Page 213 - Decision Making Applications in Modern Power Systems

176 Decision Making Applications in Modern Power Systems

TABLE 6.4 Comparison of classification accuracy of power quality events
by different techniques.
Sl. no. Classification accuracy (%)
Power quality EMD HT ANN EMD HT PNN EMD HT SVC
events
S1 63 78 100
S2 60 72 94.4
S3 56 73 88.8
S4 66 76 94.4
S5 63 73 94.4

S6 59 78 88.8
S7 74 82 100
Overall efficiency 63% 76% 94%
EMD, Empirical mode decomposition; HT, Hilbert transform; PNN, probabilistic neural network.

TABLE 6.5 Comparison scheme.

Sl. no. Scheme Classification accuracy
of PQ events (%)

l [14] 93
2 [19] 90
3 [20] 89
4 [21] 90
5 [22] 93

6 Proposed one 94.4
(with EMD HT SVC)
EMD, Empirical mode decomposition; HT, Hilbert transform; PQ, power quality.

6.3.8 Conclusion
The first part of the chapter focuses on the efficient tracking estimation of
PQ disturbances by using adaptive filters, and the second part discusses a
novel approach for the detection of PQ events. It was concluded from the