Qing Li / State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems
Shouhong Feng / Northwestern Polytechnical University
Weilin Li / Northwestern Polytechnical University
Ziyu Chen / State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems
As the controllability of power electronic devices associated with wind turbines leads to a variety of fault characteristics, fault detection for power system with wind turbine has become a serious challenge. The theory of information entropy can quantify the degree of system uncertainty which has achieved good application results in the field of feature extraction and fault detection for power system. This paper proposed a solution to detect faults through transfer entropy algorithm. Firstly, the fundamentals of the algorithm is introduced. Then the algorithm is implemented on the field testing data of wind turbine fault ride through, and the details of parameter optimization is described. Finally, the adaptability of transfer entropy is studied considering different wind turbine capacities, controller models and different gird faults. This study provides theoretical and practical basis for the application of transfer entropy algorithm in the field of feature extraction and fault detection for power system.