Power ratings of modern wind turbines are aggressively increasing to reduce the levelized cost of energy. To cope with this trend, parallel power converters and their reliability enhancement techniques are becoming desirable. Model predictive control excels in parallel power converters by optimizing multiple objectives, including zero-sequence circulating current (ZSCC) suppression, current distortion minimization, and transient response improvement. However, its intrinsic fault tolerance cannot fully eliminate ZSCC amplitude elevation during faults, which obscure conventional diagnostic features and disable most classical fault diagnosis techniques. To address this limitation, we propose an open-circuit fault diagnosis method leveraging negative-sequence current analysis. This approach utilizes the sensitivity of negative-sequence components to asymmetrical currents caused by open-circuit faults, enabling rapid and accurate fault location even under ZSCC interference. Simulations validate the effectiveness of the proposed method.

Fault Diagnosis,model predictive control,negative-sequence current,parallel power converter