Multi-Machine Equivalent Modeling Method of Wind Farm Considering Multi-Clustering Indexes Such as Ambient Temperature

Considering the limitations of the wind farm's single-machine equivalent model to accurately represent the operational characteristics of a wind farm, as well as the issue of neglecting environmental factors when selecting clustering indices during the establishment of a multi-machine equivalent model. A multi-machine equivalent modeling method of wind farm is proposed, which takes wind speed, output power and unit ambient temperature as clustering indexes, and combines Canopy algorithm and K-Means++ clustering algorithm. Taking the measured data of a wind farm as a sample, an example analysis is carried out to verify the accuracy of the multi-machine equivalent model and the feasibility of the proposed modeling method.