**5. The result of fault diagnosis**

332 Fuzzy Inference System – Theory and Applications

data has about 5487 lines which includes 63 CBs and 30 LIs in the practical system. Each line consists of three rows including X, Y coordinates and the integer '1' or '0' represents an operational state of CB and LI. The point coordinates are the input signal to the ANFIS4 whereas the integer is the output. Due to the 93 devices for all CBs and LIs, the ANFIS4 modules should be developed regarding to the numbers of the device. Thus, the modules are labeled as ANFIS4-1 to ANFIS4-63 for all CBs and followed by ANFIS4-64 to ANFIS4-93 for all LIs. Table 5 shows a distribution of the data set for each module to

Select a power distribution network

Collect a data of operational states of CB and LI for each fault point

Distribute the data as follows: Input data – Fault points in terms of XY coordinate

> Train the data to develop ANFIS4 module for power restoration plan

ANFIS4-1 ANFIS4-63 ANFIS4-64 ANFIS4-93

Output data – Operational states of CB and LI

Fig. 16. A procedure for developing ANFSI4 module in power restoration plan

**data set** 

Table 5. A distribution of the data set for power restoration plan

**Trained data set** 

ANFIS4-1 80 59 2 1 " " 2 1 " " 2 1 ANFIS4-93 " " 2 1

**Number of ANFIS input** 

Line isolator LI1……………LI30

> **Number of ANFIS output**

**ANFIS1 module Generated** 

Circuit breaker CB1……………CB63

train them.

Fault diagnosis performance is measured through a precision and accuracy of ANFIS prediction. The measurement is in percentage error for ANFIS1, ANFIS2 and ANFIS3 while in absolute error for ANFIS4. The 47 buses practical system is used to test the ANFISs. The prediction results from ANFIS1, ANFIS2 and ANFIS3 are presented for practical systems that consist of 1232 test data sets. Meanwhile, ANFIS4 predicts about 2743 test data sets for the same system. The number of test data set is taken from 50% of overall data training.
