Suppressing output power fluctuation and improving FRT Capability of DFIG‐based wind energy conversion system with SMES and dual‐mode protection scheme

With large-scale wind farms connected to AC/DC network, the transient stability assessment (TSA) of the power system becomes more and more difficult. Among them, estimating the region of attraction (ROA) of the equilibrium point is a traditional but still challenging problem. Based on the Lyapunov stability theory, this paper proposes a new approach to obtain the enlarged estimation of the ROA. The optimization and updating strategy of shape function in the sum of squares (SOS) optimization problem are studied to reduce the conservatism of estimation result. In the proposed method, the gravitational search algorithm (GSA) is employed to optimize the coefficients of initial shape function to improve estimation performance. Based on the time-domain simulation (TDS) of expected faults, the fitness value for shape function optimization is calculated using the values of state variables at the fault clearing time and the system stability information. Furthermore, the optimal Lyapunov function is computed by introducing the update condition of shape function and adjusting the iteration strategy of the ROA estimation algorithm. Finally, the proposed method is applied to a two-machine-infinite-bus system and a more complex nine-bus AC/DC system with wind power. And the effectiveness of the proposed method is verified by comparing with the existing ROA estimation methods.

Section: Introductionmentioning

confidence: 99%

A Lyapunov approach based on gravitational search algorithm for transient stability assessment of AC/DC systems with wind power

Xie

Zhang

Zhou

et al. 2023

“…Among other alternatives to fossil fuels, wind energy has become the most promising choice due to some intriguing speed operation, lower mechanical stress on the WT and distinguished control mechanism of active and reactive power [8,9]. Apart from such attractive features of DFIG, it suffers from instability problem on the occurrence of grid faults due to the direct integration of its stator windings to the grid.…”

Section: Introductionmentioning

confidence: 99%

“…The doubly‐fed induction generator (DFIG) operates on variable speed, which is one of the most popular generators used in wind power harvesting. The DFIG possesses plenty of advantages, such as higher output power, improved efficiency, variable speed operation, lower mechanical stress on the WT and distinguished control mechanism of active and reactive power [8, 9]. Apart from such attractive features of DFIG, it suffers from instability problem on the occurrence of grid faults due to the direct integration of its stator windings to the grid.…”

Section: Introductionmentioning

confidence: 99%

Protecting DFIG‐based multi‐machine power system under transient‐state by nonlinear adaptive backstepping controller‐based capacitive BFCL

Hossain

Islam

Haque

et al. 2022

The invention of doubly‐fed induction generator (DFIG) brings the wind energy one step ahead as renewable power generation. But the performance of the grid‐connected DFIGs are greatly affected by grid disturbances as their stator windings are interfaced to the grid directly. Different fault current limiters are capable of improving fault ride through capability during short circuit faults. Nonlinear controller based fault current limiters (FCLs) are superior to deal with the nonlinearity of the power systems. This paper proposes a nonlinear adaptive backstepping controller (ABSC) based capacitive bridge‐type FCL (CBFCL) to enhance the fault ride through capability of a DFIG‐based wind farm connected to a multi‐machine power system. At first, a complete modelling of the CBFCL is derived to understand its behaviour during the normal and fault period more accurately. Then, the ABSC is designed based on that dynamic model, along with the backstepping controller (BSC) and sliding mode controller (SMC) for comparison purpose. Finally, the performance of the ABSC to control the CBFCL has been analysed and verified by comparing with that of the BSC and the sliding mode controller. All the graphical and mathematical analyses favour the ABSC based CBFCL under symmetrical and asymmetrical fault (both temporary and permanent) scenarios.

“…During normal operations, a DFIG can generate the maximum power using the maximum power point tracking (MPPT) technique [5]. However, the terminal voltage of the DFIG would experience a dip when either symmetric or asymmetric grid faults occur, resulting in an overcurrent situation at the DFIG rotor and increased capacitor DC-link voltage [6,7]. According to grid codes, a wind generator needs to have the capability to ride through grid faults for a period of time to maintain system stability and prevent wider collapse [8].…”

Section: Introductionmentioning

confidence: 99%

Improving DFIG performance under fault scenarios through evolutionary reinforcement learning based control

Gao

Fan

Huang

et al. 2022

The doubly fed induction generator (DFIG) usually experiences high rotor current and DC capacitor link voltage spikes during system fault events. In this paper, a novel data‐driven approach is proposed to enhance DFIG performance under fault scenarios. An advanced reinforcement learning algorithm called guided surrogate‐gradient‐based evolution strategy (GSES) is used to control the DFIG power and capacitor DC‐link voltage by adjusting the optimal reference signals. This controller is able to prevent the DFIG rotor from over‐current risk and maintain grid‐connected operation. The proposed GSES‐based control algorithm was evaluated through simulations on a 3.6‐MW DFIG in the PSCAD/EMTDC software. Results have validated the effectiveness of the proposed GSES‐based control algorithm in improving DFIG performance under various fault scenarios.