact, recent grid codes obligate renewable energy systems to serve other duties such as generating reactive power rather than just simply supply active power, participate in fault ride through, for instance. This paper presents a comprehensive study on the doubly fed induction generator (DFIG)-based wind energy conversion system (WECS), which provides ancillary services to the grid along with performing its regular duties. These services include reactive power control, voltage ride through, power quality improvement, frequency control, and power oscillation damping. The literature survey and comparative studies show that the DFIG-based WECS has the ability to support electrical grid during normal and transient conditions, and it can also help in the large-scale renewable energy penetration to the power grid. The effect of different industrial and nonlinear controllers on DFIG performance in extracting grid ancillary services is highlighted. INDEX TERMS Doubly fed induction generator (DFIG), frequency control, grid ancillary services, power oscillation damping, power quality improvement, reactive power control, voltage ride through, wind energy conversion system (WECS).

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Section: E Dfig-based Wecs Effects On Power Systemsmentioning

confidence: 99%

Grid Ancillary Services From Doubly Fed Induction Generator-Based Wind Energy Conversion System: A Review

Debouza

Al‐Durra

2019

IEEE Access

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“…The dynamic performance evaluation and stability analysis of DFIG with their control techniques in WIPS has been analysed by many researchers as presented in [6,9]. Most of these have presented the advantage of independent control, a consequence of grid disturbance and WECS on interconnected power systems as well as maximum power point tracking (MPPT) and fault ride through behaviour.…”

Section: Introductionmentioning

confidence: 99%

Analysis and enhancement of small‐signal stability on DFIG‐based wind integrated power system through the optimal design of linear quadratic regulator

Kumar

Chatterjee

2020

IET Renewable Power Generation

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This study analyses the dynamic behaviour of a doubly fed induction generator (DFIG)-based wind integrated power system (WIPS) resulting from a major disturbance. The effects of transient disturbance on WIPS are examined without and with a controller in terms of performance and stability of the system. To enhance the performance of WIPS after a sudden disturbance, an optimally designed linear quadratic regulator (LQR) controller is applied to the system. The wind energy system is described in state-space representation, whose states and outputs are taken as feedback to the controller for improving their dynamic response. An artificial bee colony (ABC)-based swarm optimisation technique is used to evaluate the optimal weighting matrices of the LQR controller in parallel with minimising the performance index and dynamic response characteristics of the system. The effectiveness of the proposed ABC-LQR controller in WIPS is verified by comparing their simulation and numerical results with standard proportional-integral and LQR controllers. It indicates that the proposed controller provides better enhancement of dynamic response as compared with other controllers in terms of performance index and dynamic response characteristics. Moreover, the robustness and stability of various system configurations are tested by the eigenvalue analysis.

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“…Wind power generation has become one of the most important renewable energy power generation technologies in the world (Marugan et al, 2018;Tian et al, 2018a). However, it is found that the randomness of wind speed has a serious impact on the stability of power system after grid connection (Ngamroo, 2017). At present, there are two ways to solve this problem: the first one is to increase the installed capacity of wind power and the rotating reserve capacity of conventional units to restrain the impact of wind power system on the grid, but this will increase the operating costs of the system (Koivisto et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Short-term wind speed forecasting based on autoregressive moving average with echo state network compensation

2019

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In order to improve the forecasting accuracy of short-term wind speed, a forecasting method based on autoregressive moving average with echo state network compensation is proposed in this article. First, the linear and nonlinear characteristics of short-term wind speed can be determined by Brock–Dechert–Scheinkman statistics method. Then, autoregressive moving average model is used for modeling and to forecast the linear component of short-term wind speed. The linear component of short-term wind speed sequence is obtained. Artificial bee colony algorithm–optimized echo state network model is used as the forecasting model of forecasting error sequences with the nonlinear characteristic. Finally, the final forecasting value is obtained by adding forecasting values of autoregressive moving average model and forecasting error values of echo state network model. k-fold cross-validation is used to improve the generalization ability of the forecasting model. The simulation comparison results show that the proposed forecasting method has higher prediction accuracy with the smaller prediction error. The forecasting indicators are also better than other forecasting methods.

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Review of DFIG wind turbine impact on power system dynamic performances

Cited by 49 publications

References 117 publications

Grid Ancillary Services From Doubly Fed Induction Generator-Based Wind Energy Conversion System: A Review

Grid Ancillary Services From Doubly Fed Induction Generator-Based Wind Energy Conversion System: A Review

Analysis and enhancement of small‐signal stability on DFIG‐based wind integrated power system through the optimal design of linear quadratic regulator

Short-term wind speed forecasting based on autoregressive moving average with echo state network compensation

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