**4.1 Fault types classification**

Usually, the types of power fault are classified accordingly such as a phase to ground, a phase to phase, two phases to ground and three-phase faults. Fig.7 shows ANFIS1 module

Fig. 7. A procedure in fault types classification

Fault Diagnosis in Power Distribution Network

practical system.

system

**4.2 Fault location identification** 

Using Adaptive Neuro-Fuzzy Inference System (ANFIS) 325

XY coordinate layout. The selected power distribution network is a 47 buses practical system. Then, by using the commercial software of PSS-ADEPT, the network is analyzed to record a post-fault 3-phase RMS current for each identified fault point. These points are fault location in XY coordinates for every feeder and radial lines including loads. The post-fault current data is used to train ANFIS1-1 to ANFIS1-10 modules according to respective target output that are integers 1 up to 10. The integers are representative of 10 types of fault. There are 163 selected coordinates for fault points with two fault resistors in the 47 buses practical power network. Therefore, it has about 2462 simulations in generating the data set. Table 2 shows a distribution data for training, testing and classifying the types of fault in the

Select the power distribution network

SIMULATION PROCESS Consider 10 types of fault with fault resistors of 30Ω and 40Ω (AG, BG, CG, 3P, AB, BC, CA, ABG, BCG and CAG)

Record post-fault 3-phase RMS current

Train the post-current as an input and the output in integer 1 to 10 for developing ANFIS1 module

Fig. 9. A procedure for developing ANFIS1 in fault types classification

**data set** 

ANFIS1-1 to ANFIS1-3 465 445 3 1 ANFIS1-4 177 157 3 1 ANFIS1-5 to ANFIS1-10 182 162 3 1 Table 2. The training and testing data for classifying the types of fault in a 47 buses practical

1 10

Referring to Fig.10, ANFIS2 and ANFIS3 are developed to identify fault location in respective X and Y coordinates. According to previous literature, most of the methods in identifying the fault location for power distribution network are in fault distance from a substation or zone. This approach considers geometrical coordinates in determining fault location in which it produces more accurate and precise fault location identification. From

**Trained data set** 

**Number of ANFIS input** 

**Number of ANFIS output** 

**ANFIS1 module Generated** 

development that is responsible for the task of predicting various types of fault in terms of integer 1 to 10 as follows, 1- red phase to ground fault (AG), 2 – yellow phase to ground fault (BG), 3 – blue phase to ground fault (CG), 4 – Three-phase fault (3P), 5 – red phase to yellow phase fault (AB), 6 – yellow phase to blue phase fault (BC), 7 – blue phase to red phase fault (CA), 8 – red and yellow phases to ground fault (ABG), 9 – yellow and blue phases to ground fault (BCG), 10 – blue and red phases to ground (CAG).
