抽象的

Fuzzy Neural Controller Based Dynamic Voltage Restorer Control for Power Quality Improvement

Abdul Jabbar Fathel Ali, Wael Hussein Zayer and Samhar S Shukir

Power quality is a measure of electrical power efficiency which is transmitted from the point of generation to the consumers. Power quality is a set of parameters like continuity of supply and characteristics of voltages such as magnitude, frequency, symmetry and waveform. Currently, power quality is a problem that leads to financial issues. Many surveys have been shown that poor power quality causes large economic losses to industrial sectors and large amount of power is wasted due to power quality problems like sags, swells, harmonics, flickers etc. In this paper, the modeling and simulation of a Dynamic Voltage Restorer (DVR) is achieved using MATLAB/Simulink. Faults are created with the proposed systems, and the disturbances are initiated at duration of 0.8 sec till 0.95 sec. Comparison of the performances of the Fuzzy neural and Fuzzy logic based DVR are presented. Results are showed that Fuzzy logic controller is able to restore the load voltage to the nominal value in both linear and nonlinear loads quickly and efficiently. But when the 2nd and 3rd harmonics are superimposed on the voltage sag and voltage swell by the application of 3-ph programmable source, the fuzzy logic controller fails to restore and reduce the harmonic content to acceptable values which is according to IEEE standard 3% for the individual voltage and 5% for the three phase voltage. While the Fuzzy neural controller has been very powerful and efficient to restore the load voltage to the pre-sag value and make it smooth under different cases of faults and nonlinear load conditions and keep the harmonics within the permissible limits in all cases.