Amendment PI Control Approach Created on a Neural Network for an Active Harmonic Compensator

Direct power control (DPC) is attracting wide attention throughout the world outstanding to its merits of simple construction, rapid dynamic reaction, and strong robustness against parameter variations. The establishment of a switching table is the key aspect of DPC, and so far, there are various switching tables in the literature. However, they differ in the sector division and vector selection. The simulation results verify that the improved DPC using the neural network ANN method has a more satisfactory compensation effect when the grid voltage is under distorted and unbalanced circumstances, and it proves that the ANN method is correct and superior. Improved DPC achieves control of active power and its dynamic performance. The good compensation of reactive power using the adaptive ANN method results in low ripple.