symbolic dynamic models for highly varying power system loads

31
ST-B02: Here the Matlab inline function rand will generate a random number
uniformly distributed between 0 and 1. Therefore not many common points are expected
between the two signals and hence a low value of CSI. The value of CSI obtained was
0.1469.
ST-B03: In this test signal 1 is pure signal and signal 2 is contaminated with noise
having variable signal to noise ratio (S/N). Increasing S/N, it was found that CSI is also
increasing. When S/N is 1, it indicates that a significant amount of noise is present in the
signal and therefore a low value of CSI is expected. The value obtained in the test was
0.1242. When S/N is 10,000, it indicates that negligible amount of noise is present in the
signal. In other words the pure signal and the contaminated signal are almost identical.
The value of CSI obtained for this case was 0.5, which supports the claim that identical
signals have maximum value of CSI.
All the values have been tabulated in Table 3.4
ST-C01, ST-C02, and ST-C03: These tests are the same type of tests, belonging to
category C, for three different types of signals, namely, triangular, sinusoidal, and
sinusoidal contaminated with third and fifth harmonics. Since prediction of each future
value depends on random number generation, therefore three trials are reported here for
each test. Comparison of different parameters of the expected and forecasted signal has
been shown in Table 3.5.