Aggregated models and transient performances of a mixed wind farm with different wind turbine generator systems

This paper proposes a genetic algorithm (GA)-based method for the aggregation of a mixed wind farm with different wind turbine generator system (WTGS) parameters, and discusses the transient performances of a grid-connected wind farm with a squirrel-cage induction generator (SCIG) and a doubly fed induction generator (DFIG). First, the transient models of a SCIG-based WTGS and DFIG-based WTGS are presented. Then, by using the GA to minimize the error of the output power between the aggregated single-generator model and the investigated wind farm, an aggregate method for a mixed farm is proposed and validated. The proposed method is shown to be superior to the traditional method with respect to the aggregation of a mixed wind farm in terms of different WTGS parameters. Finally, the transient performances of a mixed wind farm, including the output active power and the output voltage, are investigated by using the proposed method. The simulation results show that the transient behaviors of the mixed wind farm are closely related to the generator capacity ratio, the short-circuit capacity (SCC) ratio and the impedance ratio of the connected power system.

► Genetic algorithm optimization based method for aggregation of a mixed wind farm is proposed and validate.
► Traditional weighted aggregated method may be not suitable for the aggregation of wind farms with different SCIG parameters.
► The transient interaction between power system and a connected mixed wind farm with DFIG and SCIG is investigated.
► The SCC ratio and the impedance ratio impact the transient stability of the mixed wind farm.
► The impact is greater on a SCIG-based wind farm than on a DFIG-based wind farm.