Modifying Power Quality's Indices of Load by Presenting an Adaptive Method based on Hebb Learning Algorithm for Controlling DVR

Having electricity with high quality is one of the more important aims in electrical systems. Disturbances in distribution systems can change voltage waveform. There are some methods to prepare high power quality for sensitive loads. In this research we use “Dynamic Voltage Restorer” to compensate the harmful effects of disturbances on voltage. Since power systems fundamentally have complicated dynamic behavior, especially during faults, “Hebb” learning self-tuning controller, which is a powerful adaptive controller, has been used. In order to improve the performance of this controller from point of view of power quality's indices, such as flash and sensitive load voltage THD, a new structure is proposed for this controller with fuzzification method. Simulation results indicate better operation of the system for the case of proposed controller. Voltage sag and harmonics in faulty conditions are both improved by the proposed controller. According to simulation results, it works better than both classical PI controller and conventional Hebb learning controller.