Neural Predictive Model Control for Intelligent Universal Transformers in Advanced Distribution Automation of Tomorrow

Intelligent Universal Transformer (IUT) is a key point introducing as an Intelligent Electrical Devices (IED) for Advanced Distribution Automation (ADA) in future. ADA is the state of art, comprising flexible electrical architecture contributed with open communication construction for the tomorrow’s distribution automation. IUT is based on a power electronic transformer employing the new technology of high voltage-low current solid-State devices to cope with the current transformer deficiencies. Solid-State devices in IUT topology Including rectifiers, converters and PWM inverters in input output stages which will be controlled trough the intelligent control fashion leads to robust control strategy. In this regards predictive control technique using artificial neural networks investigated for a three phase power PWM converters with current and voltages regulators. Neural Predictive Controller (NPC) is realized for a non linear optimizer, equipping Focused Time Delay Neural Network (FTDNN) for system modeling and optimization procedure. For prediction and control two strategic parts are considered. The first is FTDNN carrying out for power inverter dynamics system model and the other is optimizer unit subjected for minimizing the optimization index for performing the duty cycle of inverters as a control signals. In this approach NPC current source and voltage source controllers in input output stage of proposed four layers IUT topology results the smooth regulation in IUT output voltages and input current and improve the system characteristics under load and source disturbances. Key-Words: ADA, IUT, IED, power electronic, DER, NPC, ANN