A Multi-Machine Equivalent Model of a Wind Farm Considering LVRT Characteristic and Wake Effect
Akhilesh Prakash Gupta, Arindam Mitra, Abheejeet Mohapatra, S. N. Singh
Abstract
The wind turbines (WTs) present in a wind farm (WF) are subjected to varying wind speeds owing to the wake effect. Additionally, the response of a WF is also affected by the low voltage ride-through (LVRT) characteristic imbibed in each doubly-fed induction generator (DFIG) of WF. Consequently, for deriving an equivalent of a large WF, consideration of wake effect and LVRT are crucial. In this paper, a three-step WF aggregation is proposed. Firstly, various wind scenarios from historical wind data are taken, and the Weibull-based probabilistic and wake effect models are developed. Secondly, WTs’ clusters based on their LVRT activation status are obtained. In the final step, the WTs are aggregated based on the pre-fault wind speed, and a multi-machine dynamic equivalent model is developed. Also, a new collector network transformation method is proposed. Various low voltage cases are simulated on a 40 MW test WF at different wind conditions. A comparison of the responses from the proposed equivalent model and the detailed model of the test WF indicates the efficacy of the proposed multi-machine model. A comparison of the errors in responses confirms the superiority of the proposed model over the previous relevant works.