Robust Power System Frequency Estimation Based on a Sliding Window Approach

Table 1

Steady-state estimation performance (MSE (dB)) of all the considered algorithms under different noise levels, achieved by averaging 500 independent trials.

SNR (dB)	80	70	60	50	40	30	20
3-sample approach [19]	-27.47	-17.40	-7.36	2.61	13.73	22.69	30.17
4-sample approach [22]	-30.73	-20.70	-10.72	-0.70	9.61	20.82	28.19
1-phase Wiener filter	-51.68	-41.64	-31.60	-21.61	-11.65	-1.48	9.68
1-phase LMS	-69.80	-59.76	-49.72	-39.63	-28.80	-14.10	4.52
1-phase extended Kalman filter [17]	-72.56	-62.52	-52.48	-42.45	-31.38	-18.11	1.31
1-phase recursive DFT [38]	-74.84	-64.81	-54.77	-44.74	-33.52	-20.21	-1.43
3-phase LMS	-74.77	-64.63	-54.67	-44.42	-32.21	-15.41	4.10