Improved Park Inverse Transform Algorithm for Positive and Negative Sequence Separation of Grid Voltage under Unbalanced Grid Conditions

When an asymmetrical short-circuit fault occurs in the three-phase grid voltage, it is necessary to quickly and effectively detect the grid voltage characteristic information, such as the amplitude of the fundamental positive and negative sequence voltage components, the grid frequency, and the output phase. Aiming at the traditional grid voltage positive and negative sequence fundamental wave component detection algorithm, there are problems such as anti-harmonic interference difference and slow detection speed. This paper proposes a detection algorithm based on Park inverse transform under asymmetric conditions. Based on the establishment of the grid voltage fault model, the proposed detection method uses two orthogonal generators based on Park inverse transform to generate two sets of mutually orthogonal voltage components, and then performs the fundamental wave through the three-phase grid voltage positive and negative sequence calculation module. The positive and negative sequence voltages of the voltage components are separated, and the frequency calculation module performs frequency calculation using the fundamental component of the voltage signal and its 90-degree phase shift component. The simulation results and experiments show that the proposed detection algorithm can detect positive and negative sequence amplitude and grid frequency variation in a grid period with low harmonics and three-phase voltage imbalance, which can effectively make up for the shortcomings of traditional methods.