• Energy Research
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Abstract Increasing wind power penetration into the grid justifies the requirement of the analysis of wind power dynamics, especially during transient faults. Quantitative transient stability (TS) assessment is required to provide deeper insight into the TS problems for speeding up the operational decision making process. This can be achieved by evaluating transient stability index (TSI) through the assessment of transient energy function. This paper carries out the quantitative insight of the impact of different generator technologies on the grid by comparatively studying the impacts of the fault clearing time, the grid coupling, the inertia constant, the generator terminal voltage sag and the slip on fault responses with the TSI between synchronous generators and wind turbine generators, such as squirrel cage induction generators and doubly fed induction generators.

Abstract A novel aggregated model for wind farms consisting of wind turbines equipped with doubly-fed induction generators (DFIGs) is proposed in this paper. In the proposed model, a mechanical torque compensating factor (MTCF) is integrated into a full aggregated wind farm model to deal with the nonlinearity of wind turbines in the partial load region and to make it behave as closely as possible to a complete model of the wind farm. The MTCF is initially constructed to approximate a Gaussian function by a fuzzy logic method and optimized on a trial and error basis to achieve less than 10% discrepancy between the proposed aggregated model and the complete model. Then, a large scale offshore wind farm comprising of 72 DFIG wind turbines is used to verify the effectiveness of the proposed aggregated model. The simulation results show that the proposed aggregated model approximates active power (Pe) and reactive power (Qe) at the point of common coupling more accurately than the full aggregated model by 8.7% and 12.5%, respectively, during normal operation while showing similar level of accuracy during grid disturbance. Computational time of the proposed aggregated model is slightly higher than that of the full aggregated model but much faster than the complete model by 90.3% during normal operation and 87% during grid disturbance.