Automatic Implementation of Fuzzy Reasoning Spiking Neural P Systems for Diagnosing Faults in Complex Power Systems

Pseudocode 2

The modeling suspicious fault components with FRSN P system algorithm.

Input: Suspicious fault component logic diagram adjacent matrix , Information about each component node and breaker

node in the logic diagram

Output: The fuzzy truth values of the input proposition neurons

1: Set stop condition: All outgoing line directions of the suspicious fault component logic diagram are access completed;

2: Set Initialize state: Set initialize access outgoing line direction number , set all outgoing line directions number of

suspicious fault component ;

3: while ()  do

4:for each associated protection of suspicious fault components   do

5:if associated protection is the main protection then

6: query the protection database, obtain breaker ID number that should be tripped when protection is active;

7: for the must trip breaker when main protection action do

8: if is the breaker in the outgoing line direction   then

9:According to the operation information of breaker and protection set the fuzzy truth value vector ;

10:end if

11: end for

12: else associated protection is the backup protection then

13: query the protection database, obtain breaker ID number that should be tripped when protection is active;

14: for the must trip breaker when backup protection action do

15: if is the breaker in the outgoing line direction   then

16: According to the operation information of breaker and protection set the fuzzy truth value vector;

17: end if

18: end for

19:end if

20:;

21:end for

22: end while