ISSN: 1813-0410

Keywords : ANFIS

Comprehensive Faults Classification Method for Unbalanced Power Distribution Systems

Shamam Fadhil Alwash

journal of kerbala university, Volume 14, Issue 1, Pages 396-406

Unbalanced power distribution systems experience single faults and compound faults types. The classification of these faults is considered as one of the most important requirements for the fault analysis and the fault location techniques. However, existing methods for fault classification have been formulated to consider only single-fault types. This paper presents a comprehensive faults classification method for unbalanced power distribution systems. In this method, new fault classification indices are derived to consider all fault types including the compound-fault ones. The values of these indices are determined based on the transient analysis of the current signals using discrete wavelet transform (DWT). These indices are utilized in conjunction with adaptive neural-fuzzy inference systems (ANFIS) to classify all fault types. In order to verify the accuracy of the proposed method, a practical distribution system is used to test the method under different fault conditions.

Fuzzy Neural Design of Power Systems Stabilizers

Ibrahim F Jasim

journal of kerbala university, Volume 5, Issue 3, Pages 333-345

This paper presents a new approach of designing the Power Systems Stabilizer (PSS) that is based on fuzzy neural system. Adaptive Network based Fuzzy Inference System (ANFIS) is utilized in constructing the Fuzzy Neural Power Systems Stabilizer (FNPSS). The employment of ANFIS enables the system avoiding defects caused when using fuzzy logic and neural networks individually in designing an efficient PSS. Single Machine Infinite Bus (SMIB) power system has been taken as a case study to evaluate the suggested strategy performance. Simulation results have been conducted to confirm the approach validity.