ANALYSIS OF INFLUENCE OF POWER QUALITY DISTURBANCES USING A NEURO-FUZZY SYSTEM

The authors propose an automated neuro-fuzzy system approach (with neural network subsystem) to power quality assessment incorporating equipment susceptibility patterns. The system is expected to handle dependencies between superposition of different disturbances and specific devices ’ susceptibility to disturbances. Two neural network architectures were applied: a well known radial-basis neural networks for automatic rules’ generation and a neuro-fuzzy system for overlaid disturbances influence modeling. Proposed approach can help to predict damages or abnormal functioning of devices and implement adequate countermeasures

Power Distortion Issues in Wind Turbine Power Systems Under Transient States

In this paper time-frequency methods have been investigated for complex investigations of transient states in wind power plants. Application of parallel processing in time and frequency domain brought new findings in description of wind power plants working under transient conditions. Proposed algorithms represents standard Short-Time Fourier Transform (STFT) as well as alternative methods associated with Cohen’s class: Choi-Williams Distribution (CWD) and Zhao-Atlas-Marks Distribution (ZAMD). In order to explore advantages and disadvantages of the method several experiments were performed using model of squirrel-cage induction machine connected directly to the grid. Investigated phenomena concerned power distortion caused by switching-on capacitor banks and faults as well as influence of wind speed on instantaneous character of the transient states. Key Words: Power quality, power system harmonics, time-frequency analysis, wind power plants. 1