Modeling Method for Wind Farm Based on Equivalent Dynamic Response

The connection of large wind farms has a significant impact on the stability of the power system. It is of great significance to construct equivalent models and identify parameters for wind farms to improve simulation speed and accuracy. In this paper, a dynamic equivalent model and initialization method for permanent magnet synchronous generators (PMSG) based wind farms were first established. Then, based on the measured data at the common connection point of the wind farm, a hybrid algorithm of genetic learning particle swarm optimization (GLPSO) was proposed for parameter identification of the electrical and control systems of the wind farm, while other parameters were fixed using aggregation or typical values strategies. The effectiveness and accuracy of the proposed modeling method was verified by compared it to the detail model.