An Artificial Neural Network Controller for Three-level Shunt Active Filter to Eliminate the Current Harmonics and Compensate Reactive Power

The increased use of nonlinear devices in the industry has resulted in the direct increase of harmonic distortion in power systems during these last years. Active filter systems are proposed to mitigate current harmonics generated by nonlinear loads. The conventional scheme based on a two-level voltage source inverter controlled by a hysteresis controller has several disadvantages and cannot be used for medium or high-power applications. To overcome these drawbacks and improve the APF performance, there’s a great tendency to use multilevel inverters controlled by intelligent controllers. Three level (NPC) inverter is one of the most widely used topologies in various industrial applications such as machine drives and power factor compensators. On the other hand, artificial neural networks are under study and investigation in other power electronics applications. In order to gain the advantages of the three-level inverter and artificial neural networks and to reduce the complexity of classical control schemes, a new active power filter configuration controlled by two MLPNN (Multi-Layer Perceptron Neural Network) is proposed in this paper. The first ANN is used to replace the PWM current controller, and the second one to maintain a constant dc link voltage across the capacitors and compensate the inverter power losses. The performance of the global system, including power and control circuits is evaluated by Matlab-Simulink and SimPowerSystem Toolbox simulation. The obtained results confirm the effectiveness of the proposed control scheme.