Parameter identification of a wind generator unit RMS model using sparse grid optimization algorithm

Abstract

This paper presents a global sparse grid optimization algorithm applied in parameter identification of a wind generation Root Mean Square (RMS) phasor model. The details of vendor specific RMS models used in dynamic simulation software (e.g. PSSE) are not provided by manufacturers. Therefore, there is a need to develop a procedure which can convert vendor specific models to standardized generic models (e.g. International Electrotechnical Commission model, IEC model). The procedure we propose, identifies the parameters of the IEC generic model using dynamic response of a given vendor specific model as input. The IEC model parameters can be found and dynamic response of the vendor model can be approximated with sufficient accuracy. In the simulation example we show that the parameter identification based on the global sparse grid optimization algorithm is effective in converting a vendor specific model to a standardized generic model.